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#include "postprocess.h" |
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#include <math.h> |
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#include <stdint.h> |
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#include <stdio.h> |
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#include <stdlib.h> |
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#include <string.h> |
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#include <sys/time.h> |
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#include <set> |
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#include <vector> |
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#define LABEL_NALE_TXT_PATH "./model/coco_80_labels_list.txt" |
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static char *labels[OBJ_CLASS_NUM]; |
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const int anchor0[6] = {10, 13, 16, 30, 33, 23}; |
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const int anchor1[6] = {30, 61, 62, 45, 59, 119}; |
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const int anchor2[6] = {116, 90, 156, 198, 373, 326}; |
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inline static int clamp(float val, int min, int max) { return val > min ? (val < max ? val : max) : min; } |
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char *readLine(FILE *fp, char *buffer, int *len) |
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{ |
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int ch; |
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int i = 0; |
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size_t buff_len = 0; |
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buffer = (char *)malloc(buff_len + 1); |
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if (!buffer) |
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return NULL; |
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while ((ch = fgetc(fp)) != '\n' && ch != EOF) |
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{ |
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buff_len++; |
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void *tmp = realloc(buffer, buff_len + 1); |
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if (tmp == NULL) |
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{ |
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free(buffer); |
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return NULL; |
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} |
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buffer = (char *)tmp; |
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buffer[i] = (char)ch; |
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i++; |
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} |
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buffer[i] = '\0'; |
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*len = buff_len; |
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if (ch == EOF && (i == 0 || ferror(fp))) |
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{ |
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free(buffer); |
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return NULL; |
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} |
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return buffer; |
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} |
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int readLines(const char *fileName, char *lines[], int max_line) |
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{ |
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FILE *file = fopen(fileName, "r"); |
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char *s; |
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int i = 0; |
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int n = 0; |
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if (file == NULL) |
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{ |
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printf("Open %s fail!\n", fileName); |
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return -1; |
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} |
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while ((s = readLine(file, s, &n)) != NULL) |
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{ |
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lines[i++] = s; |
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if (i >= max_line) |
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break; |
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} |
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fclose(file); |
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return i; |
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} |
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int loadLabelName(const char *locationFilename, char *label[]) |
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{ |
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printf("loadLabelName %s\n", locationFilename); |
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readLines(locationFilename, label, OBJ_CLASS_NUM); |
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return 0; |
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} |
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static float CalculateOverlap(float xmin0, float ymin0, float xmax0, float ymax0, float xmin1, float ymin1, float xmax1, |
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float ymax1) |
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{ |
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float w = fmax(0.f, fmin(xmax0, xmax1) - fmax(xmin0, xmin1) + 1.0); |
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float h = fmax(0.f, fmin(ymax0, ymax1) - fmax(ymin0, ymin1) + 1.0); |
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float i = w * h; |
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float u = (xmax0 - xmin0 + 1.0) * (ymax0 - ymin0 + 1.0) + (xmax1 - xmin1 + 1.0) * (ymax1 - ymin1 + 1.0) - i; |
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return u <= 0.f ? 0.f : (i / u); |
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} |
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static int nms(int validCount, std::vector<float> &outputLocations, std::vector<int> classIds, std::vector<int> &order, |
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int filterId, float threshold) |
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{ |
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for (int i = 0; i < validCount; ++i) |
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{ |
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int n = order[i]; |
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if (n == -1 || classIds[n] != filterId) |
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{ |
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continue; |
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} |
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for (int j = i + 1; j < validCount; ++j) |
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{ |
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int m = order[j]; |
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if (m == -1 || classIds[m] != filterId) |
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{ |
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continue; |
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} |
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float xmin0 = outputLocations[n * 4 + 0]; |
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float ymin0 = outputLocations[n * 4 + 1]; |
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float xmax0 = outputLocations[n * 4 + 0] + outputLocations[n * 4 + 2]; |
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float ymax0 = outputLocations[n * 4 + 1] + outputLocations[n * 4 + 3]; |
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float xmin1 = outputLocations[m * 4 + 0]; |
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float ymin1 = outputLocations[m * 4 + 1]; |
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float xmax1 = outputLocations[m * 4 + 0] + outputLocations[m * 4 + 2]; |
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float ymax1 = outputLocations[m * 4 + 1] + outputLocations[m * 4 + 3]; |
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float iou = CalculateOverlap(xmin0, ymin0, xmax0, ymax0, xmin1, ymin1, xmax1, ymax1); |
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if (iou > threshold) |
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{ |
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order[j] = -1; |
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} |
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} |
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} |
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return 0; |
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} |
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static int quick_sort_indice_inverse(std::vector<float> &input, int left, int right, std::vector<int> &indices) |
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{ |
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float key; |
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int key_index; |
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int low = left; |
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int high = right; |
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if (left < right) |
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{ |
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key_index = indices[left]; |
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key = input[left]; |
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while (low < high) |
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{ |
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while (low < high && input[high] <= key) |
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{ |
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high--; |
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} |
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input[low] = input[high]; |
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indices[low] = indices[high]; |
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while (low < high && input[low] >= key) |
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{ |
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low++; |
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} |
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input[high] = input[low]; |
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indices[high] = indices[low]; |
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} |
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input[low] = key; |
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indices[low] = key_index; |
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quick_sort_indice_inverse(input, left, low - 1, indices); |
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quick_sort_indice_inverse(input, low + 1, right, indices); |
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} |
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return low; |
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} |
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static float sigmoid(float x) { return 1.0 / (1.0 + expf(-x)); } |
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static float unsigmoid(float y) { return -1.0 * logf((1.0 / y) - 1.0); } |
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inline static int32_t __clip(float val, float min, float max) |
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{ |
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float f = val <= min ? min : (val >= max ? max : val); |
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return f; |
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} |
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static int8_t qnt_f32_to_affine(float f32, int32_t zp, float scale) |
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{ |
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float dst_val = (f32 / scale) + zp; |
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int8_t res = (int8_t)__clip(dst_val, -128, 127); |
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return res; |
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} |
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static float deqnt_affine_to_f32(int8_t qnt, int32_t zp, float scale) { return ((float)qnt - (float)zp) * scale; } |
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static int process(int8_t *input, int *anchor, int grid_h, int grid_w, int height, int width, int stride, |
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std::vector<float> &boxes, std::vector<float> &objProbs, std::vector<int> &classId, float threshold, |
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int32_t zp, float scale) |
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{ |
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int validCount = 0; |
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int grid_len = grid_h * grid_w; |
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int8_t thres_i8 = qnt_f32_to_affine(threshold, zp, scale); |
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for (int a = 0; a < 3; a++) |
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{ |
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for (int i = 0; i < grid_h; i++) |
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{ |
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for (int j = 0; j < grid_w; j++) |
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{ |
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int8_t box_confidence = input[(PROP_BOX_SIZE * a + 4) * grid_len + i * grid_w + j]; |
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if (box_confidence >= thres_i8) |
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{ |
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int offset = (PROP_BOX_SIZE * a) * grid_len + i * grid_w + j; |
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int8_t *in_ptr = input + offset; |
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float box_x = (deqnt_affine_to_f32(*in_ptr, zp, scale)) * 2.0 - 0.5; |
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float box_y = (deqnt_affine_to_f32(in_ptr[grid_len], zp, scale)) * 2.0 - 0.5; |
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float box_w = (deqnt_affine_to_f32(in_ptr[2 * grid_len], zp, scale)) * 2.0; |
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float box_h = (deqnt_affine_to_f32(in_ptr[3 * grid_len], zp, scale)) * 2.0; |
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box_x = (box_x + j) * (float)stride; |
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box_y = (box_y + i) * (float)stride; |
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box_w = box_w * box_w * (float)anchor[a * 2]; |
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box_h = box_h * box_h * (float)anchor[a * 2 + 1]; |
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box_x -= (box_w / 2.0); |
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box_y -= (box_h / 2.0); |
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int8_t maxClassProbs = in_ptr[5 * grid_len]; |
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int maxClassId = 0; |
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for (int k = 1; k < OBJ_CLASS_NUM; ++k) |
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{ |
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int8_t prob = in_ptr[(5 + k) * grid_len]; |
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if (prob > maxClassProbs) |
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{ |
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maxClassId = k; |
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maxClassProbs = prob; |
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} |
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} |
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if (maxClassProbs > thres_i8) |
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{ |
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objProbs.push_back((deqnt_affine_to_f32(maxClassProbs, zp, scale)) * (deqnt_affine_to_f32(box_confidence, zp, scale))); |
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classId.push_back(maxClassId); |
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validCount++; |
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boxes.push_back(box_x); |
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boxes.push_back(box_y); |
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boxes.push_back(box_w); |
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boxes.push_back(box_h); |
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} |
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} |
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} |
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} |
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} |
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return validCount; |
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} |
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int post_process(int8_t *input0, int8_t *input1, int8_t *input2, int model_in_h, int model_in_w, float conf_threshold, |
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float nms_threshold, BOX_RECT pads, float scale_w, float scale_h, std::vector<int32_t> &qnt_zps, |
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std::vector<float> &qnt_scales, detect_result_group_t *group) |
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{ |
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static int init = -1; |
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if (init == -1) |
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{ |
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int ret = 0; |
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ret = loadLabelName(LABEL_NALE_TXT_PATH, labels); |
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if (ret < 0) |
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{ |
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return -1; |
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} |
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init = 0; |
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} |
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memset(group, 0, sizeof(detect_result_group_t)); |
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std::vector<float> filterBoxes; |
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std::vector<float> objProbs; |
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std::vector<int> classId; |
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int stride0 = 8; |
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int grid_h0 = model_in_h / stride0; |
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int grid_w0 = model_in_w / stride0; |
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int validCount0 = 0; |
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validCount0 = process(input0, (int *)anchor0, grid_h0, grid_w0, model_in_h, model_in_w, stride0, filterBoxes, objProbs, |
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classId, conf_threshold, qnt_zps[0], qnt_scales[0]); |
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int stride1 = 16; |
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int grid_h1 = model_in_h / stride1; |
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int grid_w1 = model_in_w / stride1; |
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int validCount1 = 0; |
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validCount1 = process(input1, (int *)anchor1, grid_h1, grid_w1, model_in_h, model_in_w, stride1, filterBoxes, objProbs, |
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classId, conf_threshold, qnt_zps[1], qnt_scales[1]); |
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int stride2 = 32; |
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int grid_h2 = model_in_h / stride2; |
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int grid_w2 = model_in_w / stride2; |
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int validCount2 = 0; |
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validCount2 = process(input2, (int *)anchor2, grid_h2, grid_w2, model_in_h, model_in_w, stride2, filterBoxes, objProbs, |
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classId, conf_threshold, qnt_zps[2], qnt_scales[2]); |
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int validCount = validCount0 + validCount1 + validCount2; |
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if (validCount <= 0) |
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{ |
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return 0; |
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} |
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std::vector<int> indexArray; |
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for (int i = 0; i < validCount; ++i) |
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{ |
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indexArray.push_back(i); |
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} |
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quick_sort_indice_inverse(objProbs, 0, validCount - 1, indexArray); |
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std::set<int> class_set(std::begin(classId), std::end(classId)); |
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for (auto c : class_set) |
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{ |
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nms(validCount, filterBoxes, classId, indexArray, c, nms_threshold); |
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} |
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int last_count = 0; |
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group->count = 0; |
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for (int i = 0; i < validCount; ++i) |
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{ |
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if (indexArray[i] == -1 || last_count >= OBJ_NUMB_MAX_SIZE) |
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{ |
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continue; |
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} |
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int n = indexArray[i]; |
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float x1 = filterBoxes[n * 4 + 0] - pads.left; |
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float y1 = filterBoxes[n * 4 + 1] - pads.top; |
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float x2 = x1 + filterBoxes[n * 4 + 2]; |
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float y2 = y1 + filterBoxes[n * 4 + 3]; |
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int id = classId[n]; |
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float obj_conf = objProbs[i]; |
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group->results[last_count].box.left = (int)(clamp(x1, 0, model_in_w) / scale_w); |
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group->results[last_count].box.top = (int)(clamp(y1, 0, model_in_h) / scale_h); |
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group->results[last_count].box.right = (int)(clamp(x2, 0, model_in_w) / scale_w); |
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group->results[last_count].box.bottom = (int)(clamp(y2, 0, model_in_h) / scale_h); |
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group->results[last_count].prop = obj_conf; |
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char *label = labels[id]; |
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strncpy(group->results[last_count].name, label, OBJ_NAME_MAX_SIZE); |
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last_count++; |
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} |
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group->count = last_count; |
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return 0; |
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} |
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void deinitPostProcess() |
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{ |
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for (int i = 0; i < OBJ_CLASS_NUM; i++) |
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{ |
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if (labels[i] != nullptr) |
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{ |
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free(labels[i]); |
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labels[i] = nullptr; |
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} |
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} |
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} |
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