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| #ifdef USE_OPENCV | ||
| #include <opencv2/core/core.hpp> | ||
| #include <opencv2/highgui/highgui.hpp> | ||
| #include <opencv2/imgproc/imgproc.hpp> | ||
| #include <opencv2/videoio.hpp> | ||
| #include <opencv2/video.hpp> | ||
| #endif // USE_OPENCV | ||
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| #include <cmath> | ||
| #include <vector> | ||
| #include "caffe/util/math_functions.hpp" | ||
| #include "caffe/layers/assisted_excitation_layer.hpp" | ||
| #include "caffe/layers/region_loss_layer.hpp" | ||
| #include <iostream> | ||
| #include <algorithm> | ||
| #define BOUND(a,min_val,max_val) ( (a < min_val) ? min_val : (a >= max_val) ? (max_val) : a ) | ||
| #define M_PI 3.14159265358979323846/* pi */ | ||
| namespace caffe { | ||
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| template <typename Dtype> | ||
| void AssistedExcitationLayer<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom, | ||
| const vector<Blob<Dtype>*>& top) { | ||
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| const Dtype* bottom_data = bottom[0]->cpu_data(); | ||
| Dtype* top_data = top[0]->mutable_gpu_data(); | ||
| const int count = bottom[0]->count(); | ||
| caffe_copy(count, bottom_data, top_data); | ||
| const Dtype* label_data = bottom[1]->cpu_data(); //[label,x,y,w,h] | ||
| Dtype* swap_data = swap_.mutable_cpu_data(); | ||
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| int width = bottom[0]->width(); | ||
| int height = bottom[0]->height(); | ||
| const Dtype* mean_data = bottom[2]->cpu_data(); | ||
| //cv::Mat img(width, height, CV_8UC1); | ||
| //img = cv::Scalar(0); | ||
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| float alpha = cos ((this->iter_ / (float) this->max_iter_)*M_PI/2.0f); | ||
| //LOG(INFO) << alpha ; | ||
| for (int b = 0; b < bottom[0]->num(); b++) { | ||
| Dtype* mask_data = mask_.mutable_cpu_data(); | ||
| caffe_set(bottom[2]->count(), Dtype(0), mask_data); | ||
| for (int t = 0; t < 300; ++t) { | ||
| Dtype x = label_data[b * 300 * 5 + t * 5 + 1]; | ||
| Dtype y = label_data[b * 300 * 5 + t * 5 + 2]; | ||
| Dtype w = label_data[b * 300 * 5 + t * 5 + 3]; | ||
| Dtype h = label_data[b * 300 * 5 + t * 5 + 4]; | ||
| if (!x) | ||
| break; | ||
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| int lb_x = BOUND((int) ((x - w/2) * width + 0.5),0,width); | ||
| int lb_y = BOUND((int) ((y - h/2) * height + 0.5),0,height); | ||
| int rt_x = BOUND((int) ((x + w/2) * width + 0.5),0,width); | ||
| int rt_y = BOUND((int) ((y + h/2) * height + 0.5),0,height); | ||
| //LOG(INFO) << lb_x << "," << lb_y<< ","<< rt_x << "," << rt_y; | ||
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| for (int i = lb_y;i < rt_y; i++) { | ||
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| for (int j = lb_x; j < rt_x; j++) | ||
| { | ||
| int index = i * width + j + b*bottom[2]->count(1); | ||
| mask_data[index] = alpha*mean_data[index]; | ||
| //mask_data[index] = alpha; | ||
| //LOG(INFO) << index; | ||
| //caffe_set(count, alpha*mean_data[index], swap_data); | ||
| //ptr2[j] = (unsigned char) BOUND(fabs(mask_data[index])*255,0,255); | ||
| } | ||
| } | ||
| } | ||
| mask_data = mask_.mutable_gpu_data(); | ||
| for (int c=0;c<bottom[0]->channels();c++) { | ||
| int offset = bottom[0]->offset(b) + c*bottom[2]->count(1); | ||
| caffe_gpu_axpy(width*height, Dtype(1) , mask_data, &top_data[offset]); | ||
| } | ||
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| } | ||
| } | ||
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| template <typename Dtype> | ||
| void AssistedExcitationLayer<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top, | ||
| const vector<bool>& propagate_down, | ||
| const vector<Blob<Dtype>*>& bottom) { | ||
| if (propagate_down[0]) { | ||
| const int count = top[0]->count(); | ||
| const Dtype* top_data = top[0]->gpu_data(); | ||
| const Dtype* top_diff = top[0]->gpu_diff(); | ||
| Dtype* bottom_diff = bottom[0]->mutable_gpu_diff(); | ||
| caffe_copy(count, top_diff, bottom_diff); | ||
| } | ||
| } | ||
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| INSTANTIATE_LAYER_GPU_FUNCS(AssistedExcitationLayer); | ||
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| } // namespace caffe |