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add yolov5 batch inference sample (#123)
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * AXERA is pleased to support the open source community by making ax-samples available. | ||
| * | ||
| * Copyright (c) 2022, AXERA Semiconductor (Shanghai) Co., Ltd. All rights reserved. | ||
| * | ||
| * Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | ||
| * in compliance with the License. You may obtain a copy of the License at | ||
| * | ||
| * https://opensource.org/licenses/BSD-3-Clause | ||
| * | ||
| * 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. | ||
| */ | ||
|
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| /* | ||
| * Author: ZHEQIUSHUI | ||
| */ | ||
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| #include <cstdio> | ||
| #include <cstring> | ||
| #include <numeric> | ||
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| #include <opencv2/opencv.hpp> | ||
| #include "base/common.hpp" | ||
| #include "base/detection.hpp" | ||
| #include "middleware/io.hpp" | ||
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| #include "utilities/args.hpp" | ||
| #include "utilities/cmdline.hpp" | ||
| #include "utilities/file.hpp" | ||
| #include "utilities/timer.hpp" | ||
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| #include <ax_sys_api.h> | ||
| #include <ax_engine_api.h> | ||
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| const int DEFAULT_IMG_H = 640; | ||
| const int DEFAULT_IMG_W = 640; | ||
| const int CLASS_NUM = 80; | ||
| const char* CLASS_NAMES[] = { | ||
| "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", | ||
| "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", | ||
| "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", | ||
| "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", | ||
| "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", | ||
| "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", | ||
| "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", | ||
| "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", | ||
| "hair drier", "toothbrush"}; | ||
| const float ANCHORS[18] = {10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326}; | ||
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| const int DEFAULT_LOOP_COUNT = 1; | ||
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| const float PROB_THRESHOLD = 0.45f; | ||
| const float NMS_THRESHOLD = 0.45f; | ||
| struct image_data_t | ||
| { | ||
| std::string path; | ||
| cv::Mat mat; | ||
| std::vector<uint8_t> data; | ||
| }; | ||
| namespace ax | ||
| { | ||
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| void post_process(AX_ENGINE_IO_INFO_T* io_info, AX_ENGINE_IO_T* io_data, const std::vector<image_data_t>& batchdata, int input_w, int input_h, const std::vector<float>& time_costs) | ||
| { | ||
| float prob_threshold_u_sigmoid = -1.0f * (float)std::log((1.0f / PROB_THRESHOLD) - 1.0f); | ||
| for (size_t b = 0; b < batchdata.size(); b++) | ||
| { | ||
| std::vector<detection::Object> proposals; | ||
| std::vector<detection::Object> objects; | ||
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| timer timer_postprocess; | ||
| for (uint32_t i = 0; i < io_info->nOutputSize; ++i) | ||
| { | ||
| auto& output = io_data->pOutputs[i]; | ||
| float* ptr = (float*)output.pVirAddr; | ||
| int32_t stride = (1 << i) * 8; | ||
| ptr += b * (input_w / stride) * (input_h / stride) * 3 * (CLASS_NUM + 5); | ||
| detection::generate_proposals_yolov5(stride, ptr, PROB_THRESHOLD, proposals, input_w, input_h, ANCHORS, prob_threshold_u_sigmoid, CLASS_NUM); | ||
| } | ||
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| detection::get_out_bbox(proposals, objects, NMS_THRESHOLD, input_h, input_w, batchdata[b].mat.rows, batchdata[b].mat.cols); | ||
| fprintf(stdout, "post process cost time:%.2f ms \n", timer_postprocess.cost()); | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
| fprintf(stdout, "detection num: %zu\n", objects.size()); | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
| detection::draw_objects(batchdata[b].mat, objects, CLASS_NAMES, (batchdata[b].path + ".res").c_str()); | ||
| } | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
| auto total_time = std::accumulate(time_costs.begin(), time_costs.end(), 0.f); | ||
| auto min_max_time = std::minmax_element(time_costs.begin(), time_costs.end()); | ||
| fprintf(stdout, | ||
| "Repeat %d times, avg time %.2f ms, max_time %.2f ms, min_time %.2f ms\n", | ||
| (int)time_costs.size(), | ||
| total_time / (float)time_costs.size(), | ||
| *min_max_time.second, | ||
| *min_max_time.first); | ||
| } | ||
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| bool run_model(const std::string& model, const std::vector<image_data_t>& batchdata, const int& repeat, int input_h, int input_w) | ||
| { | ||
| // 1. init engine | ||
| #ifdef AXERA_TARGET_CHIP_AX620E | ||
| auto ret = AX_ENGINE_Init(); | ||
| #else | ||
| AX_ENGINE_NPU_ATTR_T npu_attr; | ||
| memset(&npu_attr, 0, sizeof(npu_attr)); | ||
| npu_attr.eHardMode = AX_ENGINE_VIRTUAL_NPU_DISABLE; | ||
| auto ret = AX_ENGINE_Init(&npu_attr); | ||
| #endif | ||
| if (0 != ret) | ||
| { | ||
| return ret; | ||
| } | ||
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| // 2. load model | ||
| std::vector<char> model_buffer; | ||
| if (!utilities::read_file(model, model_buffer)) | ||
| { | ||
| fprintf(stderr, "Read Run-Joint model(%s) file failed.\n", model.c_str()); | ||
| return false; | ||
| } | ||
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| // 3. create handle | ||
| AX_ENGINE_HANDLE handle; | ||
| ret = AX_ENGINE_CreateHandle(&handle, model_buffer.data(), model_buffer.size()); | ||
| SAMPLE_AX_ENGINE_DEAL_HANDLE | ||
| fprintf(stdout, "Engine creating handle is done.\n"); | ||
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| // 4. create context | ||
| ret = AX_ENGINE_CreateContext(handle); | ||
| SAMPLE_AX_ENGINE_DEAL_HANDLE | ||
| fprintf(stdout, "Engine creating context is done.\n"); | ||
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| // 5. set io | ||
| AX_ENGINE_IO_INFO_T* io_info; | ||
| ret = AX_ENGINE_GetIOInfo(handle, &io_info); | ||
| SAMPLE_AX_ENGINE_DEAL_HANDLE | ||
| fprintf(stdout, "Engine get io info is done. \n"); | ||
| if (batchdata.size() > io_info->nMaxBatchSize) | ||
| { | ||
| fprintf(stderr, "The batch size is too large. %d > %d\n", batchdata.size(), io_info->nMaxBatchSize); | ||
| return AX_ENGINE_DestroyHandle(handle); | ||
| } | ||
| middleware::print_io_info(io_info); | ||
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| // 6. alloc io | ||
| AX_ENGINE_IO_T io_data; | ||
| ret = middleware::prepare_io(io_info, &io_data, std::make_pair(AX_ENGINE_ABST_DEFAULT, AX_ENGINE_ABST_CACHED)); | ||
| SAMPLE_AX_ENGINE_DEAL_HANDLE | ||
| fprintf(stdout, "Engine alloc io is done. \n"); | ||
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| // 7. insert input | ||
| io_data.nBatchSize = batchdata.size(); | ||
| int single_input_size = io_info->pInputs[0].nSize / io_info->nMaxBatchSize; | ||
| printf("single input size %d \n", single_input_size); | ||
| uint8_t* input_data = (uint8_t*)io_data.pInputs[0].pVirAddr; | ||
| for (int i = 0; i < batchdata.size(); ++i) | ||
| { | ||
| memcpy(input_data + i * single_input_size, batchdata[i].data.data(), single_input_size); | ||
| } | ||
| // memcpy(io_data.pInputs[0].pVirAddr, data.data(), data.size()); | ||
| fprintf(stdout, "Engine push input is done. \n"); | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
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| // 8. warn up | ||
| for (int i = 0; i < 5; ++i) | ||
| { | ||
| AX_ENGINE_RunSync(handle, &io_data); | ||
| } | ||
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| // 9. run model | ||
| std::vector<float> time_costs(repeat, 0); | ||
| for (int i = 0; i < repeat; ++i) | ||
| { | ||
| timer tick; | ||
| ret = AX_ENGINE_RunSync(handle, &io_data); | ||
| time_costs[i] = tick.cost(); | ||
| SAMPLE_AX_ENGINE_DEAL_HANDLE_IO | ||
| } | ||
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| // 10. get result | ||
| post_process(io_info, &io_data, batchdata, input_w, input_h, time_costs); | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
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| middleware::free_io(&io_data); | ||
| return AX_ENGINE_DestroyHandle(handle); | ||
| } | ||
| } // namespace ax | ||
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| int main(int argc, char* argv[]) | ||
| { | ||
| cmdline::parser cmd; | ||
| cmd.add<std::string>("model", 'm', "joint file(a.k.a. joint model)", true, ""); | ||
| cmd.add<std::string>("folder", 'f', "image folder", true, ""); | ||
| cmd.add<std::string>("size", 'g', "input_h, input_w", false, std::to_string(DEFAULT_IMG_H) + "," + std::to_string(DEFAULT_IMG_W)); | ||
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| cmd.add<int>("repeat", 'r', "repeat count", false, DEFAULT_LOOP_COUNT); | ||
| cmd.parse_check(argc, argv); | ||
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| // 0. get app args, can be removed from user's app | ||
| auto model_file = cmd.get<std::string>("model"); | ||
| auto image_folder = cmd.get<std::string>("folder"); | ||
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| auto model_file_flag = utilities::file_exist(model_file); | ||
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| if (!model_file_flag) | ||
| { | ||
| auto show_error = [](const std::string& kind, const std::string& value) { | ||
| fprintf(stderr, "Input file %s(%s) is not exist, please check it.\n", kind.c_str(), value.c_str()); | ||
| }; | ||
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| if (!model_file_flag) { show_error("model", model_file); } | ||
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| return -1; | ||
| } | ||
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| auto input_size_string = cmd.get<std::string>("size"); | ||
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| std::array<int, 2> input_size = {DEFAULT_IMG_H, DEFAULT_IMG_W}; | ||
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| auto input_size_flag = utilities::parse_string(input_size_string, input_size); | ||
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| if (!input_size_flag) | ||
| { | ||
| auto show_error = [](const std::string& kind, const std::string& value) { | ||
| fprintf(stderr, "Input %s(%s) is not allowed, please check it.\n", kind.c_str(), value.c_str()); | ||
| }; | ||
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| show_error("size", input_size_string); | ||
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| return -1; | ||
| } | ||
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| auto repeat = cmd.get<int>("repeat"); | ||
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| // 1. print args | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
| fprintf(stdout, "model file : %s\n", model_file.c_str()); | ||
| fprintf(stdout, "image folder : %s\n", image_folder.c_str()); | ||
| fprintf(stdout, "img_h, img_w : %d %d\n", input_size[0], input_size[1]); | ||
| fprintf(stdout, "--------------------------------------\n"); | ||
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| // 2. read image & resize & transpose | ||
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| if (image_folder.back() != '/') | ||
| { | ||
| image_folder += "/"; | ||
| } | ||
| std::vector<std::string> image_list; | ||
| cv::glob(image_folder + "*.jpg", image_list); | ||
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| std::vector<std::string> image_list_png; | ||
| cv::glob(image_folder + "*.png", image_list_png); | ||
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| std::vector<std::string> image_list_jpeg; | ||
| cv::glob(image_folder + "*.jpeg", image_list_jpeg); | ||
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| image_list.insert(image_list.end(), image_list_png.begin(), image_list_png.end()); | ||
| image_list.insert(image_list.end(), image_list_jpeg.begin(), image_list_jpeg.end()); | ||
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| std::vector<image_data_t> batchdata(image_list.size()); | ||
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| for (int i = 0; i < image_list.size(); ++i) | ||
| { | ||
| printf("read image : %s\n", image_list[i].c_str()); | ||
| batchdata[i].path = image_list[i]; | ||
| batchdata[i].mat = cv::imread(image_list[i]); | ||
| if (batchdata[i].mat.empty()) | ||
| { | ||
| fprintf(stderr, "Read image failed.\n"); | ||
| return -1; | ||
| } | ||
| batchdata[i].data.resize(input_size[0] * input_size[1] * 3, 0); | ||
| common::get_input_data_letterbox(batchdata[i].mat, batchdata[i].data, input_size[0], input_size[1]); | ||
| } | ||
| // cv::Mat mat = cv::imread(image_file); | ||
| // if (mat.empty()) | ||
| // { | ||
| // fprintf(stderr, "Read image failed.\n"); | ||
| // return -1; | ||
| // } | ||
| // common::get_input_data_letterbox(mat, image, input_size[0], input_size[1]); | ||
|
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| // 3. sys_init | ||
| AX_SYS_Init(); | ||
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| // 4. - engine model - can only use AX_ENGINE** inside | ||
| { | ||
| // AX_ENGINE_NPUReset(); // todo ?? | ||
| ax::run_model(model_file, batchdata, repeat, input_size[0], input_size[1]); | ||
|
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| // 4.3 engine de init | ||
| AX_ENGINE_Deinit(); | ||
| // AX_ENGINE_NPUReset(); | ||
| } | ||
| // 4. - engine model - | ||
|
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| AX_SYS_Deinit(); | ||
| return 0; | ||
| } |
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