Update links to OpenCV's face detection network

diff --git a/modules/dnn/misc/face_detector_accuracy.py b/modules/dnn/misc/face_detector_accuracy.py
index 0e9125e..2f0350e 100644 (file)
--- a/modules/dnn/misc/face_detector_accuracy.py
+++ b/modules/dnn/misc/face_detector_accuracy.py
@@ -17,7 +17,6 @@ parser = argparse.ArgumentParser(
                     'using COCO evaluation tool, http://cocodataset.org/#detections-eval')
 parser.add_argument('--proto', help='Path to .prototxt of Caffe model or .pbtxt of TensorFlow graph')
 parser.add_argument('--model', help='Path to .caffemodel trained in Caffe or .pb from TensorFlow')
-parser.add_argument('--caffe', help='Indicate that tested model is from Caffe. Otherwise model from TensorFlow is expected.', action='store_true')
 parser.add_argument('--cascade', help='Optional path to trained Haar cascade as '
                                       'an additional model for evaluation')
 parser.add_argument('--ann', help='Path to text file with ground truth annotations')
@@ -141,10 +140,7 @@ with open('annotations.json', 'wt') as f:
 ### Obtain detections ##########################################################
 detections = []
 if args.proto and args.model:
-    if args.caffe:
-        net = cv.dnn.readNetFromCaffe(args.proto, args.model)
-    else:
-        net = cv.dnn.readNetFromTensorflow(args.model, args.proto)
+    net = cv.dnn.readNet(args.proto, args.model)
 
     def detect(img, imageId):
         imgWidth = img.shape[1]

diff --git a/samples/dnn/CMakeLists.txt b/samples/dnn/CMakeLists.txt
index e7d8c5d..0df7651 100644 (file)
--- a/samples/dnn/CMakeLists.txt
+++ b/samples/dnn/CMakeLists.txt
@@ -13,23 +13,32 @@ if(NOT BUILD_EXAMPLES OR NOT OCV_DEPENDENCIES_FOUND)
   return()
 endif()
 
-# Model branch name: dnn_samples_face_detector_20170830
-set(DNN_FACE_DETECTOR_MODEL_COMMIT "b2bfc75f6aea5b1f834ff0f0b865a7c18ff1459f")
-set(DNN_FACE_DETECTOR_MODEL_HASH "afbb6037fd180e8d2acb3b58ca737b9e")
-set(DNN_FACE_DETECTOR_MODEL_NAME "res10_300x300_ssd_iter_140000.caffemodel")
-set(DNN_FACE_DETECTOR_MODEL_DOWNLOAD_DIR "${CMAKE_CURRENT_LIST_DIR}/face_detector")
-if(COMMAND ocv_download)
-  ocv_download(FILENAME ${DNN_FACE_DETECTOR_MODEL_NAME}
-             HASH ${DNN_FACE_DETECTOR_MODEL_HASH}
-             URL
-               "$ENV{OPENCV_DNN_MODELS_URL}"
-               "${OPENCV_DNN_MODELS_URL}"
-               "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${DNN_FACE_DETECTOR_MODEL_COMMIT}/"
-             DESTINATION_DIR ${DNN_FACE_DETECTOR_MODEL_DOWNLOAD_DIR}
-             ID DNN_FACE_DETECTOR
-             RELATIVE_URL
-             STATUS res)
-endif()
+function(download_net name commit hash)
+  set(DNN_FACE_DETECTOR_MODEL_DOWNLOAD_DIR "${CMAKE_CURRENT_LIST_DIR}/face_detector")
+  if(COMMAND ocv_download)
+    ocv_download(FILENAME ${name}
+               HASH ${hash}
+               URL
+                 "$ENV{OPENCV_DNN_MODELS_URL}"
+                 "${OPENCV_DNN_MODELS_URL}"
+                 "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${commit}/"
+               DESTINATION_DIR ${DNN_FACE_DETECTOR_MODEL_DOWNLOAD_DIR}
+               ID DNN_FACE_DETECTOR
+               RELATIVE_URL
+               STATUS res)
+  endif()
+endfunction()
+
+# Model branch name: dnn_samples_face_detector_20180205_fp16
+download_net("res10_300x300_ssd_iter_140000_fp16.caffemodel"
+             "19512576c112aa2c7b6328cb0e8d589a4a90a26d"
+             "f737f886e33835410c69e3ccfe0720a1")
+
+# Model branch name: dnn_samples_face_detector_20180220_uint8
+download_net("opencv_face_detector_uint8.pb"
+             "7b425df276ba2161b8edaab0f0756f4a735d61b9"
+             "56acf81f55d9b9e96c3347bc65409b9e")
+
 project(dnn_samples)
 ocv_include_modules_recurse(${OPENCV_DNN_SAMPLES_REQUIRED_DEPS})
 file(GLOB_RECURSE dnn_samples RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.cpp)

diff --git a/samples/dnn/README.md b/samples/dnn/README.md
index 121b703..c438bb0 100644 (file)
--- a/samples/dnn/README.md
+++ b/samples/dnn/README.md
@@ -14,6 +14,34 @@
 | [Faster-RCNN](https://github.com/rbgirshick/py-faster-rcnn) | `1.0` | `800x600` | `102.9801, 115.9465, 122.7717` | BGR |
 | [R-FCN](https://github.com/YuwenXiong/py-R-FCN) | `1.0` | `800x600` | `102.9801 115.9465 122.7717` | BGR |
 
+#### Face detection
+[An origin model](https://github.com/opencv/opencv/tree/master/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))
+applying resize to `300x300` and keeping an origin images' sizes.
+```
+AP - Average Precision                            | FP32/FP16 | UINT8          | FP32/FP16 | UINT8          |
+AR - Average Recall                               | 300x300   | 300x300        | any size  | any size       |
+--------------------------------------------------|-----------|----------------|-----------|----------------|
+AP @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] | 0.408     | 0.408          | 0.378     | 0.328 (-0.050) |
+AP @[ IoU=0.50      | area=   all | maxDets=100 ] | 0.849     | 0.849          | 0.797     | 0.790 (-0.007) |
+AP @[ IoU=0.75      | area=   all | maxDets=100 ] | 0.251     | 0.251          | 0.208     | 0.140 (-0.068) |
+AP @[ IoU=0.50:0.95 | area= small | maxDets=100 ] | 0.050     | 0.051 (+0.001) | 0.107     | 0.070 (-0.037) |
+AP @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] | 0.381     | 0.379 (-0.002) | 0.380     | 0.368 (-0.012) |
+AP @[ IoU=0.50:0.95 | area= large | maxDets=100 ] | 0.455     | 0.455          | 0.412     | 0.337 (-0.075) |
+AR @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] | 0.299     | 0.299          | 0.279     | 0.246 (-0.033) |
+AR @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] | 0.482     | 0.482          | 0.476     | 0.436 (-0.040) |
+AR @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] | 0.496     | 0.496          | 0.491     | 0.451 (-0.040) |
+AR @[ IoU=0.50:0.95 | area= small | maxDets=100 ] | 0.189     | 0.193 (+0.004) | 0.284     | 0.232 (-0.052) |
+AR @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] | 0.481     | 0.480 (-0.001) | 0.470     | 0.458 (-0.012) |
+AR @[ IoU=0.50:0.95 | area= large | maxDets=100 ] | 0.528     | 0.528          | 0.520     | 0.462 (-0.058) |
+```
+
 ### Classification
 |    Model | Scale |   Size WxH|   Mean subtraction | Channels order |
 |---------------|-------|-----------|--------------------|-------|

diff --git a/samples/dnn/face_detector/opencv_face_detector.pbtxt b/samples/dnn/face_detector/opencv_face_detector.pbtxt
new file mode 100644 (file)
index 0000000..78ba0bd
--- /dev/null
+++ b/samples/dnn/face_detector/opencv_face_detector.pbtxt
@@ -0,0 +1,2294 @@
+node {
+  name: "data"
+  op: "Placeholder"
+  attr {
+    key: "dtype"
+    value {
+      type: DT_FLOAT
+    }
+  }
+}
+node {
+  name: "data_bn/FusedBatchNorm"
+  op: "FusedBatchNorm"
+  input: "data:0"
+  input: "data_bn/gamma"
+  input: "data_bn/beta"
+  input: "data_bn/mean"
+  input: "data_bn/std"
+  attr {
+    key: "epsilon"
+    value {
+      f: 1.00099996416e-05
+    }
+  }
+}
+node {
+  name: "data_scale/Mul"
+  op: "Mul"
+  input: "data_bn/FusedBatchNorm"
+  input: "data_scale/mul"
+}
+node {
+  name: "data_scale/BiasAdd"
+  op: "BiasAdd"
+  input: "data_scale/Mul"
+  input: "data_scale/add"
+}
+node {
+  name: "Pad"
+  op: "Pad"
+  input: "data_scale/BiasAdd"
+  input: "Pad/paddings"
+}
+node {
+  name: "conv1_h/Conv2D"
+  op: "Conv2D"
+  input: "Pad"
+  input: "conv1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "VALID"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv1_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv1_h/Conv2D"
+  input: "conv1_h/bias"
+}
+node {
+  name: "conv1_bn_h/FusedBatchNorm"
+  op: "FusedBatchNorm"
+  input: "conv1_h/BiasAdd"
+  input: "conv1_bn_h/gamma"
+  input: "conv1_bn_h/beta"
+  input: "conv1_bn_h/mean"
+  input: "conv1_bn_h/std"
+  attr {
+    key: "epsilon"
+    value {
+      f: 1.00099996416e-05
+    }
+  }
+}
+node {
+  name: "conv1_scale_h/Mul"
+  op: "Mul"
+  input: "conv1_bn_h/FusedBatchNorm"
+  input: "conv1_scale_h/mul"
+}
+node {
+  name: "conv1_scale_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv1_scale_h/Mul"
+  input: "conv1_scale_h/add"
+}
+node {
+  name: "Relu"
+  op: "Relu"
+  input: "conv1_scale_h/BiasAdd"
+}
+node {
+  name: "conv1_pool/MaxPool"
+  op: "MaxPool"
+  input: "Relu"
+  attr {
+    key: "ksize"
+    value {
+      list {
+        i: 1
+        i: 3
+        i: 3
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_64_1_conv1_h/Conv2D"
+  op: "Conv2D"
+  input: "conv1_pool/MaxPool"
+  input: "layer_64_1_conv1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_64_1_bn2_h/FusedBatchNorm"
+  op: "BiasAdd"
+  input: "layer_64_1_conv1_h/Conv2D"
+  input: "layer_64_1_conv1_h/Conv2D_bn_offset"
+}
+node {
+  name: "layer_64_1_scale2_h/Mul"
+  op: "Mul"
+  input: "layer_64_1_bn2_h/FusedBatchNorm"
+  input: "layer_64_1_scale2_h/mul"
+}
+node {
+  name: "layer_64_1_scale2_h/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_64_1_scale2_h/Mul"
+  input: "layer_64_1_scale2_h/add"
+}
+node {
+  name: "Relu_1"
+  op: "Relu"
+  input: "layer_64_1_scale2_h/BiasAdd"
+}
+node {
+  name: "layer_64_1_conv2_h/Conv2D"
+  op: "Conv2D"
+  input: "Relu_1"
+  input: "layer_64_1_conv2_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "add"
+  op: "Add"
+  input: "layer_64_1_conv2_h/Conv2D"
+  input: "conv1_pool/MaxPool"
+}
+node {
+  name: "layer_128_1_bn1_h/FusedBatchNorm"
+  op: "FusedBatchNorm"
+  input: "add"
+  input: "layer_128_1_bn1_h/gamma"
+  input: "layer_128_1_bn1_h/beta"
+  input: "layer_128_1_bn1_h/mean"
+  input: "layer_128_1_bn1_h/std"
+  attr {
+    key: "epsilon"
+    value {
+      f: 1.00099996416e-05
+    }
+  }
+}
+node {
+  name: "layer_128_1_scale1_h/Mul"
+  op: "Mul"
+  input: "layer_128_1_bn1_h/FusedBatchNorm"
+  input: "layer_128_1_scale1_h/mul"
+}
+node {
+  name: "layer_128_1_scale1_h/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_128_1_scale1_h/Mul"
+  input: "layer_128_1_scale1_h/add"
+}
+node {
+  name: "Relu_2"
+  op: "Relu"
+  input: "layer_128_1_scale1_h/BiasAdd"
+}
+node {
+  name: "layer_128_1_conv_expand_h/Conv2D"
+  op: "Conv2D"
+  input: "Relu_2"
+  input: "layer_128_1_conv_expand_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_128_1_conv1_h/Conv2D"
+  op: "Conv2D"
+  input: "Relu_2"
+  input: "layer_128_1_conv1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_128_1_bn2/FusedBatchNorm"
+  op: "BiasAdd"
+  input: "layer_128_1_conv1_h/Conv2D"
+  input: "layer_128_1_conv1_h/Conv2D_bn_offset"
+}
+node {
+  name: "layer_128_1_scale2/Mul"
+  op: "Mul"
+  input: "layer_128_1_bn2/FusedBatchNorm"
+  input: "layer_128_1_scale2/mul"
+}
+node {
+  name: "layer_128_1_scale2/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_128_1_scale2/Mul"
+  input: "layer_128_1_scale2/add"
+}
+node {
+  name: "Relu_3"
+  op: "Relu"
+  input: "layer_128_1_scale2/BiasAdd"
+}
+node {
+  name: "layer_128_1_conv2/Conv2D"
+  op: "Conv2D"
+  input: "Relu_3"
+  input: "layer_128_1_conv2/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "add_1"
+  op: "Add"
+  input: "layer_128_1_conv2/Conv2D"
+  input: "layer_128_1_conv_expand_h/Conv2D"
+}
+node {
+  name: "layer_256_1_bn1/FusedBatchNorm"
+  op: "FusedBatchNorm"
+  input: "add_1"
+  input: "layer_256_1_bn1/gamma"
+  input: "layer_256_1_bn1/beta"
+  input: "layer_256_1_bn1/mean"
+  input: "layer_256_1_bn1/std"
+  attr {
+    key: "epsilon"
+    value {
+      f: 1.00099996416e-05
+    }
+  }
+}
+node {
+  name: "layer_256_1_scale1/Mul"
+  op: "Mul"
+  input: "layer_256_1_bn1/FusedBatchNorm"
+  input: "layer_256_1_scale1/mul"
+}
+node {
+  name: "layer_256_1_scale1/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_256_1_scale1/Mul"
+  input: "layer_256_1_scale1/add"
+}
+node {
+  name: "Relu_4"
+  op: "Relu"
+  input: "layer_256_1_scale1/BiasAdd"
+}
+node {
+  name: "Pad_1"
+  op: "Pad"
+  input: "Relu_4"
+  input: "Pad_1/paddings"
+}
+node {
+  name: "layer_256_1_conv_expand/Conv2D"
+  op: "Conv2D"
+  input: "Relu_4"
+  input: "layer_256_1_conv_expand/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv4_3_norm/l2_normalize"
+  op: "L2Normalize"
+  input: "Relu_4:0"
+}
+node {
+  name: "conv4_3_norm/mul_1"
+  op: "Mul"
+  input: "conv4_3_norm/l2_normalize"
+  input: "conv4_3_norm/mul"
+}
+node {
+  name: "conv4_3_norm_mbox_loc/Conv2D"
+  op: "Conv2D"
+  input: "conv4_3_norm/mul_1"
+  input: "conv4_3_norm_mbox_loc/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv4_3_norm_mbox_loc/BiasAdd"
+  op: "BiasAdd"
+  input: "conv4_3_norm_mbox_loc/Conv2D"
+  input: "conv4_3_norm_mbox_loc/bias"
+}
+node {
+  name: "flatten/Reshape"
+  op: "Flatten"
+  input: "conv4_3_norm_mbox_loc/BiasAdd"
+}
+node {
+  name: "conv4_3_norm_mbox_conf/Conv2D"
+  op: "Conv2D"
+  input: "conv4_3_norm/mul_1"
+  input: "conv4_3_norm_mbox_conf/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv4_3_norm_mbox_conf/BiasAdd"
+  op: "BiasAdd"
+  input: "conv4_3_norm_mbox_conf/Conv2D"
+  input: "conv4_3_norm_mbox_conf/bias"
+}
+node {
+  name: "flatten_6/Reshape"
+  op: "Flatten"
+  input: "conv4_3_norm_mbox_conf/BiasAdd"
+}
+node {
+  name: "layer_256_1_conv1/Conv2D"
+  op: "Conv2D"
+  input: "Pad_1"
+  input: "layer_256_1_conv1/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "VALID"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_256_1_bn2/FusedBatchNorm"
+  op: "BiasAdd"
+  input: "layer_256_1_conv1/Conv2D"
+  input: "layer_256_1_conv1/Conv2D_bn_offset"
+}
+node {
+  name: "layer_256_1_scale2/Mul"
+  op: "Mul"
+  input: "layer_256_1_bn2/FusedBatchNorm"
+  input: "layer_256_1_scale2/mul"
+}
+node {
+  name: "layer_256_1_scale2/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_256_1_scale2/Mul"
+  input: "layer_256_1_scale2/add"
+}
+node {
+  name: "Relu_5"
+  op: "Relu"
+  input: "layer_256_1_scale2/BiasAdd"
+}
+node {
+  name: "layer_256_1_conv2/Conv2D"
+  op: "Conv2D"
+  input: "Relu_5"
+  input: "layer_256_1_conv2/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "add_2"
+  op: "Add"
+  input: "layer_256_1_conv2/Conv2D"
+  input: "layer_256_1_conv_expand/Conv2D"
+}
+node {
+  name: "layer_512_1_bn1/FusedBatchNorm"
+  op: "FusedBatchNorm"
+  input: "add_2"
+  input: "layer_512_1_bn1/gamma"
+  input: "layer_512_1_bn1/beta"
+  input: "layer_512_1_bn1/mean"
+  input: "layer_512_1_bn1/std"
+  attr {
+    key: "epsilon"
+    value {
+      f: 1.00099996416e-05
+    }
+  }
+}
+node {
+  name: "layer_512_1_scale1/Mul"
+  op: "Mul"
+  input: "layer_512_1_bn1/FusedBatchNorm"
+  input: "layer_512_1_scale1/mul"
+}
+node {
+  name: "layer_512_1_scale1/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_512_1_scale1/Mul"
+  input: "layer_512_1_scale1/add"
+}
+node {
+  name: "Relu_6"
+  op: "Relu"
+  input: "layer_512_1_scale1/BiasAdd"
+}
+node {
+  name: "layer_512_1_conv_expand_h/Conv2D"
+  op: "Conv2D"
+  input: "Relu_6"
+  input: "layer_512_1_conv_expand_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_512_1_conv1_h/Conv2D"
+  op: "Conv2D"
+  input: "Relu_6"
+  input: "layer_512_1_conv1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_512_1_bn2_h/FusedBatchNorm"
+  op: "BiasAdd"
+  input: "layer_512_1_conv1_h/Conv2D"
+  input: "layer_512_1_conv1_h/Conv2D_bn_offset"
+}
+node {
+  name: "layer_512_1_scale2_h/Mul"
+  op: "Mul"
+  input: "layer_512_1_bn2_h/FusedBatchNorm"
+  input: "layer_512_1_scale2_h/mul"
+}
+node {
+  name: "layer_512_1_scale2_h/BiasAdd"
+  op: "BiasAdd"
+  input: "layer_512_1_scale2_h/Mul"
+  input: "layer_512_1_scale2_h/add"
+}
+node {
+  name: "Relu_7"
+  op: "Relu"
+  input: "layer_512_1_scale2_h/BiasAdd"
+}
+node {
+  name: "layer_512_1_conv2_h/convolution/SpaceToBatchND"
+  op: "SpaceToBatchND"
+  input: "Relu_7"
+  input: "layer_512_1_conv2_h/convolution/SpaceToBatchND/block_shape"
+  input: "layer_512_1_conv2_h/convolution/SpaceToBatchND/paddings"
+  attr {
+    key: "Tblock_shape"
+    value {
+      type: DT_INT32
+    }
+  }
+}
+node {
+  name: "layer_512_1_conv2_h/convolution"
+  op: "Conv2D"
+  input: "layer_512_1_conv2_h/convolution/SpaceToBatchND"
+  input: "layer_512_1_conv2_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "VALID"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "layer_512_1_conv2_h/convolution/BatchToSpaceND"
+  op: "BatchToSpaceND"
+  input: "layer_512_1_conv2_h/convolution"
+  input: "layer_512_1_conv2_h/convolution/BatchToSpaceND/block_shape"
+  input: "layer_512_1_conv2_h/convolution/BatchToSpaceND/crops"
+  attr {
+    key: "Tblock_shape"
+    value {
+      type: DT_INT32
+    }
+  }
+  attr {
+    key: "Tcrops"
+    value {
+      type: DT_INT32
+    }
+  }
+}
+node {
+  name: "add_3"
+  op: "Add"
+  input: "layer_512_1_conv2_h/convolution/BatchToSpaceND"
+  input: "layer_512_1_conv_expand_h/Conv2D"
+}
+node {
+  name: "last_bn_h/FusedBatchNorm"
+  op: "FusedBatchNorm"
+  input: "add_3"
+  input: "last_bn_h/gamma"
+  input: "last_bn_h/beta"
+  input: "last_bn_h/mean"
+  input: "last_bn_h/std"
+  attr {
+    key: "epsilon"
+    value {
+      f: 1.00099996416e-05
+    }
+  }
+}
+node {
+  name: "last_scale_h/Mul"
+  op: "Mul"
+  input: "last_bn_h/FusedBatchNorm"
+  input: "last_scale_h/mul"
+}
+node {
+  name: "last_scale_h/BiasAdd"
+  op: "BiasAdd"
+  input: "last_scale_h/Mul"
+  input: "last_scale_h/add"
+}
+node {
+  name: "last_relu"
+  op: "Relu"
+  input: "last_scale_h/BiasAdd"
+}
+node {
+  name: "conv6_1_h/Conv2D"
+  op: "Conv2D"
+  input: "last_relu"
+  input: "conv6_1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv6_1_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv6_1_h/Conv2D"
+  input: "conv6_1_h/bias"
+}
+node {
+  name: "conv6_1_h/Relu"
+  op: "Relu"
+  input: "conv6_1_h/BiasAdd"
+}
+node {
+  name: "conv6_2_h/Conv2D"
+  op: "Conv2D"
+  input: "conv6_1_h/Relu"
+  input: "conv6_2_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv6_2_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv6_2_h/Conv2D"
+  input: "conv6_2_h/bias"
+}
+node {
+  name: "conv6_2_h/Relu"
+  op: "Relu"
+  input: "conv6_2_h/BiasAdd"
+}
+node {
+  name: "conv7_1_h/Conv2D"
+  op: "Conv2D"
+  input: "conv6_2_h/Relu"
+  input: "conv7_1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv7_1_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv7_1_h/Conv2D"
+  input: "conv7_1_h/bias"
+}
+node {
+  name: "conv7_1_h/Relu"
+  op: "Relu"
+  input: "conv7_1_h/BiasAdd"
+}
+node {
+  name: "Pad_2"
+  op: "Pad"
+  input: "conv7_1_h/Relu"
+  input: "Pad_2/paddings"
+}
+node {
+  name: "conv7_2_h/Conv2D"
+  op: "Conv2D"
+  input: "Pad_2"
+  input: "conv7_2_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "VALID"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 2
+        i: 2
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv7_2_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv7_2_h/Conv2D"
+  input: "conv7_2_h/bias"
+}
+node {
+  name: "conv7_2_h/Relu"
+  op: "Relu"
+  input: "conv7_2_h/BiasAdd"
+}
+node {
+  name: "conv8_1_h/Conv2D"
+  op: "Conv2D"
+  input: "conv7_2_h/Relu"
+  input: "conv8_1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv8_1_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv8_1_h/Conv2D"
+  input: "conv8_1_h/bias"
+}
+node {
+  name: "conv8_1_h/Relu"
+  op: "Relu"
+  input: "conv8_1_h/BiasAdd"
+}
+node {
+  name: "conv8_2_h/Conv2D"
+  op: "Conv2D"
+  input: "conv8_1_h/Relu"
+  input: "conv8_2_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv8_2_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv8_2_h/Conv2D"
+  input: "conv8_2_h/bias"
+}
+node {
+  name: "conv8_2_h/Relu"
+  op: "Relu"
+  input: "conv8_2_h/BiasAdd"
+}
+node {
+  name: "conv9_1_h/Conv2D"
+  op: "Conv2D"
+  input: "conv8_2_h/Relu"
+  input: "conv9_1_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv9_1_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv9_1_h/Conv2D"
+  input: "conv9_1_h/bias"
+}
+node {
+  name: "conv9_1_h/Relu"
+  op: "Relu"
+  input: "conv9_1_h/BiasAdd"
+}
+node {
+  name: "conv9_2_h/Conv2D"
+  op: "Conv2D"
+  input: "conv9_1_h/Relu"
+  input: "conv9_2_h/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv9_2_h/BiasAdd"
+  op: "BiasAdd"
+  input: "conv9_2_h/Conv2D"
+  input: "conv9_2_h/bias"
+}
+node {
+  name: "conv9_2_h/Relu"
+  op: "Relu"
+  input: "conv9_2_h/BiasAdd"
+}
+node {
+  name: "conv9_2_mbox_loc/Conv2D"
+  op: "Conv2D"
+  input: "conv9_2_h/Relu"
+  input: "conv9_2_mbox_loc/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv9_2_mbox_loc/BiasAdd"
+  op: "BiasAdd"
+  input: "conv9_2_mbox_loc/Conv2D"
+  input: "conv9_2_mbox_loc/bias"
+}
+node {
+  name: "flatten_5/Reshape"
+  op: "Flatten"
+  input: "conv9_2_mbox_loc/BiasAdd"
+}
+node {
+  name: "conv9_2_mbox_conf/Conv2D"
+  op: "Conv2D"
+  input: "conv9_2_h/Relu"
+  input: "conv9_2_mbox_conf/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv9_2_mbox_conf/BiasAdd"
+  op: "BiasAdd"
+  input: "conv9_2_mbox_conf/Conv2D"
+  input: "conv9_2_mbox_conf/bias"
+}
+node {
+  name: "flatten_11/Reshape"
+  op: "Flatten"
+  input: "conv9_2_mbox_conf/BiasAdd"
+}
+node {
+  name: "conv8_2_mbox_loc/Conv2D"
+  op: "Conv2D"
+  input: "conv8_2_h/Relu"
+  input: "conv8_2_mbox_loc/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv8_2_mbox_loc/BiasAdd"
+  op: "BiasAdd"
+  input: "conv8_2_mbox_loc/Conv2D"
+  input: "conv8_2_mbox_loc/bias"
+}
+node {
+  name: "flatten_4/Reshape"
+  op: "Flatten"
+  input: "conv8_2_mbox_loc/BiasAdd"
+}
+node {
+  name: "conv8_2_mbox_conf/Conv2D"
+  op: "Conv2D"
+  input: "conv8_2_h/Relu"
+  input: "conv8_2_mbox_conf/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv8_2_mbox_conf/BiasAdd"
+  op: "BiasAdd"
+  input: "conv8_2_mbox_conf/Conv2D"
+  input: "conv8_2_mbox_conf/bias"
+}
+node {
+  name: "flatten_10/Reshape"
+  op: "Flatten"
+  input: "conv8_2_mbox_conf/BiasAdd"
+}
+node {
+  name: "conv7_2_mbox_loc/Conv2D"
+  op: "Conv2D"
+  input: "conv7_2_h/Relu"
+  input: "conv7_2_mbox_loc/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv7_2_mbox_loc/BiasAdd"
+  op: "BiasAdd"
+  input: "conv7_2_mbox_loc/Conv2D"
+  input: "conv7_2_mbox_loc/bias"
+}
+node {
+  name: "flatten_3/Reshape"
+  op: "Flatten"
+  input: "conv7_2_mbox_loc/BiasAdd"
+}
+node {
+  name: "conv7_2_mbox_conf/Conv2D"
+  op: "Conv2D"
+  input: "conv7_2_h/Relu"
+  input: "conv7_2_mbox_conf/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
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+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv7_2_mbox_conf/BiasAdd"
+  op: "BiasAdd"
+  input: "conv7_2_mbox_conf/Conv2D"
+  input: "conv7_2_mbox_conf/bias"
+}
+node {
+  name: "flatten_9/Reshape"
+  op: "Flatten"
+  input: "conv7_2_mbox_conf/BiasAdd"
+}
+node {
+  name: "conv6_2_mbox_loc/Conv2D"
+  op: "Conv2D"
+  input: "conv6_2_h/Relu"
+  input: "conv6_2_mbox_loc/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv6_2_mbox_loc/BiasAdd"
+  op: "BiasAdd"
+  input: "conv6_2_mbox_loc/Conv2D"
+  input: "conv6_2_mbox_loc/bias"
+}
+node {
+  name: "flatten_2/Reshape"
+  op: "Flatten"
+  input: "conv6_2_mbox_loc/BiasAdd"
+}
+node {
+  name: "conv6_2_mbox_conf/Conv2D"
+  op: "Conv2D"
+  input: "conv6_2_h/Relu"
+  input: "conv6_2_mbox_conf/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "conv6_2_mbox_conf/BiasAdd"
+  op: "BiasAdd"
+  input: "conv6_2_mbox_conf/Conv2D"
+  input: "conv6_2_mbox_conf/bias"
+}
+node {
+  name: "flatten_8/Reshape"
+  op: "Flatten"
+  input: "conv6_2_mbox_conf/BiasAdd"
+}
+node {
+  name: "fc7_mbox_loc/Conv2D"
+  op: "Conv2D"
+  input: "last_relu"
+  input: "fc7_mbox_loc/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "fc7_mbox_loc/BiasAdd"
+  op: "BiasAdd"
+  input: "fc7_mbox_loc/Conv2D"
+  input: "fc7_mbox_loc/bias"
+}
+node {
+  name: "flatten_1/Reshape"
+  op: "Flatten"
+  input: "fc7_mbox_loc/BiasAdd"
+}
+node {
+  name: "mbox_loc"
+  op: "ConcatV2"
+  input: "flatten/Reshape"
+  input: "flatten_1/Reshape"
+  input: "flatten_2/Reshape"
+  input: "flatten_3/Reshape"
+  input: "flatten_4/Reshape"
+  input: "flatten_5/Reshape"
+  input: "mbox_loc/axis"
+}
+node {
+  name: "fc7_mbox_conf/Conv2D"
+  op: "Conv2D"
+  input: "last_relu"
+  input: "fc7_mbox_conf/weights"
+  attr {
+    key: "dilations"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+  attr {
+    key: "padding"
+    value {
+      s: "SAME"
+    }
+  }
+  attr {
+    key: "strides"
+    value {
+      list {
+        i: 1
+        i: 1
+        i: 1
+        i: 1
+      }
+    }
+  }
+}
+node {
+  name: "fc7_mbox_conf/BiasAdd"
+  op: "BiasAdd"
+  input: "fc7_mbox_conf/Conv2D"
+  input: "fc7_mbox_conf/bias"
+}
+node {
+  name: "flatten_7/Reshape"
+  op: "Flatten"
+  input: "fc7_mbox_conf/BiasAdd"
+}
+node {
+  name: "mbox_conf"
+  op: "ConcatV2"
+  input: "flatten_6/Reshape"
+  input: "flatten_7/Reshape"
+  input: "flatten_8/Reshape"
+  input: "flatten_9/Reshape"
+  input: "flatten_10/Reshape"
+  input: "flatten_11/Reshape"
+  input: "mbox_conf/axis"
+}
+node {
+  name: "mbox_conf_reshape"
+  op: "Reshape"
+  input: "mbox_conf"
+  input: "reshape_before_softmax"
+}
+node {
+  name: "mbox_conf_softmax"
+  op: "Softmax"
+  input: "mbox_conf_reshape"
+  attr {
+    key: "axis"
+    value {
+      i: 2
+    }
+  }
+}
+node {
+  name: "mbox_conf_flatten"
+  op: "Flatten"
+  input: "mbox_conf_softmax"
+}
+node {
+  name: "PriorBox_0"
+  op: "PriorBox"
+  input: "conv4_3_norm/mul_1"
+  input: "data"
+  attr {
+    key: "aspect_ratio"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
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+        float_val: 2.0
+      }
+    }
+  }
+  attr {
+    key: "clip"
+    value {
+      b: false
+    }
+  }
+  attr {
+    key: "flip"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "max_size"
+    value {
+      i: 60
+    }
+  }
+  attr {
+    key: "min_size"
+    value {
+      i: 30
+    }
+  }
+  attr {
+    key: "offset"
+    value {
+      f: 0.5
+    }
+  }
+  attr {
+    key: "step"
+    value {
+      f: 8.0
+    }
+  }
+  attr {
+    key: "variance"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
+          dim {
+            size: 4
+          }
+        }
+        float_val: 0.10000000149
+        float_val: 0.10000000149
+        float_val: 0.20000000298
+        float_val: 0.20000000298
+      }
+    }
+  }
+}
+node {
+  name: "PriorBox_1"
+  op: "PriorBox"
+  input: "last_relu"
+  input: "data"
+  attr {
+    key: "aspect_ratio"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
+          dim {
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+        }
+        float_val: 2.0
+        float_val: 3.0
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+  }
+  attr {
+    key: "clip"
+    value {
+      b: false
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+  }
+  attr {
+    key: "flip"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "max_size"
+    value {
+      i: 111
+    }
+  }
+  attr {
+    key: "min_size"
+    value {
+      i: 60
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+  }
+  attr {
+    key: "offset"
+    value {
+      f: 0.5
+    }
+  }
+  attr {
+    key: "step"
+    value {
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+  }
+  attr {
+    key: "variance"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
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+          }
+        }
+        float_val: 0.10000000149
+        float_val: 0.10000000149
+        float_val: 0.20000000298
+        float_val: 0.20000000298
+      }
+    }
+  }
+}
+node {
+  name: "PriorBox_2"
+  op: "PriorBox"
+  input: "conv6_2_h/Relu"
+  input: "data"
+  attr {
+    key: "aspect_ratio"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
+          dim {
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+          }
+        }
+        float_val: 2.0
+        float_val: 3.0
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+  }
+  attr {
+    key: "clip"
+    value {
+      b: false
+    }
+  }
+  attr {
+    key: "flip"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "max_size"
+    value {
+      i: 162
+    }
+  }
+  attr {
+    key: "min_size"
+    value {
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+  }
+  attr {
+    key: "offset"
+    value {
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+    }
+  }
+  attr {
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+    value {
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+  attr {
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+        tensor_shape {
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+        float_val: 0.10000000149
+        float_val: 0.10000000149
+        float_val: 0.20000000298
+        float_val: 0.20000000298
+      }
+    }
+  }
+}
+node {
+  name: "PriorBox_3"
+  op: "PriorBox"
+  input: "conv7_2_h/Relu"
+  input: "data"
+  attr {
+    key: "aspect_ratio"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
+          dim {
+            size: 2
+          }
+        }
+        float_val: 2.0
+        float_val: 3.0
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+    }
+  }
+  attr {
+    key: "clip"
+    value {
+      b: false
+    }
+  }
+  attr {
+    key: "flip"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "max_size"
+    value {
+      i: 213
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+  }
+  attr {
+    key: "min_size"
+    value {
+      i: 162
+    }
+  }
+  attr {
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+    value {
+      f: 0.5
+    }
+  }
+  attr {
+    key: "step"
+    value {
+      f: 64.0
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+  }
+  attr {
+    key: "variance"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
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+            size: 4
+          }
+        }
+        float_val: 0.10000000149
+        float_val: 0.10000000149
+        float_val: 0.20000000298
+        float_val: 0.20000000298
+      }
+    }
+  }
+}
+node {
+  name: "PriorBox_4"
+  op: "PriorBox"
+  input: "conv8_2_h/Relu"
+  input: "data"
+  attr {
+    key: "aspect_ratio"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
+          dim {
+            size: 1
+          }
+        }
+        float_val: 2.0
+      }
+    }
+  }
+  attr {
+    key: "clip"
+    value {
+      b: false
+    }
+  }
+  attr {
+    key: "flip"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "max_size"
+    value {
+      i: 264
+    }
+  }
+  attr {
+    key: "min_size"
+    value {
+      i: 213
+    }
+  }
+  attr {
+    key: "offset"
+    value {
+      f: 0.5
+    }
+  }
+  attr {
+    key: "step"
+    value {
+      f: 100.0
+    }
+  }
+  attr {
+    key: "variance"
+    value {
+      tensor {
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+        tensor_shape {
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+            size: 4
+          }
+        }
+        float_val: 0.10000000149
+        float_val: 0.10000000149
+        float_val: 0.20000000298
+        float_val: 0.20000000298
+      }
+    }
+  }
+}
+node {
+  name: "PriorBox_5"
+  op: "PriorBox"
+  input: "conv9_2_h/Relu"
+  input: "data"
+  attr {
+    key: "aspect_ratio"
+    value {
+      tensor {
+        dtype: DT_FLOAT
+        tensor_shape {
+          dim {
+            size: 1
+          }
+        }
+        float_val: 2.0
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+    }
+  }
+  attr {
+    key: "clip"
+    value {
+      b: false
+    }
+  }
+  attr {
+    key: "flip"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "max_size"
+    value {
+      i: 315
+    }
+  }
+  attr {
+    key: "min_size"
+    value {
+      i: 264
+    }
+  }
+  attr {
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+    value {
+      f: 0.5
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+  }
+  attr {
+    key: "step"
+    value {
+      f: 300.0
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+  attr {
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+    value {
+      tensor {
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+        tensor_shape {
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+        }
+        float_val: 0.10000000149
+        float_val: 0.10000000149
+        float_val: 0.20000000298
+        float_val: 0.20000000298
+      }
+    }
+  }
+}
+node {
+  name: "mbox_priorbox"
+  op: "ConcatV2"
+  input: "PriorBox_0"
+  input: "PriorBox_1"
+  input: "PriorBox_2"
+  input: "PriorBox_3"
+  input: "PriorBox_4"
+  input: "PriorBox_5"
+  input: "mbox_loc/axis"
+}
+node {
+  name: "detection_out"
+  op: "DetectionOutput"
+  input: "mbox_loc"
+  input: "mbox_conf_flatten"
+  input: "mbox_priorbox"
+  attr {
+    key: "background_label_id"
+    value {
+      i: 0
+    }
+  }
+  attr {
+    key: "code_type"
+    value {
+      s: "CENTER_SIZE"
+    }
+  }
+  attr {
+    key: "confidence_threshold"
+    value {
+      f: 0.00999999977648
+    }
+  }
+  attr {
+    key: "keep_top_k"
+    value {
+      i: 200
+    }
+  }
+  attr {
+    key: "nms_threshold"
+    value {
+      f: 0.449999988079
+    }
+  }
+  attr {
+    key: "num_classes"
+    value {
+      i: 2
+    }
+  }
+  attr {
+    key: "share_location"
+    value {
+      b: true
+    }
+  }
+  attr {
+    key: "top_k"
+    value {
+      i: 400
+    }
+  }
+}
+node {
+  name: "reshape_before_softmax"
+  op: "Const"
+  attr {
+    key: "value"
+    value {
+      tensor {
+        dtype: DT_INT32
+        tensor_shape {
+          dim {
+            size: 3
+          }
+        }
+        int_val: 0
+        int_val: -1
+        int_val: 2
+      }
+    }
+  }
+}
+library {
+}

diff --git a/samples/dnn/js_face_recognition.html b/samples/dnn/js_face_recognition.html
index be02645..887f5f1 100644 (file)
--- a/samples/dnn/js_face_recognition.html
+++ b/samples/dnn/js_face_recognition.html
@@ -70,7 +70,7 @@ function recognize(face) {
 function loadModels(callback) {
   var utils = new Utils('');
   var proto = 'https://raw.githubusercontent.com/opencv/opencv/master/samples/dnn/face_detector/deploy.prototxt';
-  var weights = 'https://github.com/opencv/opencv_3rdparty/raw/19512576c112aa2c7b6328cb0e8d589a4a90a26d/res10_300x300_ssd_iter_140000_fp16.caffemodel';
+  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, () => {
     document.getElementById('status').innerHTML = 'Downloading face_detector.caffemodel';