cuda-samples/Samples/nvJPEG/nvJPEG.cpp

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/* Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
// This sample needs at least CUDA 10.0. It demonstrates usages of the nvJPEG
// library nvJPEG supports single and multiple image(batched) decode. Multiple
// images can be decoded using the API for batch mode
#include <cuda_runtime_api.h>
#include "nvJPEG_helper.hxx"
int dev_malloc(void **p, size_t s) { return (int)cudaMalloc(p, s); }
int dev_free(void *p) { return (int)cudaFree(p); }
typedef std::vector<std::string> FileNames;
typedef std::vector<std::vector<char> > FileData;
struct decode_params_t {
std::string input_dir;
int batch_size;
int total_images;
int dev;
int warmup;
nvjpegJpegState_t nvjpeg_state;
nvjpegHandle_t nvjpeg_handle;
cudaStream_t stream;
nvjpegOutputFormat_t fmt;
bool write_decoded;
std::string output_dir;
bool pipelined;
bool batched;
};
int read_next_batch(FileNames &image_names, int batch_size,
FileNames::iterator &cur_iter, FileData &raw_data,
std::vector<size_t> &raw_len, FileNames &current_names) {
int counter = 0;
while (counter < batch_size) {
if (cur_iter == image_names.end()) {
std::cerr << "Image list is too short to fill the batch, adding files "
"from the beginning of the image list"
<< std::endl;
cur_iter = image_names.begin();
}
if (image_names.size() == 0) {
std::cerr << "No valid images left in the input list, exit" << std::endl;
return EXIT_FAILURE;
}
// Read an image from disk.
std::ifstream input(cur_iter->c_str(),
std::ios::in | std::ios::binary | std::ios::ate);
if (!(input.is_open())) {
std::cerr << "Cannot open image: " << *cur_iter
<< ", removing it from image list" << std::endl;
image_names.erase(cur_iter);
continue;
}
// Get the size
std::streamsize file_size = input.tellg();
input.seekg(0, std::ios::beg);
// resize if buffer is too small
if (raw_data[counter].size() < file_size) {
raw_data[counter].resize(file_size);
}
if (!input.read(raw_data[counter].data(), file_size)) {
std::cerr << "Cannot read from file: " << *cur_iter
<< ", removing it from image list" << std::endl;
image_names.erase(cur_iter);
continue;
}
raw_len[counter] = file_size;
current_names[counter] = *cur_iter;
counter++;
cur_iter++;
}
return EXIT_SUCCESS;
}
// prepare buffers for RGBi output format
int prepare_buffers(FileData &file_data, std::vector<size_t> &file_len,
std::vector<int> &img_width, std::vector<int> &img_height,
std::vector<nvjpegImage_t> &ibuf,
std::vector<nvjpegImage_t> &isz, FileNames &current_names,
decode_params_t &params) {
int widths[NVJPEG_MAX_COMPONENT];
int heights[NVJPEG_MAX_COMPONENT];
int channels;
nvjpegChromaSubsampling_t subsampling;
for (int i = 0; i < file_data.size(); i++) {
checkCudaErrors(nvjpegGetImageInfo(
params.nvjpeg_handle, (unsigned char *)file_data[i].data(), file_len[i],
&channels, &subsampling, widths, heights));
img_width[i] = widths[0];
img_height[i] = heights[0];
std::cout << "Processing: " << current_names[i] << std::endl;
std::cout << "Image is " << channels << " channels." << std::endl;
for (int c = 0; c < channels; c++) {
std::cout << "Channel #" << c << " size: " << widths[c] << " x "
<< heights[c] << std::endl;
}
switch (subsampling) {
case NVJPEG_CSS_444:
std::cout << "YUV 4:4:4 chroma subsampling" << std::endl;
break;
case NVJPEG_CSS_440:
std::cout << "YUV 4:4:0 chroma subsampling" << std::endl;
break;
case NVJPEG_CSS_422:
std::cout << "YUV 4:2:2 chroma subsampling" << std::endl;
break;
case NVJPEG_CSS_420:
std::cout << "YUV 4:2:0 chroma subsampling" << std::endl;
break;
case NVJPEG_CSS_411:
std::cout << "YUV 4:1:1 chroma subsampling" << std::endl;
break;
case NVJPEG_CSS_410:
std::cout << "YUV 4:1:0 chroma subsampling" << std::endl;
break;
case NVJPEG_CSS_GRAY:
std::cout << "Grayscale JPEG " << std::endl;
break;
case NVJPEG_CSS_UNKNOWN:
std::cout << "Unknown chroma subsampling" << std::endl;
return EXIT_FAILURE;
}
int mul = 1;
// in the case of interleaved RGB output, write only to single channel, but
// 3 samples at once
if (params.fmt == NVJPEG_OUTPUT_RGBI || params.fmt == NVJPEG_OUTPUT_BGRI) {
channels = 1;
mul = 3;
}
// in the case of rgb create 3 buffers with sizes of original image
else if (params.fmt == NVJPEG_OUTPUT_RGB ||
params.fmt == NVJPEG_OUTPUT_BGR) {
channels = 3;
widths[1] = widths[2] = widths[0];
heights[1] = heights[2] = heights[0];
}
// realloc output buffer if required
for (int c = 0; c < channels; c++) {
int aw = mul * widths[c];
int ah = heights[c];
int sz = aw * ah;
ibuf[i].pitch[c] = aw;
if (sz > isz[i].pitch[c]) {
if (ibuf[i].channel[c]) {
checkCudaErrors(cudaFree(ibuf[i].channel[c]));
}
checkCudaErrors(cudaMalloc(&ibuf[i].channel[c], sz));
isz[i].pitch[c] = sz;
}
}
}
return EXIT_SUCCESS;
}
void release_buffers(std::vector<nvjpegImage_t> &ibuf) {
for (int i = 0; i < ibuf.size(); i++) {
for (int c = 0; c < NVJPEG_MAX_COMPONENT; c++)
if (ibuf[i].channel[c]) checkCudaErrors(cudaFree(ibuf[i].channel[c]));
}
}
int decode_images(const FileData &img_data, const std::vector<size_t> &img_len,
std::vector<nvjpegImage_t> &out, decode_params_t &params,
double &time) {
checkCudaErrors(cudaStreamSynchronize(params.stream));
nvjpegStatus_t err;
StopWatchInterface *timer = NULL;
sdkCreateTimer(&timer);
if (!params.batched) {
if (!params.pipelined) // decode one image at a time
{
int thread_idx = 0;
sdkStartTimer(&timer);
for (int i = 0; i < params.batch_size; i++) {
checkCudaErrors(nvjpegDecode(params.nvjpeg_handle, params.nvjpeg_state,
(const unsigned char *)img_data[i].data(),
img_len[i], params.fmt, &out[i],
params.stream));
checkCudaErrors(cudaStreamSynchronize(params.stream));
}
} else {
int thread_idx = 0;
sdkStartTimer(&timer);
for (int i = 0; i < params.batch_size; i++) {
checkCudaErrors(
nvjpegDecodePhaseOne(params.nvjpeg_handle, params.nvjpeg_state,
(const unsigned char *)img_data[i].data(),
img_len[i], params.fmt, params.stream));
checkCudaErrors(cudaStreamSynchronize(params.stream));
checkCudaErrors(nvjpegDecodePhaseTwo(
params.nvjpeg_handle, params.nvjpeg_state, params.stream));
checkCudaErrors(nvjpegDecodePhaseThree(
params.nvjpeg_handle, params.nvjpeg_state, &out[i], params.stream));
}
checkCudaErrors(cudaStreamSynchronize(params.stream));
}
} else {
std::vector<const unsigned char *> raw_inputs;
for (int i = 0; i < params.batch_size; i++) {
raw_inputs.push_back((const unsigned char *)img_data[i].data());
}
if (!params.pipelined) // decode multiple images in a single batch
{
sdkStartTimer(&timer);
checkCudaErrors(nvjpegDecodeBatched(
params.nvjpeg_handle, params.nvjpeg_state, raw_inputs.data(),
img_len.data(), out.data(), params.stream));
checkCudaErrors(cudaStreamSynchronize(params.stream));
} else {
int thread_idx = 0;
for (int i = 0; i < params.batch_size; i++) {
checkCudaErrors(nvjpegDecodeBatchedPhaseOne(
params.nvjpeg_handle, params.nvjpeg_state, raw_inputs[i],
img_len[i], i, thread_idx, params.stream));
}
checkCudaErrors(nvjpegDecodeBatchedPhaseTwo(
params.nvjpeg_handle, params.nvjpeg_state, params.stream));
checkCudaErrors(nvjpegDecodeBatchedPhaseThree(params.nvjpeg_handle,
params.nvjpeg_state,
out.data(), params.stream));
checkCudaErrors(cudaStreamSynchronize(params.stream));
}
}
sdkStopTimer(&timer);
time = sdkGetAverageTimerValue(&timer)/1000.0f;
return EXIT_SUCCESS;
}
int write_images(std::vector<nvjpegImage_t> &iout, std::vector<int> &widths,
std::vector<int> &heights, decode_params_t &params,
FileNames &filenames) {
for (int i = 0; i < params.batch_size; i++) {
// Get the file name, without extension.
// This will be used to rename the output file.
size_t position = filenames[i].rfind("/");
std::string sFileName =
(std::string::npos == position)
? filenames[i]
: filenames[i].substr(position + 1, filenames[i].size());
position = sFileName.rfind(".");
sFileName = (std::string::npos == position) ? sFileName
: sFileName.substr(0, position);
std::string fname(params.output_dir + "/" + sFileName + ".bmp");
int err;
if (params.fmt == NVJPEG_OUTPUT_RGB || params.fmt == NVJPEG_OUTPUT_BGR) {
err = writeBMP(fname.c_str(), iout[i].channel[0], iout[i].pitch[0],
iout[i].channel[1], iout[i].pitch[1], iout[i].channel[2],
iout[i].pitch[2], widths[i], heights[i]);
} else if (params.fmt == NVJPEG_OUTPUT_RGBI ||
params.fmt == NVJPEG_OUTPUT_BGRI) {
// Write BMP from interleaved data
err = writeBMPi(fname.c_str(), iout[i].channel[0], iout[i].pitch[0],
widths[i], heights[i]);
}
if (err) {
std::cout << "Cannot write output file: " << fname << std::endl;
return EXIT_FAILURE;
}
std::cout << "Done writing decoded image to file: " << fname << std::endl;
}
}
double process_images(FileNames &image_names, decode_params_t &params,
double &total) {
// vector for storing raw files and file lengths
FileData file_data(params.batch_size);
std::vector<size_t> file_len(params.batch_size);
FileNames current_names(params.batch_size);
std::vector<int> widths(params.batch_size);
std::vector<int> heights(params.batch_size);
// we wrap over image files to process total_images of files
FileNames::iterator file_iter = image_names.begin();
// stream for decoding
checkCudaErrors(
cudaStreamCreateWithFlags(&params.stream, cudaStreamNonBlocking));
int total_processed = 0;
// output buffers
std::vector<nvjpegImage_t> iout(params.batch_size);
// output buffer sizes, for convenience
std::vector<nvjpegImage_t> isz(params.batch_size);
for (int i = 0; i < iout.size(); i++) {
for (int c = 0; c < NVJPEG_MAX_COMPONENT; c++) {
iout[i].channel[c] = NULL;
iout[i].pitch[c] = 0;
isz[i].pitch[c] = 0;
}
}
double test_time = 0;
int warmup = 0;
while (total_processed < params.total_images) {
if (read_next_batch(image_names, params.batch_size, file_iter, file_data,
file_len, current_names))
return EXIT_FAILURE;
if (prepare_buffers(file_data, file_len, widths, heights, iout, isz,
current_names, params))
return EXIT_FAILURE;
double time;
if (decode_images(file_data, file_len, iout, params, time))
return EXIT_FAILURE;
if (warmup < params.warmup) {
warmup++;
} else {
total_processed += params.batch_size;
test_time += time;
}
if (params.write_decoded)
write_images(iout, widths, heights, params, current_names);
}
total = test_time;
release_buffers(iout);
checkCudaErrors(cudaStreamDestroy(params.stream));
return EXIT_SUCCESS;
}
// parse parameters
int findParamIndex(const char **argv, int argc, const char *parm) {
int count = 0;
int index = -1;
for (int i = 0; i < argc; i++) {
if (strncmp(argv[i], parm, 100) == 0) {
index = i;
count++;
}
}
if (count == 0 || count == 1) {
return index;
} else {
std::cout << "Error, parameter " << parm
<< " has been specified more than once, exiting\n"
<< std::endl;
return -1;
}
return -1;
}
int main(int argc, const char *argv[]) {
int pidx;
if ((pidx = findParamIndex(argv, argc, "-h")) != -1 ||
(pidx = findParamIndex(argv, argc, "--help")) != -1) {
std::cout << "Usage: " << argv[0]
<< " -i images_dir [-b batch_size] [-t total_images] [-device= "
"device_id] [-w warmup_iterations] [-o output_dir] "
"[-pipelined] [-batched] [-fmt output_format]\n";
std::cout << "Parameters: " << std::endl;
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 {
std::cerr << "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};
checkCudaErrors(nvjpegCreate(NVJPEG_BACKEND_DEFAULT, &dev_allocator,
&params.nvjpeg_handle));
checkCudaErrors(
nvjpegJpegStateCreate(params.nvjpeg_handle, &params.nvjpeg_state));
checkCudaErrors(
nvjpegDecodeBatchedInitialize(params.nvjpeg_handle, params.nvjpeg_state,
params.batch_size, 1, params.fmt));
// 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;
checkCudaErrors(nvjpegJpegStateDestroy(params.nvjpeg_state));
checkCudaErrors(nvjpegDestroy(params.nvjpeg_handle));
return EXIT_SUCCESS;
}