* Homepage: <https://opencv.org>
* Courses: <https://opencv.org/courses>
-* Docs: <https://docs.opencv.org/master/>
+* Docs: <https://docs.opencv.org/4.x/>
* Q&A forum: <https://forum.opencv.org>
* previous forum (read only): <http://answers.opencv.org>
* Issue tracking: <https://github.com/opencv/opencv/issues>
self.blender.prepare(dst_sz)
def feed(self, img, mask, corner):
- """https://docs.opencv.org/master/d6/d4a/classcv_1_1detail_1_1Blender.html#a64837308bcf4e414a6219beff6cbe37a""" # noqa
+ """https://docs.opencv.org/4.x/d6/d4a/classcv_1_1detail_1_1Blender.html#a64837308bcf4e414a6219beff6cbe37a""" # noqa
self.blender.feed(cv.UMat(img.astype(np.int16)), mask, corner)
def blend(self):
- """https://docs.opencv.org/master/d6/d4a/classcv_1_1detail_1_1Blender.html#aa0a91ce0d6046d3a63e0123cbb1b5c00""" # noqa
+ """https://docs.opencv.org/4.x/d6/d4a/classcv_1_1detail_1_1Blender.html#aa0a91ce0d6046d3a63e0123cbb1b5c00""" # noqa
result = None
result_mask = None
result, result_mask = self.blender.blend(result, result_mask)
class CameraAdjuster:
- """https://docs.opencv.org/master/d5/d56/classcv_1_1detail_1_1BundleAdjusterBase.html""" # noqa
+ """https://docs.opencv.org/4.x/d5/d56/classcv_1_1detail_1_1BundleAdjusterBase.html""" # noqa
CAMERA_ADJUSTER_CHOICES = OrderedDict()
CAMERA_ADJUSTER_CHOICES['ray'] = cv.detail_BundleAdjusterRay
class WaveCorrector:
- """https://docs.opencv.org/master/d7/d74/group__stitching__rotation.html#ga83b24d4c3e93584986a56d9e43b9cf7f""" # noqa
+ """https://docs.opencv.org/4.x/d7/d74/group__stitching__rotation.html#ga83b24d4c3e93584986a56d9e43b9cf7f""" # noqa
WAVE_CORRECT_CHOICES = OrderedDict()
WAVE_CORRECT_CHOICES['horiz'] = cv.detail.WAVE_CORRECT_HORIZ
WAVE_CORRECT_CHOICES['vert'] = cv.detail.WAVE_CORRECT_VERT
)
def feed(self, *args):
- """https://docs.opencv.org/master/d2/d37/classcv_1_1detail_1_1ExposureCompensator.html#ae6b0cc69a7bc53818ddea53eddb6bdba""" # noqa
+ """https://docs.opencv.org/4.x/d2/d37/classcv_1_1detail_1_1ExposureCompensator.html#ae6b0cc69a7bc53818ddea53eddb6bdba""" # noqa
self.compensator.feed(*args)
def apply(self, *args):
- """https://docs.opencv.org/master/d2/d37/classcv_1_1detail_1_1ExposureCompensator.html#a473eaf1e585804c08d77c91e004f93aa""" # noqa
+ """https://docs.opencv.org/4.x/d2/d37/classcv_1_1detail_1_1ExposureCompensator.html#a473eaf1e585804c08d77c91e004f93aa""" # noqa
return self.compensator.apply(*args)
**kwargs):
if matcher_type == "affine":
- """https://docs.opencv.org/master/d3/dda/classcv_1_1detail_1_1AffineBestOf2NearestMatcher.html""" # noqa
+ """https://docs.opencv.org/4.x/d3/dda/classcv_1_1detail_1_1AffineBestOf2NearestMatcher.html""" # noqa
self.matcher = cv.detail_AffineBestOf2NearestMatcher(**kwargs)
elif range_width == -1:
- """https://docs.opencv.org/master/d4/d26/classcv_1_1detail_1_1BestOf2NearestMatcher.html""" # noqa
+ """https://docs.opencv.org/4.x/d4/d26/classcv_1_1detail_1_1BestOf2NearestMatcher.html""" # noqa
self.matcher = cv.detail.BestOf2NearestMatcher_create(**kwargs)
else:
- """https://docs.opencv.org/master/d8/d72/classcv_1_1detail_1_1BestOf2NearestRangeMatcher.html""" # noqa
+ """https://docs.opencv.org/4.x/d8/d72/classcv_1_1detail_1_1BestOf2NearestRangeMatcher.html""" # noqa
self.matcher = cv.detail.BestOf2NearestRangeMatcher_create(
range_width, **kwargs
)
class SeamFinder:
- """https://docs.opencv.org/master/d7/d09/classcv_1_1detail_1_1SeamFinder.html""" # noqa
+ """https://docs.opencv.org/4.x/d7/d09/classcv_1_1detail_1_1SeamFinder.html""" # noqa
SEAM_FINDER_CHOICES = OrderedDict()
SEAM_FINDER_CHOICES['dp_color'] = cv.detail_DpSeamFinder('COLOR')
SEAM_FINDER_CHOICES['dp_colorgrad'] = cv.detail_DpSeamFinder('COLOR_GRAD')
self.finder = SeamFinder.SEAM_FINDER_CHOICES[finder]
def find(self, imgs, corners, masks):
- """https://docs.opencv.org/master/d0/dd5/classcv_1_1detail_1_1DpSeamFinder.html#a7914624907986f7a94dd424209a8a609""" # noqa
+ """https://docs.opencv.org/4.x/d0/dd5/classcv_1_1detail_1_1DpSeamFinder.html#a7914624907986f7a94dd424209a8a609""" # noqa
imgs_float = [img.astype(np.float32) for img in imgs]
return self.finder.find(imgs_float, corners, masks)
-https://github.com/opencv/opencv_extra/tree/master/testdata/stitching
+https://github.com/opencv/opencv_extra/tree/4.x/testdata/stitching
s1.jpg s2.jpg
boat1.jpg boat2.jpg boat3.jpg boat4.jpg boat5.jpg boat6.jpg
sizes = []
blender = None
timelapser = None
- # https://github.com/opencv/opencv/blob/master/samples/cpp/stitching_detailed.cpp#L725 ?
+ # https://github.com/opencv/opencv/blob/4.x/samples/cpp/stitching_detailed.cpp#L725 ?
for idx, name in enumerate(img_names):
full_img = cv.imread(name)
if not is_compose_scale_set:
)
def initialize(self, *args):
- """https://docs.opencv.org/master/dd/dac/classcv_1_1detail_1_1Timelapser.html#aaf0f7c4128009f02473332a0c41f6345""" # noqa
+ """https://docs.opencv.org/4.x/dd/dac/classcv_1_1detail_1_1Timelapser.html#aaf0f7c4128009f02473332a0c41f6345""" # noqa
self.timelapser.initialize(*args)
def process_and_save_frame(self, img_name, img, corner):
def update_scale(self, scale):
if scale is not None and scale != self.scale:
- self.warper = cv.PyRotationWarper(self.warper_type, scale) # setScale not working: https://docs.opencv.org/master/d5/d76/classcv_1_1PyRotationWarper.html#a90b000bb75f95294f9b0b6ec9859eb55
+ self.warper = cv.PyRotationWarper(self.warper_type, scale) # setScale not working: https://docs.opencv.org/4.x/d5/d76/classcv_1_1PyRotationWarper.html#a90b000bb75f95294f9b0b6ec9859eb55
self.scale = scale
@staticmethod
needSoftmax = false;
// url for label file, can from local or Internet
-labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt";
+labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt";
</script>
<script id="codeSnippet1" type="text/code-snippet">
"std": "1",
"swapRB": "false",
"needSoftmax": "false",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt",
"modelUrl": "http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel",
"configUrl": "https://raw.githubusercontent.com/BVLC/caffe/master/models/bvlc_alexnet/deploy.prototxt"
},
"std": "0.007843",
"swapRB": "false",
"needSoftmax": "true",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt",
"modelUrl": "https://drive.google.com/open?id=0B7ubpZO7HnlCcHlfNmJkU2VPelE",
"configUrl": "https://raw.githubusercontent.com/shicai/DenseNet-Caffe/master/DenseNet_121.prototxt"
},
"std": "1",
"swapRB": "false",
"needSoftmax": "false",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt",
"modelUrl": "http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel",
"configUrl": "https://raw.githubusercontent.com/BVLC/caffe/master/models/bvlc_googlenet/deploy.prototxt"
},
"std": "1",
"swapRB": "false",
"needSoftmax": "false",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt",
"modelUrl": "https://raw.githubusercontent.com/forresti/SqueezeNet/master/SqueezeNet_v1.0/squeezenet_v1.0.caffemodel",
"configUrl": "https://raw.githubusercontent.com/forresti/SqueezeNet/master/SqueezeNet_v1.0/deploy.prototxt"
},
"std": "1",
"swapRB": "false",
"needSoftmax": "false",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt",
"modelUrl": "http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_19_layers.caffemodel",
"configUrl": "https://gist.githubusercontent.com/ksimonyan/3785162f95cd2d5fee77/raw/f02f8769e64494bcd3d7e97d5d747ac275825721/VGG_ILSVRC_19_layers_deploy.prototxt"
}
needSoftmax = false;
// url for label file, can from local or Internet
-labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt";
+labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt";
</script>
<script id="codeSnippet1" type="text/code-snippet">
needSoftmax = false;
// url for label file, can from local or Internet
-labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt";
+labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt";
</script>
<script id="codeSnippet1" type="text/code-snippet">
outType = "SSD";
// url for label file, can from local or Internet
-labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/object_detection_classes_pascal_voc.txt";
+labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/object_detection_classes_pascal_voc.txt";
</script>
<script id="codeSnippet1" type="text/code-snippet">
"std": "0.007843",
"swapRB": "false",
"outType": "SSD",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/object_detection_classes_pascal_voc.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/object_detection_classes_pascal_voc.txt",
"modelUrl": "https://raw.githubusercontent.com/chuanqi305/MobileNet-SSD/master/mobilenet_iter_73000.caffemodel",
"configUrl": "https://raw.githubusercontent.com/chuanqi305/MobileNet-SSD/master/deploy.prototxt"
},
"std": "1",
"swapRB": "false",
"outType": "SSD",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/object_detection_classes_pascal_voc.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/object_detection_classes_pascal_voc.txt",
"modelUrl": "https://drive.google.com/uc?id=0BzKzrI_SkD1_WVVTSmQxU0dVRzA&export=download",
"configUrl": "https://drive.google.com/uc?id=0BzKzrI_SkD1_WVVTSmQxU0dVRzA&export=download"
}
"std": "0.00392",
"swapRB": "false",
"outType": "YOLO",
- "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/object_detection_classes_yolov3.txt",
+ "labelsUrl": "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/object_detection_classes_yolov3.txt",
"modelUrl": "https://pjreddie.com/media/files/yolov2-tiny.weights",
"configUrl": "https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov2-tiny.cfg"
}
outType = "SSD";
// url for label file, can from local or Internet
-labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/object_detection_classes_pascal_voc.txt";
+labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/object_detection_classes_pascal_voc.txt";
</script>
<script id="codeSnippet1" type="text/code-snippet">
needSoftmax = false;
// url for label file, can from local or Internet
-labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/master/samples/data/dnn/classification_classes_ILSVRC2012.txt";
+labelsUrl = "https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt";
</script>
<script id="codeSnippet1" type="text/code-snippet">
### Execute it ###
- Save the file as `exampleNodeCanvasData.js`.
-- Make sure the files `aarcascade_frontalface_default.xml` and `haarcascade_eye.xml`\e are present in project's directory. They can be obtained from [OpenCV sources](https://github.com/opencv/opencv/tree/master/data/haarcascades).
+- Make sure the files `aarcascade_frontalface_default.xml` and `haarcascade_eye.xml`\e are present in project's directory. They can be obtained from [OpenCV sources](https://github.com/opencv/opencv/tree/4.x/data/haarcascades).
- Make sure a sample image file `lena.jpg` exists in project's directory. It should display people's faces for this example to make sense. The following image is known to work:
Steps
-----
-In this tutorial, you will learn how to include and start to use `opencv.js` inside a web page. You can get a copy of `opencv.js` from `opencv-{VERSION_NUMBER}-docs.zip` in each [release](https://github.com/opencv/opencv/releases), or simply download the prebuilt script from the online documentations at "https://docs.opencv.org/{VERSION_NUMBER}/opencv.js" (For example, [https://docs.opencv.org/3.4.0/opencv.js](https://docs.opencv.org/3.4.0/opencv.js). Use `master` if you want the latest build). You can also build your own copy by following the tutorial on Build Opencv.js.
+In this tutorial, you will learn how to include and start to use `opencv.js` inside a web page.
+You can get a copy of `opencv.js` from `opencv-{VERSION_NUMBER}-docs.zip` in each [release](https://github.com/opencv/opencv/releases), or simply download the prebuilt script from the online documentations at "https://docs.opencv.org/{VERSION_NUMBER}/opencv.js" (For example, [https://docs.opencv.org/4.5.0/opencv.js](https://docs.opencv.org/4.5.0/opencv.js). Use `4.x` if you want the latest build).
+You can also build your own copy by following the tutorial @ref tutorial_js_setup.
### Create a web page
Finally, as in the previous case, we start by splitting our big dataset into individual cells. For
every digit, 250 cells are reserved for training data and remaining 250 data is reserved for
-testing. Full code is given below, you also can download it from [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py):
+testing. Full code is given below, you also can download it from [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py):
@include samples/python/tutorial_code/ml/py_svm_opencv/hogsvm.py
flag value is assumed by default if neither of the two possible values of the property is set.
For more information please refer to the example of usage
-[videocapture_realsense.cpp](https://github.com/opencv/opencv/tree/master/samples/cpp/videocapture_realsense.cpp)
+[videocapture_realsense.cpp](https://github.com/opencv/opencv/tree/4.x/samples/cpp/videocapture_realsense.cpp)
in opencv/samples/cpp folder.
- CAP_OPENNI_DEPTH_GENERATOR_REGISTRATION = CAP_OPENNI_DEPTH_GENERATOR + CAP_PROP_OPENNI_REGISTRATION
For more information please refer to the example of usage
-[videocapture_openni.cpp](https://github.com/opencv/opencv/tree/master/samples/cpp/videocapture_openni.cpp) in
+[videocapture_openni.cpp](https://github.com/opencv/opencv/tree/4.x/samples/cpp/videocapture_openni.cpp) in
opencv/samples/cpp folder.
The complete implementation can be found in
-[orbbec_astra.cpp](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/videoio/orbbec_astra/orbbec_astra.cpp)
+[orbbec_astra.cpp](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/videoio/orbbec_astra/orbbec_astra.cpp)
in `samples/cpp/tutorial_code/videoio` directory.
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp)
@include cpp/tutorial_code/HighGUI/AddingImagesTrackbar.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/highgui/trackbar/AddingImagesTrackbar.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/highgui/trackbar/AddingImagesTrackbar.java)
@include java/tutorial_code/highgui/trackbar/AddingImagesTrackbar.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py)
@include python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py
@end_toggle
video files and performs a similarity check between them. This is something you could use to check
just how well a new video compressing algorithms works. Let there be a reference (original) video
like [this small Megamind clip
-](https://github.com/opencv/opencv/tree/master/samples/data/Megamind.avi) and [a compressed
-version of it ](https://github.com/opencv/opencv/tree/master/samples/data/Megamind_bugy.avi).
+](https://github.com/opencv/opencv/tree/4.x/samples/data/Megamind.avi) and [a compressed
+version of it ](https://github.com/opencv/opencv/tree/4.x/samples/data/Megamind_bugy.avi).
You may also find the source code and these video file in the
`samples/data` folder of the OpenCV source library.
You may also find the source code and these video file in the
`samples/cpp/tutorial_code/videoio/video-write/` folder of the OpenCV source library or [download it
-from here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/videoio/video-write/video-write.cpp).
+from here ](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/videoio/video-write/video-write.cpp).
@include cpp/tutorial_code/videoio/video-write/video-write.cpp
You may also find the source code in the `samples/cpp/tutorial_code/calib3d/camera_calibration/`
folder of the OpenCV source library or [download it from here
-](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). For the usage of the program, run it with `-h` argument. The program has an
+](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/calib3d/camera_calibration/camera_calibration.cpp). For the usage of the program, run it with `-h` argument. The program has an
essential argument: the name of its configuration file. If none is given then it will try to open the
one named "default.xml". [Here's a sample configuration file
-](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
+](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/calib3d/camera_calibration/in_VID5.xml) in XML format. In the
configuration file you may choose to use camera as an input, a video file or an image list. If you
opt for the last one, you will need to create a configuration file where you enumerate the images to
-use. Here's [an example of this ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
+use. Here's [an example of this ](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/calib3d/camera_calibration/VID5.xml).
The important part to remember is that the images need to be specified using the absolute path or
the relative one from your application's working directory. You may find all this in the samples
directory mentioned above.
The goal of this tutorial is to learn how to create calibration pattern.
-You can find a chessboard pattern in https://github.com/opencv/opencv/blob/master/doc/pattern.png
+You can find a chessboard pattern in https://github.com/opencv/opencv/blob/4.x/doc/pattern.png
-You can find a circleboard pattern in https://github.com/opencv/opencv/blob/master/doc/acircles_pattern.png
+You can find a circleboard pattern in https://github.com/opencv/opencv/blob/4.x/doc/acircles_pattern.png
Create your own pattern
---------------
-Now, if you want to create your own pattern, you will need python to use https://github.com/opencv/opencv/blob/master/doc/pattern_tools/gen_pattern.py
+Now, if you want to create your own pattern, you will need python to use https://github.com/opencv/opencv/blob/4.x/doc/pattern_tools/gen_pattern.py
Example
- *camera_resolution*: resolution of camera which is used for calibration
**Note:** *charuco_dict*, *charuco_square_length* and *charuco_marker_size* are used for chAruco pattern generation
-(see Aruco module description for details: [Aruco tutorials](https://github.com/opencv/opencv_contrib/tree/master/modules/aruco/tutorials))
+(see Aruco module description for details: [Aruco tutorials](https://github.com/opencv/opencv_contrib/tree/4.x/modules/aruco/tutorials))
Default chAruco pattern:
@add_toggle_cpp
Download the source code from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
@include cpp/tutorial_code/core/AddingImages/AddingImages.cpp
@end_toggle
@add_toggle_java
Download the source code from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/AddingImages/AddingImages.java).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/core/AddingImages/AddingImages.java).
@include java/tutorial_code/core/AddingImages/AddingImages.java
@end_toggle
@add_toggle_python
Download the source code from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/AddingImages/adding_images.py).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/core/AddingImages/adding_images.py).
@include python/tutorial_code/core/AddingImages/adding_images.py
@end_toggle
@snippet python/tutorial_code/core/AddingImages/adding_images.py load
@end_toggle
-We used the following images: [LinuxLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/LinuxLogo.jpg) and [WindowsLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/WindowsLogo.jpg)
+We used the following images: [LinuxLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/LinuxLogo.jpg) and [WindowsLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/WindowsLogo.jpg)
@warning Since we are *adding* *src1* and *src2*, they both have to be of the same size
(width and height) and type.
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp)
- The following code performs the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ :
@include samples/cpp/tutorial_code/ImgProc/BasicLinearTransforms.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java)
- The following code performs the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ :
@include samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/BasicLinearTransformsDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py)
- The following code performs the operation \f$g(i,j) = \alpha \cdot f(i,j) + \beta\f$ :
@include samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py
### Code
@add_toggle_cpp
-Code for the tutorial is [here](https://github.com/opencv/opencv/blob/master/samples/cpp/tutorial_code/ImgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.cpp).
+Code for the tutorial is [here](https://github.com/opencv/opencv/blob/4.x/samples/cpp/tutorial_code/ImgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.cpp).
@end_toggle
@add_toggle_java
-Code for the tutorial is [here](https://github.com/opencv/opencv/blob/master/samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/ChangingContrastBrightnessImageDemo.java).
+Code for the tutorial is [here](https://github.com/opencv/opencv/blob/4.x/samples/java/tutorial_code/ImgProc/changing_contrast_brightness_image/ChangingContrastBrightnessImageDemo.java).
@end_toggle
@add_toggle_python
-Code for the tutorial is [here](https://github.com/opencv/opencv/blob/master/samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.py).
+Code for the tutorial is [here](https://github.com/opencv/opencv/blob/4.x/samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.py).
@end_toggle
Code for the gamma correction:
@add_toggle_cpp
You can [download this from here
-](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
+](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
find it in the
`samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp` of the
OpenCV source code library.
@add_toggle_java
You can [download this from here
-](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java) or
+](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java) or
find it in the
`samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java` of the
OpenCV source code library.
@add_toggle_python
You can [download this from here
-](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py) or
+](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py) or
find it in the
`samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py` of the
OpenCV source code library.
example, let us find out if a text is horizontal or not? Looking at some text you'll notice that the
text lines sort of form also horizontal lines and the letters form sort of vertical lines. These two
main components of a text snippet may be also seen in case of the Fourier transform. Let us use
-[this horizontal ](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/imageTextN.png) and [this rotated](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/imageTextR.png)
+[this horizontal ](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/imageTextN.png) and [this rotated](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/imageTextR.png)
image about a text.
In case of the horizontal text:
-----------
@add_toggle_cpp
You can [download this from here
-](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
+](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
`samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp` of the OpenCV source code
library.
@add_toggle_python
You can [download this from here
-](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/core/file_input_output/file_input_output.py) or find it in the
+](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/core/file_input_output/file_input_output.py) or find it in the
`samples/python/tutorial_code/core/file_input_output/file_input_output.py` of the OpenCV source code
library.
we'll make the scanning of the image using each of these methods, and print out how long it took.
You can download the full source code [here
-](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
+](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
the samples directory of OpenCV at the cpp tutorial code for the core section. Its basic usage is:
@code{.bash}
how_to_scan_images imageName.jpg intValueToReduce [G]
The goal of this tutorial is to show you how to use the OpenCV `parallel_for_` framework to easily
parallelize your code. To illustrate the concept, we will write a program to draw a Mandelbrot set
exploiting almost all the CPU load available.
-The full tutorial code is [here](https://github.com/opencv/opencv/blob/master/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
+The full tutorial code is [here](https://github.com/opencv/opencv/blob/4.x/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
If you want more information about multithreading, you will have to refer to a reference book or course as this tutorial is intended
to remain simple.
Results
-----------
-You can find the full tutorial code [here](https://github.com/opencv/opencv/blob/master/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
+You can find the full tutorial code [here](https://github.com/opencv/opencv/blob/4.x/samples/cpp/tutorial_code/core/how_to_use_OpenCV_parallel_for_/how_to_use_OpenCV_parallel_for_.cpp).
The performance of the parallel implementation depends of the type of CPU you have. For instance, on 4 cores / 8 threads
CPU, you can expect a speed-up of around 6.9X. There are many factors to explain why we do not achieve a speed-up of almost 8X.
Main reasons should be mostly due to:
@add_toggle_cpp
You can download this source code from [here
-](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
+](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
OpenCV source code libraries sample directory at
`samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.
@include samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp
@add_toggle_java
You can download this source code from [here
-](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java) or look in the
+](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java) or look in the
OpenCV source code libraries sample directory at
`samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java`.
@include samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java
@add_toggle_python
You can download this source code from [here
-](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py) or look in the
+](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py) or look in the
OpenCV source code libraries sample directory at
`samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py`.
@include samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py
Most of the samples here have been included in a small console application. You can download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
or in the core section of the cpp samples.
You can also find a quick video demonstration of this on
You may learn more about convolution from the previous tutorial. We use the same naive implementation from the previous tutorial and compare it to the vectorized version.
-The full tutorial code is [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/univ_intrin/univ_intrin.cpp).
+The full tutorial code is [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/univ_intrin/univ_intrin.cpp).
### Vectorizing Convolution
After completing the model training, please use [transform_to_onnx.py](https://github.com/zihaomu/deep-text-recognition-benchmark/blob/master/transform_to_onnx.py) to convert the model into onnx format.
#### Execute in webcam
-The Python version example code can be found at [here](https://github.com/opencv/opencv/blob/master/samples/dnn/text_detection.py).
+The Python version example code can be found at [here](https://github.com/opencv/opencv/blob/4.x/samples/dnn/text_detection.py).
Example:
@code{.bash}
@snippet dnn/edge_detection.py Register
That's it! We've replaced an implemented OpenCV's layer to a custom one.
-You may find a full script in the [source code](https://github.com/opencv/opencv/tree/master/samples/dnn/edge_detection.py).
+You may find a full script in the [source code](https://github.com/opencv/opencv/tree/4.x/samples/dnn/edge_detection.py).
<table border="0">
<tr>
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/dnn/face_detect.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/dnn/face_detect.cpp)
- **Code at glance:**
@include samples/dnn/face_detect.cpp
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/dnn/face_detect.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/dnn/face_detect.py)
- **Code at glance:**
@include samples/dnn/face_detect.py
Source Code
-----------
-We will be using snippets from the example application, that can be downloaded [here](https://github.com/opencv/opencv/blob/master/samples/dnn/classification.cpp).
+We will be using snippets from the example application, that can be downloaded [here](https://github.com/opencv/opencv/blob/4.x/samples/dnn/classification.cpp).
@include dnn/classification.cpp
-----------
-# Firstly, download GoogLeNet model files:
- [bvlc_googlenet.prototxt ](https://github.com/opencv/opencv_extra/blob/master/testdata/dnn/bvlc_googlenet.prototxt) and
+ [bvlc_googlenet.prototxt ](https://github.com/opencv/opencv_extra/blob/4.x/testdata/dnn/bvlc_googlenet.prototxt) and
[bvlc_googlenet.caffemodel](http://dl.caffe.berkeleyvision.org/bvlc_googlenet.caffemodel)
Also you need file with names of [ILSVRC2012](http://image-net.org/challenges/LSVRC/2012/browse-synsets) classes:
- [classification_classes_ILSVRC2012.txt](https://github.com/opencv/opencv/blob/master/samples/data/dnn/classification_classes_ILSVRC2012.txt).
+ [classification_classes_ILSVRC2012.txt](https://github.com/opencv/opencv/blob/4.x/samples/data/dnn/classification_classes_ILSVRC2012.txt).
Put these files into working dir of this program example.
`split: { x: 2 }` gives new ones `xo` in range `[0, 5)` and `xi` in range `[0, 2)`.
Variable name `x` is no longer available in the same scheduling node.
-You can find scheduling examples at [opencv_extra/testdata/dnn](https://github.com/opencv/opencv_extra/tree/master/testdata/dnn)
+You can find scheduling examples at [opencv_extra/testdata/dnn](https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn)
and use it for schedule your networks.
## Layers fusing
For OpenCV-Python building from source, follow the corresponding instructions from the @ref tutorial_py_table_of_contents_setup.
-Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
+Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
The below line initiates requirements installation into the previously activated virtual environment:
```console
Thus, the converted ResNet-50 will be saved in ``dnn_model_runner/dnn_conversion/models``.
### Inference Pipeline
-Now we can use ```models/resnet50.onnx``` for the inference pipeline using OpenCV C/C++ API. The implemented pipeline can be found in [samples/dnn/classification.cpp](https://github.com/opencv/opencv/blob/master/samples/dnn/classification.cpp).
+Now we can use ```models/resnet50.onnx``` for the inference pipeline using OpenCV C/C++ API. The implemented pipeline can be found in [samples/dnn/classification.cpp](https://github.com/opencv/opencv/blob/4.x/samples/dnn/classification.cpp).
After the build of samples (``BUILD_EXAMPLES`` flag value should be ``ON``), the appropriate ``example_dnn_classification`` executable file will be provided.
To provide model inference we will use the below [squirrel photo](https://www.pexels.com/photo/brown-squirrel-eating-1564292) (under [CC0](https://www.pexels.com/terms-of-service/) license) corresponding to ImageNet class ID 335:
For OpenCV-Python building from source, follow the corresponding instructions from the @ref tutorial_py_table_of_contents_setup.
-Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
+Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
The below line initiates requirements installation into the previously activated virtual environment:
```console
Chosen from the list classification model will be read into OpenCV cv.dnn.Net object. Evaluation results of PyTorch and OpenCV models (accuracy, inference time, L1) will be written into the log file. Inference time values will be also depicted in a chart to generalize the obtained model information.
-Necessary evaluation configurations are defined in the [test_config.py](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) and can be modified in accordance with actual paths of data location:
+Necessary evaluation configurations are defined in the [test_config.py](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) and can be modified in accordance with actual paths of data location:
```python
@dataclass
Here ``default_img_preprocess`` key defines whether you'd like to parametrize the model test process with some particular values or use the default values, for example, ``scale``, ``mean`` or ``std``.
-Test configuration is represented in [test_config.py](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestClsModuleConfig`` class:
+Test configuration is represented in [test_config.py](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestClsModuleConfig`` class:
```python
@dataclass
classes: str = os.path.join(cls_test_data_dir, "dnn", "classification_classes_ILSVRC2012.txt")
```
-The default image preprocessing options are defined in [default_preprocess_config.py](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/default_preprocess_config.py). For instance:
+The default image preprocessing options are defined in [default_preprocess_config.py](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/default_preprocess_config.py). For instance:
```python
BASE_IMG_SCALE_FACTOR = 1 / 255.0
}
```
-The basis of the model testing is represented in [samples/dnn/classification.py](https://github.com/opencv/opencv/blob/master/samples/dnn/classification.py). ``classification.py`` can be executed autonomously with provided converted model in ``--input`` and populated parameters for cv.dnn.blobFromImage.
+The basis of the model testing is represented in [samples/dnn/classification.py](https://github.com/opencv/opencv/blob/4.x/samples/dnn/classification.py). ``classification.py`` can be executed autonomously with provided converted model in ``--input`` and populated parameters for cv.dnn.blobFromImage.
To reproduce from scratch the described in "Model Conversion Pipeline" OpenCV steps with ``dnn_model_runner`` execute the below line:
For OpenCV-Python building from source, follow the corresponding instructions from the @ref tutorial_py_table_of_contents_setup.
-Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
+Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
The below line initiates requirements installation into the previously activated virtual environment:
```console
Chosen from the list classification model will be read into OpenCV ``cv.dnn_Net`` object. Evaluation results of TF and OpenCV models (accuracy, inference time, L1) will be written into the log file. Inference time values will be also depicted in a chart to generalize the obtained model information.
-Necessary evaluation configurations are defined in the [test_config.py](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) and can be modified in accordance with actual paths of data location::
+Necessary evaluation configurations are defined in the [test_config.py](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) and can be modified in accordance with actual paths of data location::
```python
@dataclass
Here ``default_img_preprocess`` key defines whether you'd like to parametrize the model test process with some particular values or use the default values, for example, ``scale``, ``mean`` or ``std``.
-Test configuration is represented in [test_config.py](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestClsModuleConfig`` class:
+Test configuration is represented in [test_config.py](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestClsModuleConfig`` class:
```python
@dataclass
}
```
-The basis of the model testing is represented in [samples/dnn/classification.py](https://github.com/opencv/opencv/blob/master/samples/dnn/classification.py). ``classification.py`` can be executed autonomously with provided converted model in ``--input`` and populated parameters for cv.dnn.blobFromImage.
+The basis of the model testing is represented in [samples/dnn/classification.py](https://github.com/opencv/opencv/blob/4.x/samples/dnn/classification.py). ``classification.py`` can be executed autonomously with provided converted model in ``--input`` and populated parameters for cv.dnn.blobFromImage.
To reproduce from scratch the described in "Model Conversion Pipeline" OpenCV steps with ``dnn_model_runner`` execute the below line:
For OpenCV-Python building from source, follow the corresponding instructions from the @ref tutorial_py_table_of_contents_setup.
-Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
+Before you start the installation of the libraries, you can customize the [requirements.txt](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/requirements.txt), excluding or including (for example, ``opencv-python``) some dependencies.
The below line initiates requirements installation into the previously activated virtual environment:
```console
To initiate the test process we need to provide an appropriate model configuration. We will use [``ssd_mobilenet_v1_coco.config``](https://github.com/tensorflow/models/blob/master/research/object_detection/samples/configs/ssd_mobilenet_v1_coco.config) from [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection#tensorflow-object-detection-api).
TensorFlow Object Detection API framework contains helpful mechanisms for object detection model manipulations.
-We will use this configuration to provide a text graph representation. To generate ``.pbtxt`` we will use the corresponding [``samples/dnn/tf_text_graph_ssd.py``](https://github.com/opencv/opencv/blob/master/samples/dnn/tf_text_graph_ssd.py) script:
+We will use this configuration to provide a text graph representation. To generate ``.pbtxt`` we will use the corresponding [``samples/dnn/tf_text_graph_ssd.py``](https://github.com/opencv/opencv/blob/4.x/samples/dnn/tf_text_graph_ssd.py) script:
```console
python tf_text_graph_ssd.py --input ssd_mobilenet_v1_coco_2017_11_17/frozen_inference_graph.pb --config ssd_mobilenet_v1_coco_2017_11_17/ssd_mobilenet_v1_coco.config --output ssd_mobilenet_v1_coco_2017_11_17.pbtxt
After successful execution ``ssd_mobilenet_v1_coco_2017_11_17.pbtxt`` will be created.
-Before we run ``object_detection.py``, let's have a look at the default values for the SSD MobileNetV1 test process configuration. They are located in [``models.yml``](https://github.com/opencv/opencv/blob/master/samples/dnn/models.yml):
+Before we run ``object_detection.py``, let's have a look at the default values for the SSD MobileNetV1 test process configuration. They are located in [``models.yml``](https://github.com/opencv/opencv/blob/4.x/samples/dnn/models.yml):
```yml
ssd_tf:
Chosen from the list segmentation model will be read into OpenCV ``cv.dnn_Net`` object. Evaluation results of PyTorch and OpenCV models (pixel accuracy, mean IoU, inference time) will be written into the log file. Inference time values will be also depicted in a chart to generalize the obtained model information.
-Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
+Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
```python
@dataclass
Here ``default_img_preprocess`` key defines whether you'd like to parametrize the model test process with some particular values or use the default values, for example, ``scale``, ``mean`` or ``std``.
-Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
+Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
```python
@dataclass
The model will be read into OpenCV ``cv.dnn_Net`` object. Evaluation results of TF and OpenCV models (pixel accuracy, mean IoU, inference time) will be written into the log file. Inference time values will be also depicted in a chart to generalize the obtained model information.
-Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
+Necessary evaluation configurations are defined in the [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py):
```python
@dataclass
Here ``default_img_preprocess`` key defines whether you'd like to parametrize the model test process with some particular values or use the default values, for example, ``scale``, ``mean`` or ``std``.
-Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
+Test configuration is represented in [``test_config.py``](https://github.com/opencv/opencv/tree/4.x/samples/dnn/dnn_model_runner/dnn_conversion/common/test/configs/test_config.py) ``TestSegmModuleConfig`` class:
```python
@dataclass
## Source Code
-The [source code](https://github.com/opencv/opencv/blob/master/modules/dnn/src/model.cpp)
+The [source code](https://github.com/opencv/opencv/blob/4.x/modules/dnn/src/model.cpp)
of these APIs can be found in the DNN module.
## Detailed Sample
For more information, please refer to:
-- [samples/dnn/scene_text_recognition.cpp](https://github.com/opencv/opencv/blob/master/samples/dnn/scene_text_recognition.cpp)
-- [samples/dnn/scene_text_detection.cpp](https://github.com/opencv/opencv/blob/master/samples/dnn/scene_text_detection.cpp)
-- [samples/dnn/text_detection.cpp](https://github.com/opencv/opencv/blob/master/samples/dnn/text_detection.cpp)
-- [samples/dnn/scene_text_spotting.cpp](https://github.com/opencv/opencv/blob/master/samples/dnn/scene_text_spotting.cpp)
+- [samples/dnn/scene_text_recognition.cpp](https://github.com/opencv/opencv/blob/4.x/samples/dnn/scene_text_recognition.cpp)
+- [samples/dnn/scene_text_detection.cpp](https://github.com/opencv/opencv/blob/4.x/samples/dnn/scene_text_detection.cpp)
+- [samples/dnn/text_detection.cpp](https://github.com/opencv/opencv/blob/4.x/samples/dnn/text_detection.cpp)
+- [samples/dnn/scene_text_spotting.cpp](https://github.com/opencv/opencv/blob/4.x/samples/dnn/scene_text_spotting.cpp)
#### Test with an image
Examples:
-----------
Use a universal sample for object detection models written
-[in C++](https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.cpp) and
-[in Python](https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.py) languages
+[in C++](https://github.com/opencv/opencv/blob/4.x/samples/dnn/object_detection.cpp) and
+[in Python](https://github.com/opencv/opencv/blob/4.x/samples/dnn/object_detection.py) languages
Usage examples
--------------
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/features2D/AKAZE_match.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py)
- **Code at glance:**
@include samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java)
@include samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py)
@include samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
@include samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
@include samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java)
@include samples/java/tutorial_code/features2D/feature_flann_matcher/SURFFLANNMatchingDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py)
@include samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp)
@include samples/cpp/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java)
@include samples/java/tutorial_code/features2D/feature_homography/SURFFLANNMatchingHomographyDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py)
@include samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py
@end_toggle
* An Invitation to 3-D Vision: From Images to Geometric Models, @cite Ma:2003:IVI
* Computer Vision: Algorithms and Applications, @cite RS10
-The tutorial code can be found here [C++](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/Homography),
-[Python](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/Homography),
-[Java](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/Homography).
-The images used in this tutorial can be found [here](https://github.com/opencv/opencv/tree/master/samples/data) (`left*.jpg`).
+The tutorial code can be found here [C++](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/features2D/Homography),
+[Python](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/features2D/Homography),
+[Java](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/features2D/Homography).
+The images used in this tutorial can be found [here](https://github.com/opencv/opencv/tree/4.x/samples/data) (`left*.jpg`).
Basic theory {#tutorial_homography_Basic_theory}
------------
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/cornerSubPix_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java)
@include samples/java/tutorial_code/TrackingMotion/corner_subpixels/CornerSubPixDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java)
@include samples/java/tutorial_code/TrackingMotion/generic_corner_detector/CornerDetectorDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/goodFeaturesToTrack_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java)
@include samples/java/tutorial_code/TrackingMotion/good_features_to_track/GoodFeaturesToTrackDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp)
@include samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java)
@include samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py)
@include samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py
@end_toggle
You may also find the source code and the video file in the
`samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity` directory of the OpenCV
-source library or download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
+source library or download it from [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp).
The full source code is quite long (due to the controlling of the application via the command line
arguments and performance measurement). Therefore, to avoid cluttering up these sections with those
you'll find here only the functions itself.
@add_toggle_cpp
- This code is in your OpenCV sample folder. Otherwise you can grab it from
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp)
@include samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_1.cpp
@end_toggle
@add_toggle_java
- This code is in your OpenCV sample folder. Otherwise you can grab it from
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java)
@include samples/java/tutorial_code/ImgProc/BasicGeometricDrawing/BasicGeometricDrawing.java
@end_toggle
@add_toggle_python
- This code is in your OpenCV sample folder. Otherwise you can grab it from
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py)
@include samples/python/tutorial_code/imgProc/BasicGeometricDrawing/basic_geometric_drawing.py
@end_toggle
@add_toggle_cpp
This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
@include samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp
@end_toggle
@add_toggle_java
This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/erosion_dilatation/MorphologyDemo1.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgProc/erosion_dilatation/MorphologyDemo1.java)
@include samples/java/tutorial_code/ImgProc/erosion_dilatation/MorphologyDemo1.java
@end_toggle
@add_toggle_python
This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py)
@include samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py
@end_toggle
Compile the code above and execute it (or run the script if using python) with an image as argument.
If you do not provide an image as argument the default sample image
-([LinuxLogo.jpg](https://github.com/opencv/opencv/tree/master/samples/data/LinuxLogo.jpg)) will be used.
+([LinuxLogo.jpg](https://github.com/opencv/opencv/tree/4.x/samples/data/LinuxLogo.jpg)) will be used.
For instance, using this image:
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/Smoothing/Smoothing.java)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgProc/Smoothing/Smoothing.java)
- **Code at glance:**
@include samples/java/tutorial_code/ImgProc/Smoothing/Smoothing.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/Smoothing/smoothing.py)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/imgProc/Smoothing/smoothing.py)
- **Code at glance:**
@include samples/python/tutorial_code/imgProc/Smoothing/smoothing.py
Results
-------
-- The code opens an image (in this case [lena.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/lena.jpg))
+- The code opens an image (in this case [lena.jpg](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/lena.jpg))
and display it under the effects of the 4 filters explained.
- Here is a snapshot of the image smoothed using *medianBlur*:
@add_toggle_cpp
- **Downloadable code**:
- Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo1.cpp)
for the basic version (explained in this tutorial).
- For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
skin area) you can check the [improved
- demo](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
+ demo](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/Histograms_Matching/calcBackProject_Demo2.cpp)
- ...or you can always check out the classical
- [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
+ [camshiftdemo](https://github.com/opencv/opencv/tree/4.x/samples/cpp/camshiftdemo.cpp)
in samples.
- **Code at glance:**
@add_toggle_java
- **Downloadable code**:
- Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo1.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo1.java)
for the basic version (explained in this tutorial).
- For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
skin area) you can check the [improved
- demo](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo2.java)
+ demo](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/Histograms_Matching/back_projection/CalcBackProjectDemo2.java)
- ...or you can always check out the classical
- [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
+ [camshiftdemo](https://github.com/opencv/opencv/tree/4.x/samples/cpp/camshiftdemo.cpp)
in samples.
- **Code at glance:**
@add_toggle_python
- **Downloadable code**:
- Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo1.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo1.py)
for the basic version (explained in this tutorial).
- For stuff slightly fancier (using H-S histograms and floodFill to define a mask for the
skin area) you can check the [improved
- demo](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo2.py)
+ demo](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/Histograms_Matching/back_projection/calcBackProject_Demo2.py)
- ...or you can always check out the classical
- [camshiftdemo](https://github.com/opencv/opencv/tree/master/samples/cpp/camshiftdemo.cpp)
+ [camshiftdemo](https://github.com/opencv/opencv/tree/4.x/samples/cpp/camshiftdemo.cpp)
in samples.
- **Code at glance:**
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/calcHist_Demo.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/histogram_calculation/CalcHistDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/Histograms_Matching/histogram_calculation/CalcHistDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/Histograms_Matching/histogram_calculation/CalcHistDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/histogram_calculation/calcHist_Demo.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/Histograms_Matching/histogram_calculation/calcHist_Demo.py)
- **Code at glance:**
@include samples/python/tutorial_code/Histograms_Matching/histogram_calculation/calcHist_Demo.py
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/histogram_comparison/CompareHistDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/Histograms_Matching/histogram_comparison/CompareHistDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/Histograms_Matching/histogram_comparison/CompareHistDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/histogram_comparison/compareHist_Demo.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/Histograms_Matching/histogram_comparison/compareHist_Demo.py)
- **Code at glance:**
@include samples/python/tutorial_code/Histograms_Matching/histogram_comparison/compareHist_Demo.py
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/EqualizeHist_Demo.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHistDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHistDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHistDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHist_Demo.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHist_Demo.py)
- **Code at glance:**
@include samples/python/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHist_Demo.py
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/Histograms_Matching/MatchTemplate_Demo.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/tutorial_template_matching/MatchTemplateDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgProc/tutorial_template_matching/MatchTemplateDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/ImgProc/tutorial_template_matching/MatchTemplateDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/match_template/match_template.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgProc/match_template/match_template.py)
- **Code at glance:**
@include samples/python/tutorial_code/imgProc/match_template/match_template.py
@add_toggle_cpp
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp)
@include samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp
@end_toggle
@add_toggle_java
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java)
@include samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java
@end_toggle
@add_toggle_python
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py)
@include samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py
@end_toggle
@add_toggle_cpp
- The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp
@end_toggle
@add_toggle_java
- The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgTrans/canny_detector/CannyDetectorDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgTrans/canny_detector/CannyDetectorDemo.java)
@include samples/java/tutorial_code/ImgTrans/canny_detector/CannyDetectorDemo.java
@end_toggle
@add_toggle_python
- The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ImgTrans/canny_detector/CannyDetector_Demo.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ImgTrans/canny_detector/CannyDetector_Demo.py)
@include samples/python/tutorial_code/ImgTrans/canny_detector/CannyDetector_Demo.py
@end_toggle
@add_toggle_cpp
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp
@end_toggle
@add_toggle_java
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/MakeBorder/CopyMakeBorder.java)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgTrans/MakeBorder/CopyMakeBorder.java)
@include samples/java/tutorial_code/ImgTrans/MakeBorder/CopyMakeBorder.java
@end_toggle
@add_toggle_python
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/MakeBorder/copy_make_border.py)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/MakeBorder/copy_make_border.py)
@include samples/python/tutorial_code/ImgTrans/MakeBorder/copy_make_border.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp).
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp).
@include samples/cpp/tutorial_code/ImgTrans/imageSegmentation.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgTrans/distance_transformation/ImageSegmentationDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgTrans/distance_transformation/ImageSegmentationDemo.java)
@include samples/java/tutorial_code/ImgTrans/distance_transformation/ImageSegmentationDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py)
@include samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py
@end_toggle
@add_toggle_cpp
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp)
@include cpp/tutorial_code/ImgTrans/filter2D_demo.cpp
@end_toggle
@add_toggle_java
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/Filter2D/Filter2D_Demo.java)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgTrans/Filter2D/Filter2D_Demo.java)
@include java/tutorial_code/ImgTrans/Filter2D/Filter2D_Demo.java
@end_toggle
@add_toggle_python
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/Filter2D/filter2D.py)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/Filter2D/filter2D.py)
@include python/tutorial_code/ImgTrans/Filter2D/filter2D.py
@end_toggle
@add_toggle_cpp
The sample code that we will explain can be downloaded from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp).
A slightly fancier version (which shows trackbars for changing the threshold values) can be found
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp).
@include samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp
@end_toggle
@add_toggle_java
The sample code that we will explain can be downloaded from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java).
@include samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java
@end_toggle
@add_toggle_python
The sample code that we will explain can be downloaded from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py).
@include samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py
@end_toggle
Explanation
-----------
-The image we used can be found [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/smarties.png)
+The image we used can be found [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/smarties.png)
#### Load an image:
@add_toggle_cpp
The sample code that we will explain can be downloaded from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/houghlines.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/houghlines.cpp).
A slightly fancier version (which shows both Hough standard and probabilistic
with trackbars for changing the threshold values) can be found
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp).
@include samples/cpp/tutorial_code/ImgTrans/houghlines.cpp
@end_toggle
@add_toggle_java
The sample code that we will explain can be downloaded from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/HoughLine/HoughLines.java).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgTrans/HoughLine/HoughLines.java).
@include samples/java/tutorial_code/ImgTrans/HoughLine/HoughLines.java
@end_toggle
@add_toggle_python
The sample code that we will explain can be downloaded from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/HoughLine/hough_lines.py).
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/HoughLine/hough_lines.py).
@include samples/python/tutorial_code/ImgTrans/HoughLine/hough_lines.py
@end_toggle
section. It still implements the same stuff as above, only adding the Trackbar for the
Threshold.
-Using an input image such as a [sudoku image](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/sudoku.png).
+Using an input image such as a [sudoku image](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/sudoku.png).
We get the following result by using the Standard Hough Line Transform:
And by using the Probabilistic Hough Line Transform:
@add_toggle_cpp
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
@end_toggle
@add_toggle_java
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java)
@include samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java
@end_toggle
@add_toggle_python
-# The tutorial code's is shown lines below. You can also download it from
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py)
@include samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py
@end_toggle
@add_toggle_cpp
- The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp
@end_toggle
@add_toggle_java
- The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java)
@include samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java
@end_toggle
@add_toggle_python
- The tutorial code's is shown lines below. You can also download it from
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py)
@include samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py
@end_toggle
@add_toggle_cpp
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp
@end_toggle
@add_toggle_java
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/SobelDemo/SobelDemo.java)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgTrans/SobelDemo/SobelDemo.java)
@include samples/java/tutorial_code/ImgTrans/SobelDemo/SobelDemo.java
@end_toggle
@add_toggle_python
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/SobelDemo/sobel_demo.py)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/SobelDemo/sobel_demo.py)
@include samples/python/tutorial_code/ImgTrans/SobelDemo/sobel_demo.py
@end_toggle
@add_toggle_cpp
- The tutorial's code is shown below. You can also download it
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp
@end_toggle
@add_toggle_java
- The tutorial's code is shown below. You can also download it
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/Smoothing/Smoothing.cpp)
@include samples/java/tutorial_code/ImgTrans/warp_affine/GeometricTransformsDemo.java
@end_toggle
@add_toggle_python
- The tutorial's code is shown below. You can also download it
- [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/warp_affine/Geometric_Transforms_Demo.py)
+ [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/ImgTrans/warp_affine/Geometric_Transforms_Demo.py)
@include samples/python/tutorial_code/ImgTrans/warp_affine/Geometric_Transforms_Demo.py
@end_toggle
This tutorial code's is shown lines below.
@add_toggle_cpp
-You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.cpp).
+You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.cpp).
@include samples/cpp/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.cpp
@end_toggle
@add_toggle_java
-You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.java).
+You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.java).
@include samples/java/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.java
@end_toggle
@add_toggle_python
-You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/morph_lines_detection/morph_lines_detection.py).
+You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/imgProc/morph_lines_detection/morph_lines_detection.py).
@include samples/python/tutorial_code/imgProc/morph_lines_detection/morph_lines_detection.py
@end_toggle
Explanation / Result
--------------------
-Get image from [here](https://raw.githubusercontent.com/opencv/opencv/master/doc/tutorials/imgproc/morph_lines_detection/images/src.png) .
+Get image from [here](https://raw.githubusercontent.com/opencv/opencv/4.x/doc/tutorials/imgproc/morph_lines_detection/images/src.png) .
#### Load Image
@add_toggle_cpp
This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgProc/Morphology_2.cpp)
@include cpp/tutorial_code/ImgProc/Morphology_2.cpp
@end_toggle
@add_toggle_java
This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/opening_closing_hats/MorphologyDemo2.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgProc/opening_closing_hats/MorphologyDemo2.java)
@include java/tutorial_code/ImgProc/opening_closing_hats/MorphologyDemo2.java
@end_toggle
@add_toggle_python
This tutorial's code is shown below. You can also download it
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/opening_closing_hats/morphology_2.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgProc/opening_closing_hats/morphology_2.py)
@include python/tutorial_code/imgProc/opening_closing_hats/morphology_2.py
@end_toggle
@add_toggle_cpp
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/Pyramids/Pyramids.cpp)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/tutorial_code/ImgProc/Pyramids/Pyramids.cpp)
@include samples/cpp/tutorial_code/ImgProc/Pyramids/Pyramids.cpp
@end_toggle
@add_toggle_java
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/Pyramids/Pyramids.java)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/java/tutorial_code/ImgProc/Pyramids/Pyramids.java)
@include samples/java/tutorial_code/ImgProc/Pyramids/Pyramids.java
@end_toggle
@add_toggle_python
You can also download it from
-[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/Pyramids/pyramids.py)
+[here](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/tutorial_code/imgProc/Pyramids/pyramids.py)
@include samples/python/tutorial_code/imgProc/Pyramids/pyramids.py
@end_toggle
Results
-------
-- The program calls by default an image [chicky_512.png](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/chicky_512.png)
+- The program calls by default an image [chicky_512.png](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/data/chicky_512.png)
that comes in the `samples/data` folder. Notice that this image is \f$512 \times 512\f$,
hence a downsample won't generate any error (\f$512 = 2^{9}\f$). The original image is shown below:
to populate our image with a big number of geometric figures. Since we will be initializing them
in a random fashion, this process will be automatic and made by using *loops* .
- This code is in your OpenCV sample folder. Otherwise you can grab it from
- [here](http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/core/Matrix/Drawing_2.cpp)
+ [here](https://github.com/opencv/opencv/blob/4.x/samples/cpp/tutorial_code/ImgProc/basic_drawing/Drawing_2.cpp)
Explanation
-----------
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo1.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ShapeDescriptors/bounding_rects_circles/GeneralContoursDemo1.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ShapeDescriptors/bounding_rects_circles/GeneralContoursDemo1.java)
@include samples/java/tutorial_code/ShapeDescriptors/bounding_rects_circles/GeneralContoursDemo1.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ShapeDescriptors/bounding_rects_circles/generalContours_demo1.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ShapeDescriptors/bounding_rects_circles/generalContours_demo1.py)
@include samples/python/tutorial_code/ShapeDescriptors/bounding_rects_circles/generalContours_demo1.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/generalContours_demo2.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/GeneralContoursDemo2.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/GeneralContoursDemo2.java)
@include samples/java/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/GeneralContoursDemo2.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/generalContours_demo2.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/generalContours_demo2.py)
@include samples/python/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/generalContours_demo2.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/findContours_demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ShapeDescriptors/find_contours/FindContoursDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ShapeDescriptors/find_contours/FindContoursDemo.java)
@include samples/java/tutorial_code/ShapeDescriptors/find_contours/FindContoursDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ShapeDescriptors/find_contours/findContours_demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ShapeDescriptors/find_contours/findContours_demo.py)
@include samples/python/tutorial_code/ShapeDescriptors/find_contours/findContours_demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/hull_demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ShapeDescriptors/hull/HullDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ShapeDescriptors/hull/HullDemo.java)
@include samples/java/tutorial_code/ShapeDescriptors/hull/HullDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ShapeDescriptors/hull/hull_demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ShapeDescriptors/hull/hull_demo.py)
@include samples/python/tutorial_code/ShapeDescriptors/hull/hull_demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/moments_demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ShapeDescriptors/moments/MomentsDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ShapeDescriptors/moments/MomentsDemo.java)
@include samples/java/tutorial_code/ShapeDescriptors/moments/MomentsDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ShapeDescriptors/moments/moments_demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ShapeDescriptors/moments/moments_demo.py)
@include samples/python/tutorial_code/ShapeDescriptors/moments/moments_demo.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp)
@include samples/cpp/tutorial_code/ShapeDescriptors/pointPolygonTest_demo.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ShapeDescriptors/point_polygon_test/PointPolygonTestDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ShapeDescriptors/point_polygon_test/PointPolygonTestDemo.java)
@include samples/java/tutorial_code/ShapeDescriptors/point_polygon_test/PointPolygonTestDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ShapeDescriptors/point_polygon_test/pointPolygonTest_demo.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ShapeDescriptors/point_polygon_test/pointPolygonTest_demo.py)
@include samples/python/tutorial_code/ShapeDescriptors/point_polygon_test/pointPolygonTest_demo.py
@end_toggle
@add_toggle_cpp
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgProc/Threshold.cpp)
@include samples/cpp/tutorial_code/ImgProc/Threshold.cpp
@end_toggle
@add_toggle_java
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/threshold/Threshold.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgProc/threshold/Threshold.java)
@include samples/java/tutorial_code/ImgProc/threshold/Threshold.java
@end_toggle
@add_toggle_python
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/threshold/threshold.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgProc/threshold/threshold.py)
@include samples/python/tutorial_code/imgProc/threshold/threshold.py
@end_toggle
@add_toggle_cpp
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp)
@include samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp
@end_toggle
@add_toggle_java
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java)
@include samples/java/tutorial_code/ImgProc/threshold_inRange/ThresholdInRange.java
@end_toggle
@add_toggle_python
The tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py)
@include samples/python/tutorial_code/imgProc/threshold_inRange/threshold_inRange.py
@end_toggle
- `doc` folder contains various OpenCV documentation in PDF format. It's also available online at
<http://docs.opencv.org>.
- @note The most recent docs (nightly build) are at <http://docs.opencv.org/master>. Generally, it's more
+ @note The most recent docs (nightly build) are at <http://docs.opencv.org/4.x>. Generally, it's more
up-to-date, but can refer to not-yet-released functionality.
@todo I'm not sure that this is the best place to talk about OpenCV Manager
This tutorial also assumes you have an Android operated device with OpenCL enabled.
The related source code is located within OpenCV samples at
-[opencv/samples/android/tutorial-4-opencl](https://github.com/opencv/opencv/tree/master/samples/android/tutorial-4-opencl/) directory.
+[opencv/samples/android/tutorial-4-opencl](https://github.com/opencv/opencv/tree/4.x/samples/android/tutorial-4-opencl/) directory.
Preface
-------
@endcode
Let's leave the details of their implementation beyond of this tutorial, please refer the
-[source code](https://github.com/opencv/opencv/tree/master/samples/android/tutorial-4-opencl/) to see them.
+[source code](https://github.com/opencv/opencv/tree/4.x/samples/android/tutorial-4-opencl/) to see them.
Preview Frames modification
---------------------------
classes.
@note
-[Here](https://docs.opencv.org/master/javadoc/index.html) you can find the full OpenCV Java API.
+[Here](https://docs.opencv.org/4.x/javadoc/index.html) you can find the full OpenCV Java API.
@code{.clojure}
user=> (org.opencv.core.Point. 0 0)
- _swscale_
- _avresample_ (optional)
-Exception is Windows platform where a prebuilt [plugin library containing FFmpeg](https://github.com/opencv/opencv_3rdparty/tree/ffmpeg/master) will be downloaded during a configuration stage and copied to the `bin` folder with all produced libraries.
+Exception is Windows platform where a prebuilt [plugin library containing FFmpeg](https://github.com/opencv/opencv_3rdparty/tree/ffmpeg/4.x) will be downloaded during a configuration stage and copied to the `bin` folder with all produced libraries.
@note [Libav](https://en.wikipedia.org/wiki/Libav) library can be used instead of FFmpeg, but this combination is not actively supported.
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/introduction/display_image/display_image.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/introduction/display_image/display_image.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/introduction/display_image/display_image.cpp
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/introduction/display_image/display_image.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/introduction/display_image/display_image.py)
- **Code at glance:**
@include samples/python/tutorial_code/introduction/display_image/display_image.py
--------
Now to try this out download our little test [source code
-](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/introduction/windows_visual_studio_opencv/introduction_windows_vs.cpp)
+](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/introduction/windows_visual_studio_opencv/introduction_windows_vs.cpp)
or get it from the sample code folder of the OpenCV sources. Add this to your project and build it.
Here's its content:
This is important to remember when you code inside the code open and save commands. Your resources
will be saved ( and queried for at opening!!!) relatively to your working directory. This is unless
you give a full, explicit path as a parameter for the I/O functions. In the code above we open [this
-OpenCV logo](https://github.com/opencv/opencv/tree/master/samples/data/opencv-logo.png). Before starting up the application,
+OpenCV logo](https://github.com/opencv/opencv/tree/4.x/samples/data/opencv-logo.png). Before starting up the application,
make sure you place
the image file in your current working directory. Modify the image file name inside the code to try
it out on other images too. Run it and voil á:
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/bg_sub.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/video/bg_sub.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/video/bg_sub.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/video/background_subtraction/BackgroundSubtractionDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/video/background_subtraction/BackgroundSubtractionDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/video/background_subtraction/BackgroundSubtractionDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/video/background_subtraction/bg_sub.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/video/background_subtraction/bg_sub.py)
- **Code at glance:**
@include samples/python/tutorial_code/video/background_subtraction/bg_sub.py
Haar-cascade Detection in OpenCV
--------------------------------
OpenCV provides a training method (see @ref tutorial_traincascade) or pretrained models, that can be read using the @ref cv::CascadeClassifier::load method.
-The pretrained models are located in the data folder in the OpenCV installation or can be found [here](https://github.com/opencv/opencv/tree/master/data).
+The pretrained models are located in the data folder in the OpenCV installation or can be found [here](https://github.com/opencv/opencv/tree/4.x/data).
The following code example will use pretrained Haar cascade models to detect faces and eyes in an image.
First, a @ref cv::CascadeClassifier is created and the necessary XML file is loaded using the @ref cv::CascadeClassifier::load method.
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/objectDetection/objectDetection.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/objectDetection/objectDetection.cpp)
@include samples/cpp/tutorial_code/objectDetection/objectDetection.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/objectDetection/cascade_classifier/ObjectDetectionDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/objectDetection/cascade_classifier/ObjectDetectionDemo.java)
@include samples/java/tutorial_code/objectDetection/cascade_classifier/ObjectDetectionDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/objectDetection/cascade_classifier/objectDetection.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/objectDetection/cascade_classifier/objectDetection.py)
@include samples/python/tutorial_code/objectDetection/cascade_classifier/objectDetection.py
@end_toggle
@add_toggle_cpp
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/photo/hdr_imaging/hdr_imaging.cpp)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/photo/hdr_imaging/hdr_imaging.cpp)
@include samples/cpp/tutorial_code/photo/hdr_imaging/hdr_imaging.cpp
@end_toggle
@add_toggle_java
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/photo/hdr_imaging/HDRImagingDemo.java)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/photo/hdr_imaging/HDRImagingDemo.java)
@include samples/java/tutorial_code/photo/hdr_imaging/HDRImagingDemo.java
@end_toggle
@add_toggle_python
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/photo/hdr_imaging/hdr_imaging.py)
+[here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/photo/hdr_imaging/hdr_imaging.py)
@include samples/python/tutorial_code/photo/hdr_imaging/hdr_imaging.py
@end_toggle
-------------
Data directory that contains images, exposure times and `list.txt` file can be downloaded from
-[here](https://github.com/opencv/opencv_extra/tree/master/testdata/cv/hdr/exposures).
+[here](https://github.com/opencv/opencv_extra/tree/4.x/testdata/cv/hdr/exposures).
Explanation
-----------
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/ml/introduction_to_pca/introduction_to_pca.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ml/introduction_to_pca/IntroductionToPCADemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ml/introduction_to_pca/IntroductionToPCADemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/ml/introduction_to_pca/IntroductionToPCADemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ml/introduction_to_pca/introduction_to_pca.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ml/introduction_to_pca/introduction_to_pca.py)
- **Code at glance:**
@include samples/python/tutorial_code/ml/introduction_to_pca/introduction_to_pca.py
@end_toggle
-@note Another example using PCA for dimensionality reduction while maintaining an amount of variance can be found at [opencv_source_code/samples/cpp/pca.cpp](https://github.com/opencv/opencv/tree/master/samples/cpp/pca.cpp)
+@note Another example using PCA for dimensionality reduction while maintaining an amount of variance can be found at [opencv_source_code/samples/cpp/pca.cpp](https://github.com/opencv/opencv/tree/4.x/samples/cpp/pca.cpp)
Explanation
-----------
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ml/introduction_to_svm/introduction_to_svm.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ml/introduction_to_svm/introduction_to_svm.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/ml/introduction_to_svm/introduction_to_svm.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ml/introduction_to_svm/IntroductionToSVMDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ml/introduction_to_svm/IntroductionToSVMDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/ml/introduction_to_svm/IntroductionToSVMDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ml/introduction_to_svm/introduction_to_svm.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ml/introduction_to_svm/introduction_to_svm.py)
- **Code at glance:**
@include samples/python/tutorial_code/ml/introduction_to_svm/introduction_to_svm.py
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/meanshift/meanshift.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/video/meanshift/meanshift.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/video/meanshift/meanshift.cpp
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/video/meanshift/meanshift.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/video/meanshift/meanshift.py)
- **Code at glance:**
@include samples/python/tutorial_code/video/meanshift/meanshift.py
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/video/meanshift/MeanshiftDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/video/meanshift/MeanshiftDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/video/meanshift/MeanshiftDemo.java
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/meanshift/camshift.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/video/meanshift/camshift.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/video/meanshift/camshift.cpp
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/video/meanshift/camshift.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/video/meanshift/camshift.py)
- **Code at glance:**
@include samples/python/tutorial_code/video/meanshift/camshift.py
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/video/meanshift/CamshiftDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/video/meanshift/CamshiftDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/video/meanshift/CamshiftDemo.java
Exercises
---------
--# OpenCV comes with a Python [sample](https://github.com/opencv/opencv/blob/master/samples/python/camshift.py) for an interactive demo of camshift. Use it, hack it, understand
+-# OpenCV comes with a Python [sample](https://github.com/opencv/opencv/blob/4.x/samples/python/camshift.py) for an interactive demo of camshift. Use it, hack it, understand
it.
-----------
You may also find the source code in `samples/cpp/tutorial_code/ml/non_linear_svms` folder of the OpenCV source library or
-[download it from here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp).
+[download it from here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp).
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/ml/non_linear_svms/non_linear_svms.cpp
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ml/non_linear_svms/NonLinearSVMsDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/ml/non_linear_svms/NonLinearSVMsDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/ml/non_linear_svms/NonLinearSVMsDemo.java
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ml/non_linear_svms/non_linear_svms.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/ml/non_linear_svms/non_linear_svms.py)
- **Code at glance:**
@include samples/python/tutorial_code/ml/non_linear_svms/non_linear_svms.py
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/optical_flow/optical_flow.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/video/optical_flow/optical_flow.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/video/optical_flow/optical_flow.cpp
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/video/optical_flow/optical_flow.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/video/optical_flow/optical_flow.py)
- **Code at glance:**
@include samples/python/tutorial_code/video/optical_flow/optical_flow.py
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/video/optical_flow/OpticalFlowDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/video/optical_flow/OpticalFlowDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/video/optical_flow/OpticalFlowDemo.java
@add_toggle_cpp
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/optical_flow/optical_flow_dense.cpp)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/tutorial_code/video/optical_flow/optical_flow_dense.cpp)
- **Code at glance:**
@include samples/cpp/tutorial_code/video/optical_flow/optical_flow_dense.cpp
@add_toggle_python
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/video/optical_flow/optical_flow_dense.py)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/python/tutorial_code/video/optical_flow/optical_flow_dense.py)
- **Code at glance:**
@include samples/python/tutorial_code/video/optical_flow/optical_flow_dense.py
@add_toggle_java
- **Downloadable code**: Click
- [here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/video/optical_flow/OpticalFlowDenseDemo.java)
+ [here](https://github.com/opencv/opencv/tree/4.x/samples/java/tutorial_code/video/optical_flow/OpticalFlowDenseDemo.java)
- **Code at glance:**
@include samples/java/tutorial_code/video/optical_flow/OpticalFlowDenseDemo.java
----
This tutorial code's is shown lines below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/stitching.cpp).
+[here](https://github.com/opencv/opencv/tree/4.x/samples/cpp/stitching.cpp).
@include samples/cpp/stitching.cpp
<H4>stitching_detailed</H4>
@add_toggle_cpp
-[stitching_detailed.cpp](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/stitching_detailed.cpp)
+[stitching_detailed.cpp](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/cpp/stitching_detailed.cpp)
@end_toggle
@add_toggle_python
-[stitching_detailed.py](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/stitching_detailed.py)
+[stitching_detailed.py](https://raw.githubusercontent.com/opencv/opencv/4.x/samples/python/stitching_detailed.py)
@end_toggle
stitching_detailed program uses command line to get stitching parameter. Many parameters exists. Above examples shows some command line parameters possible :
-You can find all images in https://github.com/opencv/opencv_extra/tree/master/testdata/stitching
+You can find all images in https://github.com/opencv/opencv_extra/tree/4.x/testdata/stitching
Working with a boosted cascade of weak classifiers includes two major stages: the training and the detection stage. The detection stage using either HAAR or LBP based models, is described in the @ref tutorial_cascade_classifier "object detection tutorial". This documentation gives an overview of the functionality needed to train your own boosted cascade of weak classifiers. The current guide will walk through all the different stages: collecting training data, preparation of the training data and executing the actual model training.
-To support this tutorial, several official OpenCV applications will be used: [opencv_createsamples](https://github.com/opencv/opencv/tree/master/apps/createsamples), [opencv_annotation](https://github.com/opencv/opencv/tree/master/apps/annotation), [opencv_traincascade](https://github.com/opencv/opencv/tree/master/apps/traincascade) and [opencv_visualisation](https://github.com/opencv/opencv/tree/master/apps/visualisation).
+To support this tutorial, several official OpenCV applications will be used: [opencv_createsamples](https://github.com/opencv/opencv/tree/4.x/apps/createsamples), [opencv_annotation](https://github.com/opencv/opencv/tree/4.x/apps/annotation), [opencv_traincascade](https://github.com/opencv/opencv/tree/4.x/apps/traincascade) and [opencv_visualisation](https://github.com/opencv/opencv/tree/4.x/apps/visualisation).
@note Createsamples and traincascade are disabled since OpenCV 4.0. Consider using these apps for training from 3.4 branch for Cascade Classifier. Model format is the same between 3.4 and 4.x.
3. Merge the results into a single disparity map.
With this algorithm, a dual GPU gave a 180% performance increase comparing to the single Fermi GPU.
-For a source code example, see <https://github.com/opencv/opencv/tree/master/samples/gpu/>.
+For a source code example, see <https://github.com/opencv/opencv/tree/4.x/samples/gpu/>.
/**
Helper header to support SIMD intrinsics (universal intrinsics) in user code.
-Intrinsics documentation: https://docs.opencv.org/master/df/d91/group__core__hal__intrin.html
+Intrinsics documentation: https://docs.opencv.org/4.x/df/d91/group__core__hal__intrin.html
Checks of target CPU instruction set based on compiler definitions don't work well enough.
"with weights from OpenCV's face detection network. "
"Only backbone part of SSD model is converted this way. "
"Look for .pbtxt configuration file at "
- "https://github.com/opencv/opencv_extra/tree/master/testdata/dnn/opencv_face_detector.pbtxt")
+ "https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn/opencv_face_detector.pbtxt")
parser.add_argument('--model', help='Path to .caffemodel weights', required=True)
parser.add_argument('--proto', help='Path to .prototxt Caffe model definition', required=True)
parser.add_argument('--pb', help='Path to output .pb TensorFlow model', required=True)
parser = argparse.ArgumentParser()
parser.add_argument("--imgs_dir", help="path to ImageNet validation subset images dir, ILSVRC2012_img_val dir")
parser.add_argument("--img_cls_file", help="path to file with classes ids for images, download it here:"
- "https://github.com/opencv/opencv_extra/tree/master/testdata/dnn/img_classes_inception.txt")
+ "https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn/img_classes_inception.txt")
parser.add_argument("--model", help="path to tensorflow model, download it here:"
"https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip")
parser.add_argument("--log", help="path to logging file")
parser.add_argument("--val_names", help="path to file with validation set image names, download it here: "
"https://github.com/shelhamer/fcn.berkeleyvision.org/blob/master/data/pascal/seg11valid.txt")
parser.add_argument("--cls_file", help="path to file with colors for classes, download it here: "
- "https://github.com/opencv/opencv/blob/master/samples/data/dnn/pascal-classes.txt")
+ "https://github.com/opencv/opencv/blob/4.x/samples/data/dnn/pascal-classes.txt")
parser.add_argument("--prototxt", help="path to caffe prototxt, download it here: "
- "https://github.com/opencv/opencv/blob/master/samples/data/dnn/fcn8s-heavy-pascal.prototxt")
+ "https://github.com/opencv/opencv/blob/4.x/samples/data/dnn/fcn8s-heavy-pascal.prototxt")
parser.add_argument("--caffemodel", help="path to caffemodel file, download it here: "
"http://dl.caffe.berkeleyvision.org/fcn8s-heavy-pascal.caffemodel")
parser.add_argument("--log", help="path to logging file")
regions are calculated rapidly using integral images (see below and the integral description).
To see the object detector at work, have a look at the facedetect demo:
-<https://github.com/opencv/opencv/tree/master/samples/cpp/dbt_face_detection.cpp>
+<https://github.com/opencv/opencv/tree/4.x/samples/cpp/dbt_face_detection.cpp>
The following reference is for the detection part only. There is a separate application called
opencv_traincascade that can train a cascade of boosted classifiers from a set of samples.
repoPath = None
extraTestDataPath = None
# github repository url
- repoUrl = 'https://raw.github.com/opencv/opencv/master'
+ repoUrl = 'https://raw.github.com/opencv/opencv/4.x'
def find_file(self, filename, searchPaths=[], required=True):
searchPaths = searchPaths if searchPaths else [self.repoPath, self.extraTestDataPath]
This folder contains toolchains and additional files that are needed for cross compilation.
For more information see introduction tutorials for target platform in documentation:
-https://docs.opencv.org/master/df/d65/tutorial_table_of_content_introduction.html
+https://docs.opencv.org/4.x/df/d65/tutorial_table_of_content_introduction.html
// This sample is based on "Camera calibration With OpenCV" tutorial:
-// https://docs.opencv.org/3.4/d4/d94/tutorial_camera_calibration.html
+// https://docs.opencv.org/4.x/d4/d94/tutorial_camera_calibration.html
//
// It uses standard OpenCV asymmetric circles grid pattern 11x4:
-// https://github.com/opencv/opencv/blob/3.4/doc/acircles_pattern.png
+// https://github.com/opencv/opencv/blob/4.x/doc/acircles_pattern.png
// The results are the camera matrix and 5 distortion coefficients.
//
// Tap on highlighted pattern to capture pattern corners for calibration.
// These descriptors are going to be detecting and computing BLOBS with 6 different params
// Param for first BLOB detector we want all
- typeDesc.push_back("BLOB"); // see http://docs.opencv.org/master/d0/d7a/classcv_1_1SimpleBlobDetector.html
+ typeDesc.push_back("BLOB"); // see http://docs.opencv.org/4.x/d0/d7a/classcv_1_1SimpleBlobDetector.html
pBLOB.push_back(pDefaultBLOB);
pBLOB.back().filterByArea = true;
pBLOB.back().minArea = 1;
"\tThis will detect only the face in image.jpg.\n";
cout << " \n\nThe classifiers for face and eyes can be downloaded from : "
- " \nhttps://github.com/opencv/opencv/tree/master/data/haarcascades";
+ " \nhttps://github.com/opencv/opencv/tree/4.x/data/haarcascades";
cout << "\n\nThe classifiers for nose and mouth can be downloaded from : "
- " \nhttps://github.com/opencv/opencv_contrib/tree/master/modules/face/data/cascades\n";
+ " \nhttps://github.com/opencv/opencv_contrib/tree/4.x/modules/face/data/cascades\n";
}
static void detectFaces(Mat& img, vector<Rect_<int> >& faces, string cascade_path)
cout << "This program demonstrates the use of template matching with mask." << endl
<< endl
- << "Available methods: https://docs.opencv.org/master/df/dfb/group__imgproc__object.html#ga3a7850640f1fe1f58fe91a2d7583695d" << endl
+ << "Available methods: https://docs.opencv.org/4.x/df/dfb/group__imgproc__object.html#ga3a7850640f1fe1f58fe91a2d7583695d" << endl
<< " TM_SQDIFF = " << (int)TM_SQDIFF << endl
<< " TM_SQDIFF_NORMED = " << (int)TM_SQDIFF_NORMED << endl
<< " TM_CCORR = " << (int)TM_CCORR << endl
vector<String> typeAlgoMatch;
vector<String> fileName;
// This descriptor are going to be detect and compute
- typeDesc.push_back("AKAZE-DESCRIPTOR_KAZE_UPRIGHT"); // see https://docs.opencv.org/master/d8/d30/classcv_1_1AKAZE.html
- typeDesc.push_back("AKAZE"); // see http://docs.opencv.org/master/d8/d30/classcv_1_1AKAZE.html
- typeDesc.push_back("ORB"); // see http://docs.opencv.org/master/de/dbf/classcv_1_1BRISK.html
- typeDesc.push_back("BRISK"); // see http://docs.opencv.org/master/db/d95/classcv_1_1ORB.html
- // This algorithm would be used to match descriptors see http://docs.opencv.org/master/db/d39/classcv_1_1DescriptorMatcher.html#ab5dc5036569ecc8d47565007fa518257
+ typeDesc.push_back("AKAZE-DESCRIPTOR_KAZE_UPRIGHT"); // see https://docs.opencv.org/4.x/d8/d30/classcv_1_1AKAZE.html
+ typeDesc.push_back("AKAZE"); // see http://docs.opencv.org/4.x/d8/d30/classcv_1_1AKAZE.html
+ typeDesc.push_back("ORB"); // see http://docs.opencv.org/4.x/de/dbf/classcv_1_1BRISK.html
+ typeDesc.push_back("BRISK"); // see http://docs.opencv.org/4.x/db/d95/classcv_1_1ORB.html
+ // This algorithm would be used to match descriptors see http://docs.opencv.org/4.x/db/d39/classcv_1_1DescriptorMatcher.html#ab5dc5036569ecc8d47565007fa518257
typeAlgoMatch.push_back("BruteForce");
typeAlgoMatch.push_back("BruteForce-L1");
typeAlgoMatch.push_back("BruteForce-Hamming");
If OpenCV is built with [Intel's Inference Engine support](https://github.com/opencv/opencv/wiki/Intel%27s-Deep-Learning-Inference-Engine-backend) you can use [Intel's pre-trained](https://github.com/opencv/open_model_zoo) models.
There are different preprocessing parameters such mean subtraction or scale factors for different models.
-You may check the most popular models and their parameters at [models.yml](https://github.com/opencv/opencv/blob/master/samples/dnn/models.yml) configuration file. It might be also used for aliasing samples parameters. In example,
+You may check the most popular models and their parameters at [models.yml](https://github.com/opencv/opencv/blob/4.x/samples/dnn/models.yml) configuration file. It might be also used for aliasing samples parameters. In example,
```bash
python object_detection.py opencv_fd --model /path/to/caffemodel --config /path/to/prototxt
python download_models.py --save_dir FaceDetector opencv_fd
```
-You can use default configuration files adopted for OpenCV from [here](https://github.com/opencv/opencv_extra/tree/master/testdata/dnn).
+You can use default configuration files adopted for OpenCV from [here](https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn).
You also can use the script to download necessary files from your code. Assume you have the following code inside ```your_script.py```:
**Note** that you can provide a directory using **save_dir** parameter or via **OPENCV_SAVE_DIR** environment variable.
#### Face detection
-[An origin model](https://github.com/opencv/opencv/tree/master/samples/dnn/face_detector)
+[An origin model](https://github.com/opencv/opencv/tree/4.x/samples/dnn/face_detector)
with single precision floating point weights has been quantized using [TensorFlow framework](https://www.tensorflow.org/).
To achieve the best accuracy run the model on BGR images resized to `300x300` applying mean subtraction
of values `(104, 177, 123)` for each blue, green and red channels correspondingly.
The following are accuracy metrics obtained using [COCO object detection evaluation
tool](http://cocodataset.org/#detections-eval) on [FDDB dataset](http://vis-www.cs.umass.edu/fddb/)
-(see [script](https://github.com/opencv/opencv/blob/master/modules/dnn/misc/face_detector_accuracy.py))
+(see [script](https://github.com/opencv/opencv/blob/4.x/modules/dnn/misc/face_detector_accuracy.py))
applying resize to `300x300` and keeping an origin images' sizes.
```
AP - Average Precision | FP32/FP16 | UINT8 | FP32/FP16 | UINT8 |
## References
* [Models downloading script](https://github.com/opencv/opencv/samples/dnn/download_models.py)
-* [Configuration files adopted for OpenCV](https://github.com/opencv/opencv_extra/tree/master/testdata/dnn)
+* [Configuration files adopted for OpenCV](https://github.com/opencv/opencv_extra/tree/4.x/testdata/dnn)
* [How to import models from TensorFlow Object Detection API](https://github.com/opencv/opencv/wiki/TensorFlow-Object-Detection-API)
-* [Names of classes from different datasets](https://github.com/opencv/opencv/tree/master/samples/data/dnn)
+* [Names of classes from different datasets](https://github.com/opencv/opencv/tree/4.x/samples/data/dnn)
function loadModels(callback) {
var utils = new Utils('');
- var proto = 'https://raw.githubusercontent.com/opencv/opencv/master/samples/dnn/face_detector/deploy_lowres.prototxt';
+ var proto = 'https://raw.githubusercontent.com/opencv/opencv/4.x/samples/dnn/face_detector/deploy_lowres.prototxt';
var weights = 'https://raw.githubusercontent.com/opencv/opencv_3rdparty/dnn_samples_face_detector_20180205_fp16/res10_300x300_ssd_iter_140000_fp16.caffemodel';
var recognModel = 'https://raw.githubusercontent.com/pyannote/pyannote-data/master/openface.nn4.small2.v1.t7';
utils.createFileFromUrl('face_detector.prototxt', proto, () => {
//
// it can be used for body pose detection, using either the COCO model(18 parts):
// http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/coco/pose_iter_440000.caffemodel
-// https://raw.githubusercontent.com/opencv/opencv_extra/master/testdata/dnn/openpose_pose_coco.prototxt
+// https://raw.githubusercontent.com/opencv/opencv_extra/4.x/testdata/dnn/openpose_pose_coco.prototxt
//
// or the MPI model(16 parts):
// http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/mpi/pose_iter_160000.caffemodel
-// https://raw.githubusercontent.com/opencv/opencv_extra/master/testdata/dnn/openpose_pose_mpi_faster_4_stages.prototxt
+// https://raw.githubusercontent.com/opencv/opencv_extra/4.x/testdata/dnn/openpose_pose_mpi_faster_4_stages.prototxt
//
// (to simplify this sample, the body models are restricted to a single person.)
//
# [wget]
# [download]
-wget -O opencv.zip https://github.com/opencv/opencv/archive/master.zip
+wget -O opencv.zip https://github.com/opencv/opencv/archive/4.x.zip
unzip opencv.zip
-mv opencv-master opencv
+mv opencv-4.x opencv
# [download]
# [prepare]
# [download]
git clone https://github.com/opencv/opencv.git
-git -C opencv checkout master
+git -C opencv checkout 4.x
# [download]
# [prepare]
sudo apt update && sudo apt install -y cmake g++ wget unzip
# Download and unpack sources
-wget -O opencv.zip https://github.com/opencv/opencv/archive/master.zip
+wget -O opencv.zip https://github.com/opencv/opencv/archive/4.x.zip
unzip opencv.zip
# Create build directory
mkdir -p build && cd build
# Configure
-cmake ../opencv-master
+cmake ../opencv-4.x
# Build
cmake --build .
sudo apt update && sudo apt install -y cmake g++ wget unzip
# Download and unpack sources
-wget -O opencv.zip https://github.com/opencv/opencv/archive/master.zip
-wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/master.zip
+wget -O opencv.zip https://github.com/opencv/opencv/archive/4.x.zip
+wget -O opencv_contrib.zip https://github.com/opencv/opencv_contrib/archive/4.x.zip
unzip opencv.zip
unzip opencv_contrib.zip
mkdir -p build && cd build
# Configure
-cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib-master/modules ../opencv-master
+cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib-4.x/modules ../opencv-4.x
# Build
cmake --build .
sizes = []
blender = None
timelapser = None
- # https://github.com/opencv/opencv/blob/master/samples/cpp/stitching_detailed.cpp#L725 ?
+ # https://github.com/opencv/opencv/blob/4.x/samples/cpp/stitching_detailed.cpp#L725 ?
for idx, name in enumerate(img_names):
full_img = cv.imread(name)
if not is_compose_scale_set:
// Number of experiment runs
int no_runs = 2;
- // https://docs.opencv.org/master/d3/d63/classcv_1_1Mat.html
+ // https://docs.opencv.org/4.x/d3/d63/classcv_1_1Mat.html
cv::Mat src_new(IMG_ROWS, IMG_COLS, CV_8UC1, (void *)raw_pixels);
// Set parameters
// Number of experiment runs
int no_runs = 2;
- // https://docs.opencv.org/master/d3/d63/classcv_1_1Mat.html
+ // https://docs.opencv.org/4.x/d3/d63/classcv_1_1Mat.html
cv::Mat src(IMG_ROWS, IMG_COLS, CV_8UC1, (void *)raw_pixels);
// Run calc Hist
projects / platform / upstream / opencv.git / commitdiff