BLUE = [255,0,0]
-img1 = cv2.imread('opencv_logo.png')
+img1 = cv2.imread('opencv-logo.png')
replicate = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BORDER_REPLICATE)
reflect = cv2.copyMakeBorder(img1,10,10,10,10,cv2.BORDER_REFLECT)
Here \f$\gamma\f$ is taken as zero.
@code{.py}
img1 = cv2.imread('ml.png')
-img2 = cv2.imread('opencv_logo.jpg')
+img2 = cv2.imread('opencv-logo.png')
dst = cv2.addWeighted(img1,0.7,img2,0.3,0)
@code{.py}
# Load two images
img1 = cv2.imread('messi5.jpg')
-img2 = cv2.imread('opencv_logo.png')
+img2 = cv2.imread('opencv-logo.png')
# I want to put logo on top-left corner, So I create a ROI
rows,cols,channels = img2.shape
import numpy as np
from matplotlib import pyplot as plt
-img = cv2.imread('opencv_logo.png')
+img = cv2.imread('opencv-logo-white.png')
blur = cv2.blur(img,(5,5))
See the code below:
@code{.py}
-img = cv2.imread('sudokusmall.png')
+img = cv2.imread('sudoku.png')
rows,cols,ch = img.shape
pts1 = np.float32([[56,65],[368,52],[28,387],[389,390]])
import cv2
import numpy as np
-img = cv2.imread('opencv_logo.png',0)
+img = cv2.imread('opencv-logo-white.png',0)
img = cv2.medianBlur(img,5)
cimg = cv2.cvtColor(img,cv2.COLOR_GRAY2BGR)
import cv2
import numpy as np
-img = cv2.imread('dave.jpg')
+img = cv2.imread('sudoku.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
import cv2
import numpy as np
-img = cv2.imread('dave.jpg')
+img = cv2.imread('sudoku.png')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)
import numpy as np
from matplotlib import pyplot as plt
-img = cv2.imread('dave.jpg',0)
+img = cv2.imread('sudoku.png',0)
img = cv2.medianBlur(img,5)
ret,th1 = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
"{ help h | | print help message }"
"{ image i | | specify input image}"
"{ camera c | | enable camera capturing }"
- "{ video v | ../data/768x576.avi | use video as input }"
+ "{ video v | ../data/vtest.avi | use video as input }"
"{ directory d | | images directory}"
};
namedWindow("people detector", 1);
string pattern_glob = "";
- string video_filename = "../data/768x576.avi";
+ string video_filename = "../data/vtest.avi";
int camera_id = -1;
if (parser.has("directory"))
{
int main(int argc, const char** argv)
{
cv::CommandLineParser cmd(argc, argv,
- "{ c camera | | use camera }"
- "{ f file | ../data/768x576.avi | input video file }"
- "{ m method | mog | method (mog, mog2, gmg, fgd) }"
- "{ h help | | print help message }");
+ "{ c camera | | use camera }"
+ "{ f file | ../data/vtest.avi | input video file }"
+ "{ m method | mog | method (mog, mog2, gmg, fgd) }"
+ "{ h help | | print help message }");
if (cmd.has("help") || !cmd.check())
{
TEST(MOG)
{
- const std::string inputFile = abspath("../data/768x576.avi");
+ const std::string inputFile = abspath("../data/vtest.avi");
cv::VideoCapture cap(inputFile);
- if (!cap.isOpened()) throw runtime_error("can't open ../data/768x576.avi");
+ if (!cap.isOpened()) throw runtime_error("can't open ../data/vtest.avi");
cv::Mat frame;
cap >> frame;
int main(int argc, const char** argv)
{
CommandLineParser cmd(argc, argv,
- "{ c camera | | use camera }"
- "{ f file | ../data/768x576.avi | input video file }"
- "{ t type | mog2 | method's type (knn, mog2) }"
- "{ h help | | print help message }"
- "{ m cpu_mode | false | press 'm' to switch OpenCL<->CPU}");
+ "{ c camera | | use camera }"
+ "{ f file | ../data/vtest.avi | input video file }"
+ "{ t type | mog2 | method's type (knn, mog2) }"
+ "{ h help | | print help message }"
+ "{ m cpu_mode | false | press 'm' to switch OpenCL<->CPU}");
if (cmd.has("help"))
{
"{ h help | | print help message }"
"{ i input | | specify input image}"
"{ c camera | -1 | enable camera capturing }"
- "{ v video | ../data/768x576.avi | use video as input }"
+ "{ v video | ../data/vtest.avi | use video as input }"
"{ g gray | | convert image to gray one or not}"
"{ s scale | 1.0 | resize the image before detect}"
"{ o output | | specify output path when input is images}";