// Copyright (c) 2021 by Rockchip Electronics Co., Ltd. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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/*-------------------------------------------
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Includes
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-------------------------------------------*/
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#include "opencv2/core/core.hpp"
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/imgproc.hpp"
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#include "rknn_api.h"
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#include "ssd.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 <sys/time.h>
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#include <fstream>
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#include <iostream>
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using namespace std;
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using namespace cv;
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/*-------------------------------------------
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Functions
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-------------------------------------------*/
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static void dump_tensor_attr(rknn_tensor_attr* attr)
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{
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printf(" index=%d, name=%s, n_dims=%d, dims=[%d, %d, %d, %d], n_elems=%d, size=%d, fmt=%s, type=%s, qnt_type=%s, "
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"zp=%d, scale=%f\n",
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attr->index, attr->name, attr->n_dims, attr->dims[0], attr->dims[1], attr->dims[2], attr->dims[3],
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attr->n_elems, attr->size, get_format_string(attr->fmt), get_type_string(attr->type),
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get_qnt_type_string(attr->qnt_type), attr->zp, attr->scale);
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}
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static unsigned char* load_model(const char* filename, int* model_size)
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{
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FILE* fp = fopen(filename, "rb");
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if (fp == nullptr) {
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printf("fopen %s fail!\n", filename);
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return NULL;
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}
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fseek(fp, 0, SEEK_END);
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int model_len = ftell(fp);
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unsigned char* model = (unsigned char*)malloc(model_len);
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fseek(fp, 0, SEEK_SET);
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if (model_len != fread(model, 1, model_len, fp)) {
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printf("fread %s fail!\n", filename);
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free(model);
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return NULL;
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}
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*model_size = model_len;
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if (fp) {
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fclose(fp);
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}
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return model;
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}
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/*-------------------------------------------
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Main Function
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-------------------------------------------*/
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int main(int argc, char** argv)
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{
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const int img_width = 300;
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const int img_height = 300;
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const int img_channels = 3;
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int ret = 0;
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int model_len = 0;
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unsigned char* model = nullptr;
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rknn_context ctx = 0;
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const char* model_path = argv[1];
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const char* img_path = argv[2];
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if (argc != 3) {
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printf("Usage:%s model image\n", argv[0]);
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return -1;
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}
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// Load image
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cv::Mat orig_img = cv::imread(img_path, 1);
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if (!orig_img.data) {
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printf("cv::imread %s fail!\n", img_path);
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return -1;
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}
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// if origin model is from Caffe, you maybe not need do BGR2RGB.
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cv::Mat orig_img_rgb;
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cv::cvtColor(orig_img, orig_img_rgb, cv::COLOR_BGR2RGB);
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cv::Mat img = orig_img_rgb.clone();
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if (orig_img_rgb.cols != img_width || orig_img_rgb.rows != img_height) {
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printf("resize %d %d to %d %d\n", orig_img_rgb.cols, orig_img_rgb.rows, img_width, img_height);
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cv::resize(orig_img_rgb, img, cv::Size(img_width, img_height), 0, 0, cv::INTER_LINEAR);
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}
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// Load RKNN Model
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printf("Loading model ...\n");
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model = load_model(model_path, &model_len);
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printf("rknn_init ...\n");
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ret = rknn_init(&ctx, model, model_len, 0, NULL);
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if (ret < 0) {
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printf("rknn_init fail! ret=%d\n", ret);
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return -1;
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}
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// Get Model Input Output Info
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rknn_input_output_num io_num;
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ret = rknn_query(ctx, RKNN_QUERY_IN_OUT_NUM, &io_num, sizeof(io_num));
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if (ret != RKNN_SUCC) {
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printf("rknn_query fail! ret=%d\n", ret);
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return -1;
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}
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printf("model input num: %d, output num: %d\n", io_num.n_input, io_num.n_output);
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printf("input tensors:\n");
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rknn_tensor_attr input_attrs[io_num.n_input];
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memset(input_attrs, 0, sizeof(input_attrs));
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for (int i = 0; i < io_num.n_input; i++) {
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input_attrs[i].index = i;
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ret = rknn_query(ctx, RKNN_QUERY_INPUT_ATTR, &(input_attrs[i]), sizeof(rknn_tensor_attr));
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if (ret != RKNN_SUCC) {
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printf("rknn_query fail! ret=%d\n", ret);
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return -1;
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}
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dump_tensor_attr(&(input_attrs[i]));
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}
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printf("output tensors:\n");
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rknn_tensor_attr output_attrs[io_num.n_output];
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memset(output_attrs, 0, sizeof(output_attrs));
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for (int i = 0; i < io_num.n_output; i++) {
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output_attrs[i].index = i;
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ret = rknn_query(ctx, RKNN_QUERY_OUTPUT_ATTR, &(output_attrs[i]), sizeof(rknn_tensor_attr));
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if (ret != RKNN_SUCC) {
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printf("rknn_query fail! ret=%d\n", ret);
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return -1;
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}
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dump_tensor_attr(&(output_attrs[i]));
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}
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// Set Input Data
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rknn_input inputs[1];
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memset(inputs, 0, sizeof(inputs));
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inputs[0].index = 0;
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inputs[0].type = RKNN_TENSOR_UINT8;
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inputs[0].size = img.cols * img.rows * img.channels() * sizeof(uint8_t);
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inputs[0].fmt = RKNN_TENSOR_NHWC;
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inputs[0].buf = img.data;
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ret = rknn_inputs_set(ctx, io_num.n_input, inputs);
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if (ret < 0) {
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printf("rknn_input_set fail! ret=%d\n", ret);
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return -1;
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}
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// Run
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printf("rknn_run\n");
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ret = rknn_run(ctx, nullptr);
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if (ret < 0) {
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printf("rknn_run fail! ret=%d\n", ret);
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return -1;
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}
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// Get Output
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rknn_output outputs[2];
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memset(outputs, 0, sizeof(outputs));
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outputs[0].want_float = 1;
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outputs[1].want_float = 1;
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ret = rknn_outputs_get(ctx, io_num.n_output, outputs, NULL);
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if (ret < 0) {
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printf("rknn_outputs_get fail! ret=%d\n", ret);
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return -1;
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}
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// Post Process
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detect_result_group_t detect_result_group;
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postProcessSSD((float*)(outputs[0].buf), (float*)(outputs[1].buf), orig_img.cols, orig_img.rows,
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&detect_result_group);
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// Release rknn_outputs
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rknn_outputs_release(ctx, 2, outputs);
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// Draw Objects
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for (int i = 0; i < detect_result_group.count; i++) {
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detect_result_t* det_result = &(detect_result_group.results[i]);
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printf("%s @ (%d %d %d %d) %f\n", det_result->name, det_result->box.left, det_result->box.top,
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det_result->box.right, det_result->box.bottom, det_result->prop);
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int x1 = det_result->box.left;
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int y1 = det_result->box.top;
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int x2 = det_result->box.right;
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int y2 = det_result->box.bottom;
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rectangle(orig_img, Point(x1, y1), Point(x2, y2), Scalar(255, 0, 0, 255), 3);
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putText(orig_img, det_result->name, Point(x1, y1 - 12), 1, 2, Scalar(0, 255, 0, 255));
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}
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imwrite("./out.jpg", orig_img);
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deinitPostProcessSSD();
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// Release
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if (ctx > 0)
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{
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rknn_destroy(ctx);
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}
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if (model) {
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free(model);
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}
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return 0;
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}
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