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@ -85,11 +85,12 @@ void forward_detection_layer(const detection_layer l, network_state state)
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int size = get_detection_layer_output_size(l) * l.batch;
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memset(l.delta, 0, size * sizeof(float));
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for (i = 0; i < l.batch*locations; ++i) {
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int classes = l.objectness+l.classes;
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int classes = (l.objectness || l.background)+l.classes;
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int offset = i*(classes+l.coords);
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for (j = offset; j < offset+classes; ++j) {
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*(l.cost) += pow(state.truth[j] - l.output[j], 2);
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l.delta[j] = state.truth[j] - l.output[j];
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if(l.background && j == offset) l.delta[j] *= .1;
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}
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box truth;
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@ -115,9 +116,15 @@ void forward_detection_layer(const detection_layer l, network_state state)
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l.delta[j+2] = 4 * (state.truth[j+2] - l.output[j+2]);
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l.delta[j+3] = 4 * (state.truth[j+3] - l.output[j+3]);
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if(l.rescore){
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for (j = offset; j < offset+classes; ++j) {
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if(state.truth[j]) state.truth[j] = iou;
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l.delta[j] = state.truth[j] - l.output[j];
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if(l.objectness){
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state.truth[offset] = iou;
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l.delta[offset] = state.truth[offset] - l.output[offset];
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}
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else{
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for (j = offset; j < offset+classes; ++j) {
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if(state.truth[j]) state.truth[j] = iou;
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l.delta[j] = state.truth[j] - l.output[j];
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}
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}
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}
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}
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@ -145,7 +152,7 @@ void backward_detection_layer(const detection_layer l, network_state state)
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if (l.objectness) {
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}else if (l.background) gradient_array(l.output + out_i, l.coords, LOGISTIC, l.delta + out_i);
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for(j = 0; j < l.coords; ++j){
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for (j = 0; j < l.coords; ++j){
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state.delta[in_i++] += l.delta[out_i++];
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}
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if(l.joint) state.delta[in_i-l.coords-l.classes-l.joint] += latent_delta;
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