mirror of
https://github.com/NVIDIA/cuda-samples.git
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614 lines
22 KiB
C++
614 lines
22 KiB
C++
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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// This sample needs at least CUDA 10.0. It demonstrates usages of the nvJPEG
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// library nvJPEG supports single and multiple image(batched) decode. Multiple
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// images can be decoded using the API for batch mode
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#include <cuda_runtime_api.h>
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#include "helper_nvJPEG.hxx"
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int dev_malloc(void **p, size_t s) { return (int)cudaMalloc(p, s); }
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int dev_free(void *p) { return (int)cudaFree(p); }
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int host_malloc(void** p, size_t s, unsigned int f) { return (int)cudaHostAlloc(p, s, f); }
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int host_free(void* p) { return (int)cudaFreeHost(p); }
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typedef std::vector<std::string> FileNames;
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typedef std::vector<std::vector<char> > FileData;
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struct decode_params_t {
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std::string input_dir;
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int batch_size;
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int total_images;
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int dev;
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int warmup;
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nvjpegJpegState_t nvjpeg_state;
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nvjpegHandle_t nvjpeg_handle;
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cudaStream_t stream;
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// used with decoupled API
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nvjpegJpegState_t nvjpeg_decoupled_state;
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nvjpegBufferPinned_t pinned_buffers[2]; // 2 buffers for pipelining
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nvjpegBufferDevice_t device_buffer;
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nvjpegJpegStream_t jpeg_streams[2]; // 2 streams for pipelining
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nvjpegDecodeParams_t nvjpeg_decode_params;
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nvjpegJpegDecoder_t nvjpeg_decoder;
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nvjpegOutputFormat_t fmt;
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bool write_decoded;
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std::string output_dir;
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bool pipelined;
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bool batched;
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};
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int read_next_batch(FileNames &image_names, int batch_size,
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FileNames::iterator &cur_iter, FileData &raw_data,
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std::vector<size_t> &raw_len, FileNames ¤t_names) {
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int counter = 0;
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while (counter < batch_size) {
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if (cur_iter == image_names.end()) {
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std::cerr << "Image list is too short to fill the batch, adding files "
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"from the beginning of the image list"
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<< std::endl;
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cur_iter = image_names.begin();
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}
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if (image_names.size() == 0) {
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std::cerr << "No valid images left in the input list, exit" << std::endl;
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return EXIT_FAILURE;
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}
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// Read an image from disk.
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std::ifstream input(cur_iter->c_str(),
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std::ios::in | std::ios::binary | std::ios::ate);
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if (!(input.is_open())) {
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std::cerr << "Cannot open image: " << *cur_iter
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<< ", removing it from image list" << std::endl;
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image_names.erase(cur_iter);
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continue;
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}
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// Get the size
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std::streamsize file_size = input.tellg();
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input.seekg(0, std::ios::beg);
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// resize if buffer is too small
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if (raw_data[counter].size() < file_size) {
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raw_data[counter].resize(file_size);
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}
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if (!input.read(raw_data[counter].data(), file_size)) {
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std::cerr << "Cannot read from file: " << *cur_iter
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<< ", removing it from image list" << std::endl;
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image_names.erase(cur_iter);
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continue;
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}
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raw_len[counter] = file_size;
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current_names[counter] = *cur_iter;
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counter++;
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cur_iter++;
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}
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return EXIT_SUCCESS;
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}
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// prepare buffers for RGBi output format
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int prepare_buffers(FileData &file_data, std::vector<size_t> &file_len,
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std::vector<int> &img_width, std::vector<int> &img_height,
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std::vector<nvjpegImage_t> &ibuf,
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std::vector<nvjpegImage_t> &isz, FileNames ¤t_names,
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decode_params_t ¶ms) {
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int widths[NVJPEG_MAX_COMPONENT];
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int heights[NVJPEG_MAX_COMPONENT];
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int channels;
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nvjpegChromaSubsampling_t subsampling;
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for (int i = 0; i < file_data.size(); i++) {
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checkCudaErrors(nvjpegGetImageInfo(
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params.nvjpeg_handle, (unsigned char *)file_data[i].data(), file_len[i],
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&channels, &subsampling, widths, heights));
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img_width[i] = widths[0];
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img_height[i] = heights[0];
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std::cout << "Processing: " << current_names[i] << std::endl;
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std::cout << "Image is " << channels << " channels." << std::endl;
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for (int c = 0; c < channels; c++) {
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std::cout << "Channel #" << c << " size: " << widths[c] << " x "
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<< heights[c] << std::endl;
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}
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switch (subsampling) {
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case NVJPEG_CSS_444:
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std::cout << "YUV 4:4:4 chroma subsampling" << std::endl;
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break;
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case NVJPEG_CSS_440:
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std::cout << "YUV 4:4:0 chroma subsampling" << std::endl;
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break;
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case NVJPEG_CSS_422:
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std::cout << "YUV 4:2:2 chroma subsampling" << std::endl;
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break;
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case NVJPEG_CSS_420:
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std::cout << "YUV 4:2:0 chroma subsampling" << std::endl;
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break;
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case NVJPEG_CSS_411:
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std::cout << "YUV 4:1:1 chroma subsampling" << std::endl;
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break;
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case NVJPEG_CSS_410:
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std::cout << "YUV 4:1:0 chroma subsampling" << std::endl;
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break;
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case NVJPEG_CSS_GRAY:
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std::cout << "Grayscale JPEG " << std::endl;
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break;
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case NVJPEG_CSS_UNKNOWN:
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std::cout << "Unknown chroma subsampling" << std::endl;
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return EXIT_FAILURE;
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}
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int mul = 1;
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// in the case of interleaved RGB output, write only to single channel, but
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// 3 samples at once
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if (params.fmt == NVJPEG_OUTPUT_RGBI || params.fmt == NVJPEG_OUTPUT_BGRI) {
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channels = 1;
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mul = 3;
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}
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// in the case of rgb create 3 buffers with sizes of original image
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else if (params.fmt == NVJPEG_OUTPUT_RGB ||
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params.fmt == NVJPEG_OUTPUT_BGR) {
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channels = 3;
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widths[1] = widths[2] = widths[0];
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heights[1] = heights[2] = heights[0];
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}
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// realloc output buffer if required
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for (int c = 0; c < channels; c++) {
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int aw = mul * widths[c];
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int ah = heights[c];
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int sz = aw * ah;
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ibuf[i].pitch[c] = aw;
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if (sz > isz[i].pitch[c]) {
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if (ibuf[i].channel[c]) {
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checkCudaErrors(cudaFree(ibuf[i].channel[c]));
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}
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checkCudaErrors(cudaMalloc(&ibuf[i].channel[c], sz));
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isz[i].pitch[c] = sz;
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}
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}
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}
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return EXIT_SUCCESS;
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}
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void create_decoupled_api_handles(decode_params_t& params){
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checkCudaErrors(nvjpegDecoderCreate(params.nvjpeg_handle, NVJPEG_BACKEND_DEFAULT, ¶ms.nvjpeg_decoder));
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checkCudaErrors(nvjpegDecoderStateCreate(params.nvjpeg_handle, params.nvjpeg_decoder, ¶ms.nvjpeg_decoupled_state));
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checkCudaErrors(nvjpegBufferPinnedCreate(params.nvjpeg_handle, NULL, ¶ms.pinned_buffers[0]));
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checkCudaErrors(nvjpegBufferPinnedCreate(params.nvjpeg_handle, NULL, ¶ms.pinned_buffers[1]));
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checkCudaErrors(nvjpegBufferDeviceCreate(params.nvjpeg_handle, NULL, ¶ms.device_buffer));
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checkCudaErrors(nvjpegJpegStreamCreate(params.nvjpeg_handle, ¶ms.jpeg_streams[0]));
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checkCudaErrors(nvjpegJpegStreamCreate(params.nvjpeg_handle, ¶ms.jpeg_streams[1]));
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checkCudaErrors(nvjpegDecodeParamsCreate(params.nvjpeg_handle, ¶ms.nvjpeg_decode_params));
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}
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void destroy_decoupled_api_handles(decode_params_t& params){
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checkCudaErrors(nvjpegDecodeParamsDestroy(params.nvjpeg_decode_params));
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checkCudaErrors(nvjpegJpegStreamDestroy(params.jpeg_streams[0]));
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checkCudaErrors(nvjpegJpegStreamDestroy(params.jpeg_streams[1]));
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checkCudaErrors(nvjpegBufferPinnedDestroy(params.pinned_buffers[0]));
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checkCudaErrors(nvjpegBufferPinnedDestroy(params.pinned_buffers[1]));
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checkCudaErrors(nvjpegBufferDeviceDestroy(params.device_buffer));
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checkCudaErrors(nvjpegJpegStateDestroy(params.nvjpeg_decoupled_state));
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checkCudaErrors(nvjpegDecoderDestroy(params.nvjpeg_decoder));
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}
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void release_buffers(std::vector<nvjpegImage_t> &ibuf) {
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for (int i = 0; i < ibuf.size(); i++) {
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for (int c = 0; c < NVJPEG_MAX_COMPONENT; c++)
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if (ibuf[i].channel[c]) checkCudaErrors(cudaFree(ibuf[i].channel[c]));
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}
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}
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int decode_images(const FileData &img_data, const std::vector<size_t> &img_len,
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std::vector<nvjpegImage_t> &out, decode_params_t ¶ms,
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double &time) {
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checkCudaErrors(cudaStreamSynchronize(params.stream));
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cudaEvent_t startEvent = NULL, stopEvent = NULL;
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float loopTime = 0;
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checkCudaErrors(cudaEventCreate(&startEvent, cudaEventBlockingSync));
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checkCudaErrors(cudaEventCreate(&stopEvent, cudaEventBlockingSync));
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if (!params.batched) {
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if (!params.pipelined) // decode one image at a time
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{
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checkCudaErrors(cudaEventRecord(startEvent, params.stream));
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for (int i = 0; i < params.batch_size; i++) {
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checkCudaErrors(nvjpegDecode(params.nvjpeg_handle, params.nvjpeg_state,
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(const unsigned char *)img_data[i].data(),
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img_len[i], params.fmt, &out[i],
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params.stream));
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}
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checkCudaErrors(cudaEventRecord(stopEvent, params.stream));
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} else {
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// use de-coupled API in pipelined mode
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checkCudaErrors(cudaEventRecord(startEvent, params.stream));
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checkCudaErrors(nvjpegStateAttachDeviceBuffer(params.nvjpeg_decoupled_state, params.device_buffer));
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int buffer_index = 0;
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checkCudaErrors(nvjpegDecodeParamsSetOutputFormat(params.nvjpeg_decode_params, params.fmt));
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for (int i = 0; i < params.batch_size; i++) {
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checkCudaErrors(
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nvjpegJpegStreamParse(params.nvjpeg_handle, (const unsigned char *)img_data[i].data(), img_len[i],
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0, 0, params.jpeg_streams[buffer_index]));
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checkCudaErrors(nvjpegStateAttachPinnedBuffer(params.nvjpeg_decoupled_state,
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params.pinned_buffers[buffer_index]));
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checkCudaErrors(nvjpegDecodeJpegHost(params.nvjpeg_handle, params.nvjpeg_decoder, params.nvjpeg_decoupled_state,
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params.nvjpeg_decode_params, params.jpeg_streams[buffer_index]));
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checkCudaErrors(cudaStreamSynchronize(params.stream));
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checkCudaErrors(nvjpegDecodeJpegTransferToDevice(params.nvjpeg_handle, params.nvjpeg_decoder, params.nvjpeg_decoupled_state,
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params.jpeg_streams[buffer_index], params.stream));
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buffer_index = 1 - buffer_index; // switch pinned buffer in pipeline mode to avoid an extra sync
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checkCudaErrors(nvjpegDecodeJpegDevice(params.nvjpeg_handle, params.nvjpeg_decoder, params.nvjpeg_decoupled_state,
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&out[i], params.stream));
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}
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checkCudaErrors(cudaEventRecord(stopEvent, params.stream));
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}
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} else {
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std::vector<const unsigned char *> raw_inputs;
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for (int i = 0; i < params.batch_size; i++) {
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raw_inputs.push_back((const unsigned char *)img_data[i].data());
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}
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checkCudaErrors(cudaEventRecord(startEvent, params.stream));
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checkCudaErrors(nvjpegDecodeBatched(
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params.nvjpeg_handle, params.nvjpeg_state, raw_inputs.data(),
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img_len.data(), out.data(), params.stream));
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checkCudaErrors(cudaEventRecord(stopEvent, params.stream));
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}
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checkCudaErrors(cudaEventSynchronize(stopEvent));
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checkCudaErrors(cudaEventElapsedTime(&loopTime, startEvent, stopEvent));
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time = static_cast<double>(loopTime);
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return EXIT_SUCCESS;
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}
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int write_images(std::vector<nvjpegImage_t> &iout, std::vector<int> &widths,
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std::vector<int> &heights, decode_params_t ¶ms,
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FileNames &filenames) {
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for (int i = 0; i < params.batch_size; i++) {
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// Get the file name, without extension.
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// This will be used to rename the output file.
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size_t position = filenames[i].rfind("/");
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std::string sFileName =
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(std::string::npos == position)
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? filenames[i]
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: filenames[i].substr(position + 1, filenames[i].size());
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position = sFileName.rfind(".");
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sFileName = (std::string::npos == position) ? sFileName
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: sFileName.substr(0, position);
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std::string fname(params.output_dir + "/" + sFileName + ".bmp");
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int err;
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if (params.fmt == NVJPEG_OUTPUT_RGB || params.fmt == NVJPEG_OUTPUT_BGR) {
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err = writeBMP(fname.c_str(), iout[i].channel[0], iout[i].pitch[0],
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iout[i].channel[1], iout[i].pitch[1], iout[i].channel[2],
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iout[i].pitch[2], widths[i], heights[i]);
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} else if (params.fmt == NVJPEG_OUTPUT_RGBI ||
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params.fmt == NVJPEG_OUTPUT_BGRI) {
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// Write BMP from interleaved data
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err = writeBMPi(fname.c_str(), iout[i].channel[0], iout[i].pitch[0],
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widths[i], heights[i]);
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}
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if (err) {
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std::cout << "Cannot write output file: " << fname << std::endl;
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return EXIT_FAILURE;
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}
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std::cout << "Done writing decoded image to file: " << fname << std::endl;
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}
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}
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double process_images(FileNames &image_names, decode_params_t ¶ms,
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double &total) {
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// vector for storing raw files and file lengths
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FileData file_data(params.batch_size);
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std::vector<size_t> file_len(params.batch_size);
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FileNames current_names(params.batch_size);
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std::vector<int> widths(params.batch_size);
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std::vector<int> heights(params.batch_size);
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// we wrap over image files to process total_images of files
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FileNames::iterator file_iter = image_names.begin();
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// stream for decoding
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checkCudaErrors(
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cudaStreamCreateWithFlags(¶ms.stream, cudaStreamNonBlocking));
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int total_processed = 0;
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// output buffers
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std::vector<nvjpegImage_t> iout(params.batch_size);
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// output buffer sizes, for convenience
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std::vector<nvjpegImage_t> isz(params.batch_size);
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for (int i = 0; i < iout.size(); i++) {
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for (int c = 0; c < NVJPEG_MAX_COMPONENT; c++) {
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iout[i].channel[c] = NULL;
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iout[i].pitch[c] = 0;
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isz[i].pitch[c] = 0;
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}
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}
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double test_time = 0;
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int warmup = 0;
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while (total_processed < params.total_images) {
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if (read_next_batch(image_names, params.batch_size, file_iter, file_data,
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file_len, current_names))
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return EXIT_FAILURE;
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if (prepare_buffers(file_data, file_len, widths, heights, iout, isz,
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current_names, params))
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return EXIT_FAILURE;
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double time;
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if (decode_images(file_data, file_len, iout, params, time))
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return EXIT_FAILURE;
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if (warmup < params.warmup) {
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warmup++;
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} else {
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total_processed += params.batch_size;
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test_time += time;
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}
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if (params.write_decoded)
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write_images(iout, widths, heights, params, current_names);
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}
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total = test_time;
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release_buffers(iout);
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checkCudaErrors(cudaStreamDestroy(params.stream));
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return EXIT_SUCCESS;
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}
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// parse parameters
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int findParamIndex(const char **argv, int argc, const char *parm) {
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int count = 0;
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int index = -1;
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for (int i = 0; i < argc; i++) {
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if (strncmp(argv[i], parm, 100) == 0) {
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index = i;
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count++;
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}
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}
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if (count == 0 || count == 1) {
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return index;
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} else {
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std::cout << "Error, parameter " << parm
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<< " has been specified more than once, exiting\n"
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<< std::endl;
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return -1;
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}
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return -1;
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}
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int main(int argc, const char *argv[]) {
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int pidx;
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if ((pidx = findParamIndex(argv, argc, "-h")) != -1 ||
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(pidx = findParamIndex(argv, argc, "--help")) != -1) {
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std::cout << "Usage: " << argv[0]
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<< " -i images_dir [-b batch_size] [-t total_images] [-device= "
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"device_id] [-w warmup_iterations] [-o output_dir] "
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"[-pipelined] [-batched] [-fmt output_format]\n";
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std::cout << "Parameters: " << std::endl;
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std::cout << "\timages_dir\t:\tPath to single image or directory of images"
|
|
<< std::endl;
|
|
std::cout << "\tbatch_size\t:\tDecode images from input by batches of "
|
|
"specified size"
|
|
<< std::endl;
|
|
std::cout << "\ttotal_images\t:\tDecode this much images, if there are "
|
|
"less images \n"
|
|
<< "\t\t\t\t\tin the input than total images, decoder will loop "
|
|
"over the input"
|
|
<< std::endl;
|
|
std::cout << "\tdevice_id\t:\tWhich device to use for decoding"
|
|
<< std::endl;
|
|
std::cout << "\twarmup_iterations\t:\tRun this amount of batches first "
|
|
"without measuring performance"
|
|
<< std::endl;
|
|
std::cout
|
|
<< "\toutput_dir\t:\tWrite decoded images as BMPs to this directory"
|
|
<< std::endl;
|
|
std::cout << "\tpipelined\t:\tUse decoding in phases" << std::endl;
|
|
std::cout << "\tbatched\t\t:\tUse batched interface" << std::endl;
|
|
std::cout << "\toutput_format\t:\tnvJPEG output format for decoding. One "
|
|
"of [rgb, rgbi, bgr, bgri, yuv, y, unchanged]"
|
|
<< std::endl;
|
|
return EXIT_SUCCESS;
|
|
}
|
|
|
|
decode_params_t params;
|
|
|
|
params.input_dir = "./";
|
|
if ((pidx = findParamIndex(argv, argc, "-i")) != -1) {
|
|
params.input_dir = argv[pidx + 1];
|
|
} else {
|
|
// Search in default paths for input images.
|
|
int found = getInputDir(params.input_dir, argv[0]);
|
|
if (!found)
|
|
{
|
|
std::cout << "Please specify input directory with encoded images"<< std::endl;
|
|
return EXIT_WAIVED;
|
|
}
|
|
}
|
|
|
|
params.batch_size = 1;
|
|
if ((pidx = findParamIndex(argv, argc, "-b")) != -1) {
|
|
params.batch_size = std::atoi(argv[pidx + 1]);
|
|
}
|
|
|
|
params.total_images = -1;
|
|
if ((pidx = findParamIndex(argv, argc, "-t")) != -1) {
|
|
params.total_images = std::atoi(argv[pidx + 1]);
|
|
}
|
|
|
|
params.dev = 0;
|
|
params.dev = findCudaDevice(argc, argv);
|
|
|
|
params.warmup = 0;
|
|
if ((pidx = findParamIndex(argv, argc, "-w")) != -1) {
|
|
params.warmup = std::atoi(argv[pidx + 1]);
|
|
}
|
|
|
|
params.batched = false;
|
|
if ((pidx = findParamIndex(argv, argc, "-batched")) != -1) {
|
|
params.batched = true;
|
|
}
|
|
|
|
params.pipelined = false;
|
|
if ((pidx = findParamIndex(argv, argc, "-pipelined")) != -1) {
|
|
params.pipelined = true;
|
|
}
|
|
|
|
params.fmt = NVJPEG_OUTPUT_RGB;
|
|
if ((pidx = findParamIndex(argv, argc, "-fmt")) != -1) {
|
|
std::string sfmt = argv[pidx + 1];
|
|
if (sfmt == "rgb")
|
|
params.fmt = NVJPEG_OUTPUT_RGB;
|
|
else if (sfmt == "bgr")
|
|
params.fmt = NVJPEG_OUTPUT_BGR;
|
|
else if (sfmt == "rgbi")
|
|
params.fmt = NVJPEG_OUTPUT_RGBI;
|
|
else if (sfmt == "bgri")
|
|
params.fmt = NVJPEG_OUTPUT_BGRI;
|
|
else if (sfmt == "yuv")
|
|
params.fmt = NVJPEG_OUTPUT_YUV;
|
|
else if (sfmt == "y")
|
|
params.fmt = NVJPEG_OUTPUT_Y;
|
|
else if (sfmt == "unchanged")
|
|
params.fmt = NVJPEG_OUTPUT_UNCHANGED;
|
|
else {
|
|
std::cout << "Unknown format: " << sfmt << std::endl;
|
|
return EXIT_FAILURE;
|
|
}
|
|
}
|
|
|
|
params.write_decoded = false;
|
|
if ((pidx = findParamIndex(argv, argc, "-o")) != -1) {
|
|
params.output_dir = argv[pidx + 1];
|
|
if (params.fmt != NVJPEG_OUTPUT_RGB && params.fmt != NVJPEG_OUTPUT_BGR &&
|
|
params.fmt != NVJPEG_OUTPUT_RGBI && params.fmt != NVJPEG_OUTPUT_BGRI) {
|
|
std::cout << "We can write ony BMPs, which require output format be "
|
|
"either RGB/BGR or RGBi/BGRi"
|
|
<< std::endl;
|
|
return EXIT_FAILURE;
|
|
}
|
|
params.write_decoded = true;
|
|
}
|
|
|
|
cudaDeviceProp props;
|
|
checkCudaErrors(cudaGetDeviceProperties(&props, params.dev));
|
|
|
|
printf("Using GPU %d (%s, %d SMs, %d th/SM max, CC %d.%d, ECC %s)\n",
|
|
params.dev, props.name, props.multiProcessorCount,
|
|
props.maxThreadsPerMultiProcessor, props.major, props.minor,
|
|
props.ECCEnabled ? "on" : "off");
|
|
|
|
nvjpegDevAllocator_t dev_allocator = {&dev_malloc, &dev_free};
|
|
nvjpegPinnedAllocator_t pinned_allocator ={&host_malloc, &host_free};
|
|
int flags = 0;
|
|
checkCudaErrors(nvjpegCreateEx(NVJPEG_BACKEND_DEFAULT, &dev_allocator,
|
|
&pinned_allocator,flags, ¶ms.nvjpeg_handle));
|
|
|
|
checkCudaErrors(
|
|
nvjpegJpegStateCreate(params.nvjpeg_handle, ¶ms.nvjpeg_state));
|
|
checkCudaErrors(
|
|
nvjpegDecodeBatchedInitialize(params.nvjpeg_handle, params.nvjpeg_state,
|
|
params.batch_size, 1, params.fmt));
|
|
|
|
if(params.pipelined ){
|
|
create_decoupled_api_handles(params);
|
|
}
|
|
// read source images
|
|
FileNames image_names;
|
|
readInput(params.input_dir, image_names);
|
|
|
|
if (params.total_images == -1) {
|
|
params.total_images = image_names.size();
|
|
} else if (params.total_images % params.batch_size) {
|
|
params.total_images =
|
|
((params.total_images) / params.batch_size) * params.batch_size;
|
|
std::cout << "Changing total_images number to " << params.total_images
|
|
<< " to be multiple of batch_size - " << params.batch_size
|
|
<< std::endl;
|
|
}
|
|
|
|
std::cout << "Decoding images in directory: " << params.input_dir
|
|
<< ", total " << params.total_images << ", batchsize "
|
|
<< params.batch_size << std::endl;
|
|
|
|
double total;
|
|
if (process_images(image_names, params, total)) return EXIT_FAILURE;
|
|
std::cout << "Total decoding time: " << total << std::endl;
|
|
std::cout << "Avg decoding time per image: " << total / params.total_images
|
|
<< std::endl;
|
|
std::cout << "Avg images per sec: " << params.total_images / total
|
|
<< std::endl;
|
|
std::cout << "Avg decoding time per batch: "
|
|
<< total / ((params.total_images + params.batch_size - 1) /
|
|
params.batch_size)
|
|
<< std::endl;
|
|
|
|
if(params.pipelined ){
|
|
destroy_decoupled_api_handles(params);
|
|
}
|
|
|
|
checkCudaErrors(nvjpegJpegStateDestroy(params.nvjpeg_state));
|
|
checkCudaErrors(nvjpegDestroy(params.nvjpeg_handle));
|
|
|
|
return EXIT_SUCCESS;
|
|
}
|