| /* |
| * Copyright 2022 Google LLC |
| * |
| * Licensed under the Apache License, Version 2.0 (the "License"); |
| * you may not use this file except in compliance with the License. |
| * You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| |
| // SSD box decoding and extracting |
| |
| #include "ssd_postprocess/box.h" |
| |
| #include <math.h> |
| #include <stdio.h> |
| #include <stdlib.h> |
| #include <string.h> |
| |
| static SsdParams params = { |
| .num_layers = 4, |
| .num_boxes = 1602, |
| .input_height = 320, |
| .input_width = 320, |
| .global_scales = {10, 10, 5, 5}, // y, x, h, w |
| .box_zero_points = {115, 129, 125, 119}, |
| .box_scales = {0.0813235, 0.0786732, 0.0687513, 0.0522251}, |
| .score_zero_points = {211, 195, 200, 225}, |
| .score_scales = {0.177373, 0.121247, 0.100491, 0.0550178}, |
| .score_threshold = 0.5, |
| .anchors_per_cell = 3, |
| .anchor_base_size = {24.0, 32.0, 40.0, 48.0, 64.0, 80.0, 96.0, 128.0, 160.0, |
| 192.0, 256.0, 320.0}, |
| .anchor_stride = {16, 32, 64, 128}}; |
| |
| // Set SSD parameters |
| void set_params(SsdParams* params_in) { params = *params_in; } |
| |
| static inline float dequantize(int val, int zero_point, float scale) { |
| return scale * (val - zero_point); |
| } |
| |
| static inline float sigmoid(float val) { return 1.0 / (1.0 + expf(-val)); } |
| |
| // Generate model anchors |
| // layer0: 20 * 20 * 3 = 1200 |
| // layer1: 10 * 10 * 3 = 300 |
| // layer2: 5 * 5 * 3 = 75 |
| // layer3: 3 * 3 * 3 = 27 |
| // total sum: 1602 |
| static void generate_anchors(BoxCenterEncode* anchors) { |
| int idx = 0; |
| for (int layer = 0; layer < params.num_layers; ++layer) { |
| int height_size = (params.input_height + params.anchor_stride[layer] - 1) / |
| params.anchor_stride[layer]; |
| int width_size = (params.input_width + params.anchor_stride[layer] - 1) / |
| params.anchor_stride[layer]; |
| for (int h = 0; h < height_size; h++) { |
| for (int w = 0; w < width_size; w++) { |
| for (int base = 0; base < params.anchors_per_cell; ++base) { |
| anchors[idx].y = |
| (float)params.anchor_stride[layer] * h / params.input_height; |
| anchors[idx].x = |
| (float)params.anchor_stride[layer] * w / params.input_width; |
| anchors[idx].h = |
| params.anchor_base_size[layer * params.anchors_per_cell + base] / |
| params.input_height; |
| anchors[idx].w = |
| params.anchor_base_size[layer * params.anchors_per_cell + base] / |
| params.input_width; |
| idx++; |
| } |
| } |
| } |
| } |
| } |
| |
| // Decode boxes (with score) from model inference outputs |
| // The locations channel dim is 16 x 3. |
| // Each 16 is composed of (4 box coordinates + 6 * 2 landmarks coordinates). |
| // We need only the first 4 box coordinates - so want to keep only indexes: |
| // 0, 1, 2, 3 |
| // 16,17,18,19 |
| // 32,33,34,35 |
| static void decode_boxes(uint8_t** model_out, BoxCenterEncode* boxes) { |
| const int num_coordinates = 16; |
| int box_idx = 0; |
| for (int layer = 0; layer < params.num_layers; layer++) { |
| int height_size = (params.input_height + params.anchor_stride[layer] - 1) / |
| params.anchor_stride[layer]; |
| int width_size = (params.input_width + params.anchor_stride[layer] - 1) / |
| params.anchor_stride[layer]; |
| // Boxes at even indicees; scores at odd indices |
| uint8_t* boxes_out = model_out[2 * layer]; |
| uint8_t* scores_out = model_out[2 * layer + 1]; |
| for (int i = 0; i < height_size * width_size; i++) { |
| for (int j = 0; j < params.anchors_per_cell; j++) { |
| int score_idx = i * params.anchors_per_cell + j; |
| int chan_idx = num_coordinates * score_idx; |
| // dequantize box |
| boxes[box_idx].y = |
| dequantize(boxes_out[chan_idx], params.box_zero_points[layer], |
| params.box_scales[layer]); |
| boxes[box_idx].x = |
| dequantize(boxes_out[chan_idx + 1], params.box_zero_points[layer], |
| params.box_scales[layer]); |
| boxes[box_idx].h = |
| dequantize(boxes_out[chan_idx + 2], params.box_zero_points[layer], |
| params.box_scales[layer]); |
| boxes[box_idx].w = |
| dequantize(boxes_out[chan_idx + 3], params.box_zero_points[layer], |
| params.box_scales[layer]); |
| // dequantize score |
| float dequant_score = |
| dequantize(scores_out[score_idx], params.score_zero_points[layer], |
| params.score_scales[layer]); |
| boxes[box_idx].score = sigmoid(dequant_score); |
| box_idx++; |
| } |
| } |
| } |
| } |
| |
| // Convert box from center encoding to corner encoding format |
| static void convert_box(const BoxCenterEncode* box_in, BoxCenterEncode* anchor, |
| BoxCornerEncode* box_out) { |
| float y_center = box_in->y / params.global_scales[0] * anchor->h + anchor->y; |
| float x_center = box_in->x / params.global_scales[1] * anchor->w + anchor->x; |
| float half_h = 0.5 * expf(box_in->h / params.global_scales[2]) * anchor->h; |
| float half_w = 0.5 * expf(box_in->w / params.global_scales[3]) * anchor->w; |
| |
| box_out->ymin = y_center - half_h; |
| box_out->xmin = x_center - half_w; |
| box_out->ymax = y_center + half_h; |
| box_out->xmax = x_center + half_w; |
| box_out->score = box_in->score; |
| } |
| |
| // Detect boxes by score thresholding |
| static void detect_boxes(const BoxCenterEncode* boxes_in, |
| BoxCenterEncode* anchors, Boxes* boxes_out) { |
| int num_detected_boxes = 0; |
| for (int i = 0; i < params.num_boxes; ++i) { |
| if (boxes_in[i].score > params.score_threshold) { |
| num_detected_boxes++; |
| } |
| } |
| if (!(boxes_out->box)) { |
| boxes_out->box = |
| (BoxCornerEncode*)malloc(sizeof(BoxCornerEncode) * num_detected_boxes); |
| } |
| |
| num_detected_boxes = 0; |
| for (int i = 0; i < params.num_boxes; ++i) { |
| if (boxes_in[i].score > params.score_threshold) { |
| convert_box(&(boxes_in[i]), &(anchors[i]), |
| &(boxes_out->box[num_detected_boxes])); |
| num_detected_boxes++; |
| } |
| } |
| boxes_out->num_boxes = num_detected_boxes; |
| } |
| |
| // Decode and extract detected boxes |
| void get_detected_boxes(uint8_t** model_out, Boxes* boxes_out) { |
| BoxCenterEncode* boxes_in = |
| (BoxCenterEncode*)malloc(sizeof(BoxCenterEncode) * params.num_boxes); |
| BoxCenterEncode* anchors = |
| (BoxCenterEncode*)malloc(sizeof(BoxCenterEncode) * params.num_boxes); |
| |
| generate_anchors(anchors); |
| |
| decode_boxes(model_out, boxes_in); |
| |
| detect_boxes(boxes_in, anchors, boxes_out); |
| |
| free(anchors); |
| free(boxes_in); |
| } |