get regions
This commit is contained in:
Francesco Gatti
+13
-1
@@ -272,6 +272,11 @@ public:
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int stride;
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};
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struct box {
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float x, y, w, h;
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};
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/**
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Region layer
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Mantain same dimension but change C*H*W distribution
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@@ -279,16 +284,23 @@ public:
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class Region : public Layer {
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public:
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Region(Network *net, int classes, int coords, int num, float thresh);
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Region(Network *net, int classes, int coords, int num, float thresh, const char* fname_weights);
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virtual ~Region();
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virtual layerType_t getLayerType() { return LAYER_REGION; };
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virtual value_type* infer(dataDim_t &dim, value_type* srcData);
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value_type *bias_h, *bias_d;
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int classes, coords, num;
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float thresh;
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int entry_index(int batch, int location, int entry);
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box get_region_box(float *x, float *biases, int n, int index, int i, int j, int w, int h, int stride);
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void get_region_boxes( float *input, int w, int h, int netw, int neth, float thresh,
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float **probs, box *boxes, int only_objectness,
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int *map, float tree_thresh, int relative);
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void correct_region_boxes(box *boxes, int n, int w, int h, int netw, int neth, int relative);
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void interpretData();
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};
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+183
-1
@@ -5,7 +5,7 @@
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namespace tkDNN {
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Region::Region(Network *net, int classes, int coords, int num, float thresh) :
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Region::Region(Network *net, int classes, int coords, int num, float thresh, const char* fname_weights) :
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Layer(net) {
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this->classes = classes;
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@@ -20,6 +20,9 @@ Region::Region(Network *net, int classes, int coords, int num, float thresh) :
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output_dim.w = input_dim.w;
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output_dim.l = input_dim.l;
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//load anchors
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readBinaryFile(fname_weights, 2*num, &bias_h, &bias_d);
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checkCuda( cudaMalloc(&dstData, input_dim.tot()*sizeof(value_type)) );
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}
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@@ -56,4 +59,183 @@ value_type* Region::infer(dataDim_t &dim, value_type* srcData) {
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return dstData;
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}
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box Region::get_region_box(float *x, float *biases, int n, int index, int i, int j, int w, int h, int stride)
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{
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box b;
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b.x = (i + x[index + 0*stride]) / w;
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b.y = (j + x[index + 1*stride]) / h;
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b.w = exp(x[index + 2*stride]) * biases[2*n] / w;
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b.h = exp(x[index + 3*stride]) * biases[2*n+1] / h;
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return b;
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}
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void Region::get_region_boxes( float *input, int w, int h, int netw, int neth, float thresh,
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float **probs, box *boxes, int only_objectness,
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int *map, float tree_thresh, int relative) {
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int lh = output_dim.h;
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int lw = output_dim.w;
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float *predictions = input;
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for (int i = 0; i < lw*lh; ++i){
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int row = i / lw;
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int col = i % lw;
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for(int n = 0; n < num; ++n){
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int index = n*lw*lh + i;
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for(int j = 0; j < classes; ++j){
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probs[index][j] = 0;
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}
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int obj_index = entry_index(0, n*lw*lh + i, coords);
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int box_index = entry_index(0, n*lw*lh + i, 0);
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float scale = predictions[obj_index];
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boxes[index] = get_region_box(predictions, bias_h, n, box_index, col, row, lw, lh, lw*lh);
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float max = 0;
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for(int j = 0; j < classes; ++j){
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int class_index = entry_index(0, n*lw*lh + i, coords + 1 + j);
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float prob = scale*predictions[class_index];
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probs[index][j] = (prob > thresh) ? prob : 0;
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if(prob > max) max = prob;
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}
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probs[index][classes] = max;
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}
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}
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correct_region_boxes(boxes, lw*lh*num, w, h, netw, neth, relative);
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}
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void Region::correct_region_boxes(box *boxes, int n, int w, int h, int netw, int neth, int relative) {
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int i;
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int new_w=0;
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int new_h=0;
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if (((float)netw/w) < ((float)neth/h)) {
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new_w = netw;
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new_h = (h * netw)/w;
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} else {
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new_h = neth;
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new_w = (w * neth)/h;
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}
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for (i = 0; i < n; ++i){
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box b = boxes[i];
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b.x = (b.x - (netw - new_w)/2./netw) / ((float)new_w/netw);
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b.y = (b.y - (neth - new_h)/2./neth) / ((float)new_h/neth);
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b.w *= (float)netw/new_w;
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b.h *= (float)neth/new_h;
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if(!relative){
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b.x *= w;
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b.w *= w;
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b.y *= h;
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b.h *= h;
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}
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boxes[i] = b;
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}
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}
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//############################ BOX PROBABILITY UTILS ############################
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struct sortable_bbox {
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int index;
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int cl;
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float **probs;
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};
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int nms_comparator(const void *pa, const void *pb) {
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sortable_bbox a = *(sortable_bbox *)pa;
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sortable_bbox b = *(sortable_bbox *)pb;
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float diff = a.probs[a.index][b.cl] - b.probs[b.index][b.cl];
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if(diff < 0) return 1;
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else if(diff > 0) return -1;
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return 0;
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}
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float overlap(float x1, float w1, float x2, float w2) {
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float l1 = x1 - w1/2;
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float l2 = x2 - w2/2;
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float left = l1 > l2 ? l1 : l2;
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float r1 = x1 + w1/2;
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float r2 = x2 + w2/2;
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float right = r1 < r2 ? r1 : r2;
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return right - left;
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}
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float box_intersection(box a, box b) {
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float w = overlap(a.x, a.w, b.x, b.w);
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float h = overlap(a.y, a.h, b.y, b.h);
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if(w < 0 || h < 0) return 0;
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float area = w*h;
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return area;
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}
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float box_union(box a, box b) {
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float i = box_intersection(a, b);
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float u = a.w*a.h + b.w*b.h - i;
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return u;
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}
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float box_iou(box a, box b) {
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return box_intersection(a, b)/box_union(a, b);
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}
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int max_index(float *a, int n) {
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if(n <= 0) return -1;
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int i, max_i = 0;
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float max = a[0];
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for(i = 1; i < n; ++i){
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if(a[i] > max){
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max = a[i];
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max_i = i;
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}
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}
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return max_i;
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}
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//###############################################################################
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void Region::interpretData() {
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int imW = 768, imH = 576;
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int tot = output_dim.w*output_dim.h*num;
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float *lel = new value_type[output_dim.tot()];
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cudaMemcpy(lel, dstData, output_dim.tot()*sizeof(value_type), cudaMemcpyDeviceToHost);
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box *boxes = (box*) calloc(tot, sizeof(box));
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float **probs = (float**) calloc(tot, sizeof(float *));
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for(int j = 0; j < tot; ++j) probs[j] = (float*)calloc(classes + 1, sizeof(float *));
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get_region_boxes(lel, imW, imH, output_dim.w, output_dim.h, thresh, probs, boxes, 0, 0, 0.5, 1);
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//delete repeats
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sortable_bbox *s = (sortable_bbox*)calloc(tot, sizeof(sortable_bbox));
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for(int i = 0; i < tot; ++i){
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s[i].index = i;
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s[i].cl = classes;
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s[i].probs = probs;
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}
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qsort(s, tot, sizeof(sortable_bbox), nms_comparator);
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for(int i = 0; i < tot; ++i){
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if(probs[s[i].index][classes] == 0) continue;
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box a = boxes[s[i].index];
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for(int j = i+1; j < tot; ++j){
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box b = boxes[s[j].index];
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if (box_iou(a, b) > thresh){
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for(int k = 0; k < classes+1; ++k){
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probs[s[j].index][k] = 0;
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}
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}
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}
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}
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free(s);
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//
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//print results
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for(int i = 0; i < tot; ++i){
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int cl = max_index(probs[i], classes);
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float prob = probs[i][cl];
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if(prob > thresh) {
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//printf("%d %s: %.0f%%\n", i, names[class], prob*100);
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printf("%d: %.0f%%\n", cl, prob*100);
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}
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}
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}
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}
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@@ -12,6 +12,7 @@ const char *c10_bin = "../tests/yolo-tiny/layers/c10.bin";
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const char *c12_bin = "../tests/yolo-tiny/layers/c12.bin";
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const char *c13_bin = "../tests/yolo-tiny/layers/c13.bin";
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const char *c14_bin = "../tests/yolo-tiny/layers/c14.bin";
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const char *g15_bin = "../tests/yolo-tiny/layers/g15.bin";
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const char *output_bin = "../tests/yolo-tiny/layers/outputLEL.bin";
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int main() {
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@@ -49,7 +50,7 @@ int main() {
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tkDNN::Conv2d c13(&net, 1024, 3, 3, 1, 1, 1, 1, c13_bin, true);
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tkDNN::Activation a13(&net, tkDNN::ACTIVATION_LEAKY);
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tkDNN::Conv2d c14(&net, 125, 1, 1, 1, 1, 0, 0, c14_bin, false);
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tkDNN::Region g15(&net, 20, 4, 5, 0.6f);
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tkDNN::Region g15(&net, 20, 4, 5, 0.6f, g15_bin);
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// Load input
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value_type *data;
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@@ -86,5 +87,8 @@ int main() {
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std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
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std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
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std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
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std::cout<<"\n\nDetected objects: \n";
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g15.interpretData();
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return 0;
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}
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+5
-1
@@ -25,6 +25,7 @@ const char *c24_bin = "../tests/yolo/layers/c24.bin";
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const char *c26_bin = "../tests/yolo/layers/c26.bin";
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const char *c29_bin = "../tests/yolo/layers/c29.bin";
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const char *c30_bin = "../tests/yolo/layers/c30.bin";
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const char *g31_bin = "../tests/yolo/layers/g31.bin";
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const char *output_bin = "../tests/yolo/layers/output.bin";
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int main() {
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@@ -96,7 +97,7 @@ int main() {
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tkDNN::Conv2d c29(&net, 1024, 3, 3, 1, 1, 1, 1, c29_bin, true);
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tkDNN::Activation a29(&net, tkDNN::ACTIVATION_LEAKY);
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tkDNN::Conv2d c30(&net, 425, 1, 1, 1, 1, 0, 0, c30_bin, false);
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tkDNN::Region g31(&net, 80, 4, 5, 0.6f);
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tkDNN::Region g31(&net, 80, 4, 5, 0.6f, g31_bin);
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// Load input
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value_type *data;
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@@ -133,5 +134,8 @@ int main() {
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std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
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std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
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std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
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std::cout<<"\n\nDetected objects: \n";
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g31.interpretData();
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return 0;
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}
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