Added DNN Darknet Yolo v2 for object detection

2017-09-24 23:34:08 +03:00
parent 39e742765a
commit ecc34dc521
11 changed files with 1764 additions and 1 deletions
@@ -0,0 +1,140 @@
+/*M ///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+// Copyright (C) 2017, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other materials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "../precomp.hpp"
+#include <opencv2/dnn/shape_utils.hpp>
+#include <opencv2/dnn/all_layers.hpp>
+#include <iostream>
+
+namespace cv
+{
+namespace dnn
+{
+
+class ReorgLayerImpl : public ReorgLayer
+{
+    int reorgStride;
+public:
+
+    ReorgLayerImpl(const LayerParams& params)
+    {
+        setParamsFrom(params);
+
+        reorgStride = params.get<int>("reorg_stride", 2);
+        CV_Assert(reorgStride > 0);
+    }
+
+    bool getMemoryShapes(const std::vector<MatShape> &inputs,
+                         const int requiredOutputs,
+                         std::vector<MatShape> &outputs,
+                         std::vector<MatShape> &internals) const
+    {
+        CV_Assert(inputs.size() > 0);
+        outputs = std::vector<MatShape>(inputs.size(), shape(
+            inputs[0][0],
+            inputs[0][1] * reorgStride * reorgStride,
+            inputs[0][2] / reorgStride,
+            inputs[0][3] / reorgStride));
+
+        CV_Assert(outputs[0][0] > 0 && outputs[0][1] > 0 && outputs[0][2] > 0 && outputs[0][3] > 0);
+        CV_Assert(total(outputs[0]) == total(inputs[0]));
+
+        return false;
+    }
+
+    virtual bool supportBackend(int backendId)
+    {
+        return backendId == DNN_BACKEND_DEFAULT;
+    }
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    {
+        CV_TRACE_FUNCTION();
+        CV_TRACE_ARG_VALUE(name, "name", name.c_str());
+
+        for (size_t i = 0; i < inputs.size(); i++)
+        {
+            Mat srcBlob = *inputs[i];
+            MatShape inputShape = shape(srcBlob), outShape = shape(outputs[i]);
+            float *dstData = outputs[0].ptr<float>();
+            const float *srcData = srcBlob.ptr<float>();
+
+            int channels = inputShape[1], height = inputShape[2], width = inputShape[3];
+
+            int out_c = channels / (reorgStride*reorgStride);
+
+            for (int k = 0; k < channels; ++k) {
+                for (int j = 0; j < height; ++j) {
+                    for (int i = 0; i < width; ++i) {
+                        int out_index = i + width*(j + height*k);
+                        int c2 = k % out_c;
+                        int offset = k / out_c;
+                        int w2 = i*reorgStride + offset % reorgStride;
+                        int h2 = j*reorgStride + offset / reorgStride;
+                        int in_index = w2 + width*reorgStride*(h2 + height*reorgStride*c2);
+                        dstData[out_index] = srcData[in_index];
+                    }
+                }
+            }
+        }
+    }
+
+    virtual int64 getFLOPS(const std::vector<MatShape> &inputs,
+                           const std::vector<MatShape> &outputs) const
+    {
+        (void)outputs; // suppress unused variable warning
+
+        int64 flops = 0;
+        for(int i = 0; i < inputs.size(); i++)
+        {
+            flops += 21*total(inputs[i]);
+        }
+        return flops;
+    }
+};
+
+Ptr<ReorgLayer> ReorgLayer::create(const LayerParams& params)
+{
+    return Ptr<ReorgLayer>(new ReorgLayerImpl(params));
+}
+
+}  // namespace dnn
+}  // namespace cv