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467 lines
26 KiB
C++
467 lines
26 KiB
C++
// ------------------------- OpenPose Library Tutorial - Thread - Example 2 - Synchronous -------------------------
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// Synchronous mode: ideal for performance. The user can add his own frames producer / post-processor / consumer to the OpenPose wrapper or use the default ones.
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// This example shows the user how to use the OpenPose wrapper class:
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// 1. Extract and render keypoint / heatmap / PAF of that image
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// 2. Save the results on disc
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// 3. Display the rendered pose
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// Everything in a multi-thread scenario
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// In addition to the previous OpenPose modules, we also need to use:
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// 1. `core` module:
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// For the Array<float> class that the `pose` module needs
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// For the Datum struct that the `thread` module sends between the queues
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// 2. `utilities` module: for the error & logging functions, i.e. op::error & op::log respectively
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// This file should only be used for the user to take specific examples.
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// C++ std library dependencies
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#include <atomic>
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#include <chrono> // `std::chrono::` functions and classes, e.g. std::chrono::milliseconds
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#include <cstdio> // sscanf
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#include <string>
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#include <thread> // std::this_thread
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#include <vector>
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// Other 3rdpary depencencies
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#include <gflags/gflags.h> // DEFINE_bool, DEFINE_int32, DEFINE_int64, DEFINE_uint64, DEFINE_double, DEFINE_string
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#include <glog/logging.h> // google::InitGoogleLogging
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// OpenPose dependencies
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// Option a) Importing all modules
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#include <openpose/headers.hpp>
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// Option b) Manually importing the desired modules. Recommended if you only intend to use a few modules.
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// #include <openpose/core/headers.hpp>
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// #include <openpose/experimental/headers.hpp>
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// #include <openpose/face/headers.hpp>
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// #include <openpose/filestream/headers.hpp>
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// #include <openpose/gui/headers.hpp>
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// #include <openpose/pose/headers.hpp>
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// #include <openpose/producer/headers.hpp>
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// #include <openpose/thread/headers.hpp>
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// #include <openpose/utilities/headers.hpp>
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// #include <openpose/wrapper/headers.hpp>
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// See all the available parameter options withe the `--help` flag. E.g. `./build/examples/openpose/openpose.bin --help`.
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// Note: This command will show you flags for other unnecessary 3rdparty files. Check only the flags for the OpenPose
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// executable. E.g. for `openpose.bin`, look for `Flags from examples/openpose/openpose.cpp:`.
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// Debugging
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DEFINE_int32(logging_level, 3, "The logging level. Integer in the range [0, 255]. 0 will output any log() message, while"
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" 255 will not output any. Current OpenPose library messages are in the range 0-4: 1 for"
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" low priority messages and 4 for important ones.");
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// Producer
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DEFINE_string(image_dir, "examples/media/", "Process a directory of images.");
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// OpenPose
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DEFINE_string(model_folder, "models/", "Folder where the pose models (COCO and MPI) are located.");
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DEFINE_string(resolution, "1280x720", "The image resolution (display and output). Use \"-1x-1\" to force the program to use the"
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" default images resolution.");
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DEFINE_int32(num_gpu, -1, "The number of GPU devices to use. If negative, it will use all the available GPUs in your"
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" machine.");
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DEFINE_int32(num_gpu_start, 0, "GPU device start number.");
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DEFINE_int32(keypoint_scale, 0, "Scaling of the (x,y) coordinates of the final pose data array, i.e. the scale of the (x,y)"
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" coordinates that will be saved with the `write_keypoint` & `write_keypoint_json` flags."
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" Select `0` to scale it to the original source resolution, `1`to scale it to the net output"
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" size (set with `net_resolution`), `2` to scale it to the final output size (set with"
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" `resolution`), `3` to scale it in the range [0,1], and 4 for range [-1,1]. Non related"
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" with `num_scales` and `scale_gap`.");
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// OpenPose Body Pose
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DEFINE_string(model_pose, "COCO", "Model to be used (e.g. COCO, MPI, MPI_4_layers).");
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DEFINE_string(net_resolution, "656x368", "Multiples of 16. If it is increased, the accuracy usually increases. If it is decreased,"
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" the speed increases.");
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DEFINE_int32(num_scales, 1, "Number of scales to average.");
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DEFINE_double(scale_gap, 0.3, "Scale gap between scales. No effect unless num_scales>1. Initial scale is always 1. If you"
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" want to change the initial scale, you actually want to multiply the `net_resolution` by"
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" your desired initial scale.");
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DEFINE_bool(heatmaps_add_parts, false, "If true, it will add the body part heatmaps to the final op::Datum::poseHeatMaps array"
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" (program speed will decrease). Not required for our library, enable it only if you intend"
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" to process this information later. If more than one `add_heatmaps_X` flag is enabled, it"
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" will place then in sequential memory order: body parts + bkg + PAFs. It will follow the"
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" order on POSE_BODY_PART_MAPPING in `include/openpose/pose/poseParameters.hpp`.");
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DEFINE_bool(heatmaps_add_bkg, false, "Same functionality as `add_heatmaps_parts`, but adding the heatmap corresponding to"
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" background.");
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DEFINE_bool(heatmaps_add_PAFs, false, "Same functionality as `add_heatmaps_parts`, but adding the PAFs.");
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DEFINE_int32(heatmaps_scale, 2, "Set 0 to scale op::Datum::poseHeatMaps in the range [0,1], 1 for [-1,1]; and 2 for integer"
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" rounded [0,255].");
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// OpenPose Face
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DEFINE_bool(face, false, "Enables face keypoint detection. It will share some parameters from the body pose, e.g."
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" `model_folder`.");
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DEFINE_string(face_net_resolution, "368x368", "Multiples of 16. Analogous to `net_resolution` but applied to the face keypoint detector."
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" 320x320 usually works fine while giving a substantial speed up when multiple faces on the"
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" image.");
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// OpenPose Hand
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// OpenPose Rendering
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DEFINE_int32(part_to_show, 0, "Part to show from the start.");
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DEFINE_bool(disable_blending, false, "If blending is enabled, it will merge the results with the original frame. If disabled, it"
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" will only display the results.");
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// OpenPose Rendering Pose
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DEFINE_int32(render_pose, 1, "Set to 0 for no rendering, 1 for CPU rendering (slightly faster), and 2 for GPU rendering"
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" (slower but greater functionality, e.g. `alpha_X` flags). If rendering is enabled, it will"
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" render both `outputData` and `cvOutputData` with the original image and desired body part"
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" to be shown (i.e. keypoints, heat maps or PAFs).");
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DEFINE_double(alpha_pose, 0.6, "Blending factor (range 0-1) for the body part rendering. 1 will show it completely, 0 will"
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" hide it. Only valid for GPU rendering.");
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DEFINE_double(alpha_heatmap, 0.7, "Blending factor (range 0-1) between heatmap and original frame. 1 will only show the"
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" heatmap, 0 will only show the frame. Only valid for GPU rendering.");
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// OpenPose Rendering Face
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DEFINE_int32(render_face, -1, "Analogous to `render_pose` but applied to the face. Extra option: -1 to use the same"
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" configuration that `render_pose` is using.");
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DEFINE_double(alpha_face, 0.6, "Analogous to `alpha_pose` but applied to face.");
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DEFINE_double(alpha_heatmap_face, 0.7, "Analogous to `alpha_heatmap` but applied to face.");
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// Result Saving
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DEFINE_string(write_images, "", "Directory to write rendered frames in `write_images_format` image format.");
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DEFINE_string(write_images_format, "png", "File extension and format for `write_images`, e.g. png, jpg or bmp. Check the OpenCV"
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" function cv::imwrite for all compatible extensions.");
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DEFINE_string(write_video, "", "Full file path to write rendered frames in motion JPEG video format. It might fail if the"
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" final path does not finish in `.avi`. It internally uses cv::VideoWriter.");
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DEFINE_string(write_keypoint, "", "Directory to write the people pose keypoint data. Format with `write_keypoint_format`.");
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DEFINE_string(write_keypoint_format, "yml", "File extension and format for `write_keypoint`: json, xml, yaml & yml. Json not available"
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" for OpenCV < 3.0, use `write_keypoint_json` instead.");
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DEFINE_string(write_keypoint_json, "", "Directory to write people pose data in *.json format, compatible with any OpenCV version.");
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DEFINE_string(write_coco_json, "", "Full file path to write people pose data with *.json COCO validation format.");
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DEFINE_string(write_heatmaps, "", "Directory to write heatmaps in *.png format. At least 1 `add_heatmaps_X` flag must be"
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" enabled.");
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DEFINE_string(write_heatmaps_format, "png", "File extension and format for `write_heatmaps`, analogous to `write_images_format`."
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" Recommended `png` or any compressed and lossless format.");
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// If the user needs his own variables, he can inherit the op::Datum struct and add them
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// UserDatum can be directly used by the OpenPose wrapper because it inherits from op::Datum, just define Wrapper<UserDatum> instead of
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// Wrapper<op::Datum>
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struct UserDatum : public op::Datum
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{
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bool boolThatUserNeedsForSomeReason;
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UserDatum(const bool boolThatUserNeedsForSomeReason_ = false) :
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boolThatUserNeedsForSomeReason{boolThatUserNeedsForSomeReason_}
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{}
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};
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// The W-classes can be implemented either as a template or as simple classes given
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// that the user usually knows which kind of data he will move between the queues,
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// in this case we assume a std::shared_ptr of a std::vector of UserDatum
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// This worker will just read and return all the jpg files in a directory
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class WUserInput : public op::WorkerProducer<std::shared_ptr<std::vector<UserDatum>>>
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{
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public:
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WUserInput(const std::string& directoryPath) :
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mImageFiles{op::getFilesOnDirectory(directoryPath, "jpg")},
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// mImageFiles{op::getFilesOnDirectory(directoryPath, std::vector<std::string>{"jpg", "png"})}, // If we want "jpg" + "png" images
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mCounter{0}
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{
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if (mImageFiles.empty())
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op::error("No images found on: " + directoryPath, __LINE__, __FUNCTION__, __FILE__);
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}
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void initializationOnThread() {}
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std::shared_ptr<std::vector<UserDatum>> workProducer()
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{
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try
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{
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// Close program when empty frame
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if (mImageFiles.size() <= mCounter)
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{
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op::log("Last frame read and added to queue. Closing program after it is processed.", op::Priority::Max);
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// This funtion stops this worker, which will eventually stop the whole thread system once all the frames have been processed
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this->stop();
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return nullptr;
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}
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else
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{
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// Create new datum
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auto datumsPtr = std::make_shared<std::vector<UserDatum>>();
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datumsPtr->emplace_back();
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auto& datum = datumsPtr->at(0);
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// Fill datum
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datum.cvInputData = cv::imread(mImageFiles.at(mCounter++));
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// If empty frame -> return nullptr
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if (datum.cvInputData.empty())
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{
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op::log("Empty frame detected on path: " + mImageFiles.at(mCounter-1) + ". Closing program.", op::Priority::Max);
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this->stop();
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datumsPtr = nullptr;
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}
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return datumsPtr;
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}
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}
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catch (const std::exception& e)
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{
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op::log("Some kind of unexpected error happened.");
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this->stop();
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op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
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return nullptr;
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}
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}
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private:
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const std::vector<std::string> mImageFiles;
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unsigned long long mCounter;
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};
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// This worker will just invert the image
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class WUserPostProcessing : public op::Worker<std::shared_ptr<std::vector<UserDatum>>>
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{
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public:
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WUserPostProcessing()
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{
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// User's constructor here
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}
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void initializationOnThread() {}
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void work(std::shared_ptr<std::vector<UserDatum>>& datumsPtr)
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{
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// User's post-processing (after OpenPose processing & before OpenPose outputs) here
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// datum.cvOutputData: rendered frame with pose or heatmaps
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// datum.poseKeypoints: Array<float> with the estimated pose
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try
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{
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if (datumsPtr != nullptr && !datumsPtr->empty())
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for (auto& datum : *datumsPtr)
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cv::bitwise_not(datum.cvOutputData, datum.cvOutputData);
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}
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catch (const std::exception& e)
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{
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op::log("Some kind of unexpected error happened.");
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this->stop();
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op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
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}
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}
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};
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// This worker will just read and return all the jpg files in a directory
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class WUserOutput : public op::WorkerConsumer<std::shared_ptr<std::vector<UserDatum>>>
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{
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public:
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void initializationOnThread() {}
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void workConsumer(const std::shared_ptr<std::vector<UserDatum>>& datumsPtr)
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{
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try
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{
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// User's displaying/saving/other processing here
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// datum.cvOutputData: rendered frame with pose or heatmaps
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// datum.poseKeypoints: Array<float> with the estimated pose
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if (datumsPtr != nullptr && !datumsPtr->empty())
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{
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cv::imshow("User worker GUI", datumsPtr->at(0).cvOutputData);
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cv::waitKey(1); // It displays the image and sleeps at least 1 ms (it usually sleeps ~5-10 msec to display the image)
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}
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}
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catch (const std::exception& e)
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{
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op::log("Some kind of unexpected error happened.");
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this->stop();
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op::error(e.what(), __LINE__, __FUNCTION__, __FILE__);
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}
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}
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};
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op::PoseModel gflagToPoseModel(const std::string& poseModeString)
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{
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op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
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if (poseModeString == "COCO")
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return op::PoseModel::COCO_18;
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else if (poseModeString == "MPI")
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return op::PoseModel::MPI_15;
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else if (poseModeString == "MPI_4_layers")
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return op::PoseModel::MPI_15_4;
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else
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{
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op::error("String does not correspond to any model (COCO, MPI, MPI_4_layers)", __LINE__, __FUNCTION__, __FILE__);
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return op::PoseModel::COCO_18;
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}
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}
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op::ScaleMode gflagToScaleMode(const int keypointScale)
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{
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op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
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if (keypointScale == 0)
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return op::ScaleMode::InputResolution;
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else if (keypointScale == 1)
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return op::ScaleMode::NetOutputResolution;
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else if (keypointScale == 2)
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return op::ScaleMode::OutputResolution;
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else if (keypointScale == 3)
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return op::ScaleMode::ZeroToOne;
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else if (keypointScale == 4)
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return op::ScaleMode::PlusMinusOne;
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else
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{
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const std::string message = "String does not correspond to any scale mode: (0, 1, 2, 3, 4) for (InputResolution,"
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" NetOutputResolution, OutputResolution, ZeroToOne, PlusMinusOne).";
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op::error(message, __LINE__, __FUNCTION__, __FILE__);
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return op::ScaleMode::InputResolution;
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}
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}
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std::vector<op::HeatMapType> gflagToHeatMaps(const bool heatMapsAddParts, const bool heatMapsAddBkg, const bool heatMapsAddPAFs)
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{
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std::vector<op::HeatMapType> heatMapTypes;
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if (heatMapsAddParts)
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heatMapTypes.emplace_back(op::HeatMapType::Parts);
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if (heatMapsAddBkg)
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heatMapTypes.emplace_back(op::HeatMapType::Background);
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if (heatMapsAddPAFs)
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heatMapTypes.emplace_back(op::HeatMapType::PAFs);
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return heatMapTypes;
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}
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op::RenderMode gflagToRenderMode(const int renderFlag, const int renderPoseFlag = -2)
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{
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if (renderFlag == -1 && renderPoseFlag != -2)
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return gflagToRenderMode(renderPoseFlag, -2);
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else if (renderFlag == 0)
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return op::RenderMode::None;
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else if (renderFlag == 1)
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return op::RenderMode::Cpu;
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else if (renderFlag == 2)
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return op::RenderMode::Gpu;
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else
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{
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op::error("Undefined RenderMode selected.", __LINE__, __FUNCTION__, __FILE__);
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return op::RenderMode::None;
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}
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}
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// Google flags into program variables
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std::tuple<op::Point<int>, op::Point<int>, op::Point<int>, op::PoseModel, op::ScaleMode, std::vector<op::HeatMapType>,
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op::ScaleMode> gflagsToOpParameters()
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{
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op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
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// outputSize
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op::Point<int> outputSize;
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auto nRead = sscanf(FLAGS_resolution.c_str(), "%dx%d", &outputSize.x, &outputSize.y);
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op::checkE(nRead, 2, "Error, resolution format (" + FLAGS_resolution + ") invalid, should be e.g., 960x540 ",
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__LINE__, __FUNCTION__, __FILE__);
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// netInputSize
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op::Point<int> netInputSize;
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nRead = sscanf(FLAGS_net_resolution.c_str(), "%dx%d", &netInputSize.x, &netInputSize.y);
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op::checkE(nRead, 2, "Error, net resolution format (" + FLAGS_net_resolution + ") invalid, should be e.g., 656x368 (multiples of 16)",
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__LINE__, __FUNCTION__, __FILE__);
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// faceNetInputSize
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op::Point<int> faceNetInputSize;
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nRead = sscanf(FLAGS_face_net_resolution.c_str(), "%dx%d", &faceNetInputSize.x, &faceNetInputSize.y);
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op::checkE(nRead, 2, "Error, face net resolution format (" + FLAGS_face_net_resolution
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+ ") invalid, should be e.g., 368x368 (multiples of 16)", __LINE__, __FUNCTION__, __FILE__);
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// poseModel
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const auto poseModel = gflagToPoseModel(FLAGS_model_pose);
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// keypointScale
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const auto keypointScale = gflagToScaleMode(FLAGS_keypoint_scale);
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// heatmaps to add
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const auto heatMapTypes = gflagToHeatMaps(FLAGS_heatmaps_add_parts, FLAGS_heatmaps_add_bkg, FLAGS_heatmaps_add_PAFs);
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op::check(FLAGS_heatmaps_scale >= 0 && FLAGS_heatmaps_scale <= 2, "Non valid `heatmaps_scale`.", __LINE__, __FUNCTION__, __FILE__);
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const auto heatMapScale = (FLAGS_heatmaps_scale == 0 ? op::ScaleMode::PlusMinusOne
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: (FLAGS_heatmaps_scale == 1 ? op::ScaleMode::ZeroToOne : op::ScaleMode::UnsignedChar ));
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// return
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return std::make_tuple(outputSize, netInputSize, faceNetInputSize, poseModel, keypointScale, heatMapTypes, heatMapScale);
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}
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int openPoseTutorialWrapper2()
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{
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// logging_level
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op::check(0 <= FLAGS_logging_level && FLAGS_logging_level <= 255, "Wrong logging_level value.", __LINE__, __FUNCTION__, __FILE__);
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op::ConfigureLog::setPriorityThreshold((op::Priority)FLAGS_logging_level);
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// op::ConfigureLog::setPriorityThreshold(op::Priority::None); // To print all logging messages
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op::log("Starting pose estimation demo.", op::Priority::Max);
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const auto timerBegin = std::chrono::high_resolution_clock::now();
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// Applying user defined configuration
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op::Point<int> outputSize;
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op::Point<int> netInputSize;
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op::Point<int> faceNetInputSize;
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op::PoseModel poseModel;
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op::ScaleMode keypointScale;
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std::vector<op::HeatMapType> heatMapTypes;
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op::ScaleMode heatMapScale;
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std::tie(outputSize, netInputSize, faceNetInputSize, poseModel, keypointScale, heatMapTypes, heatMapScale) = gflagsToOpParameters();
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op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__);
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// Initializing the user custom classes
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// Frames producer (e.g. video, webcam, ...)
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auto wUserInput = std::make_shared<WUserInput>(FLAGS_image_dir);
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// Processing
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auto wUserPostProcessing = std::make_shared<WUserPostProcessing>();
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// GUI (Display)
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auto wUserOutput = std::make_shared<WUserOutput>();
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op::Wrapper<std::vector<UserDatum>> opWrapper;
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// Add custom input
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const auto workerInputOnNewThread = false;
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opWrapper.setWorkerInput(wUserInput, workerInputOnNewThread);
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// Add custom processing
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const auto workerProcessingOnNewThread = false;
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opWrapper.setWorkerPostProcessing(wUserPostProcessing, workerProcessingOnNewThread);
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// Add custom output
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const auto workerOutputOnNewThread = true;
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opWrapper.setWorkerOutput(wUserOutput, workerOutputOnNewThread);
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// Configure OpenPose
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const bool displayGui = false;
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const bool guiVerbose = false;
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const bool fullScreen = false;
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const op::WrapperStructPose wrapperStructPose{netInputSize, outputSize, keypointScale, FLAGS_num_gpu, FLAGS_num_gpu_start,
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FLAGS_num_scales, (float)FLAGS_scale_gap, gflagToRenderMode(FLAGS_render_pose), poseModel,
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!FLAGS_disable_blending, (float)FLAGS_alpha_pose, (float)FLAGS_alpha_heatmap,
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FLAGS_part_to_show, FLAGS_model_folder, heatMapTypes, heatMapScale};
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// Face configuration (use op::WrapperStructFace{} to disable it)
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const op::WrapperStructFace wrapperStructFace{FLAGS_face, faceNetInputSize, gflagToRenderMode(FLAGS_render_face, FLAGS_render_pose),
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(float)FLAGS_alpha_face, (float)FLAGS_alpha_heatmap_face};
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// Hand configuration (use op::WrapperStructHand{} to disable it)
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const op::experimental::WrapperStructHand wrapperStructHand{false};
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// Consumer (comment or use default argument to disable any output)
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const op::WrapperStructOutput wrapperStructOutput{displayGui, guiVerbose, fullScreen, FLAGS_write_keypoint,
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op::stringToDataFormat(FLAGS_write_keypoint_format), FLAGS_write_keypoint_json,
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FLAGS_write_coco_json, FLAGS_write_images, FLAGS_write_images_format, FLAGS_write_video,
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FLAGS_write_heatmaps, FLAGS_write_heatmaps_format};
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// Configure wrapper
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opWrapper.configure(wrapperStructPose, wrapperStructFace, wrapperStructHand, op::WrapperStructInput{}, wrapperStructOutput);
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// Set to single-thread running (e.g. for debugging purposes)
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// opWrapper.disableMultiThreading();
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op::log("Starting thread(s)", op::Priority::Max);
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// Two different ways of running the program on multithread environment
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// // Option a) Recommended - Also using the main thread (this thread) for processing (it saves 1 thread)
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// // Start, run & stop threads
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opWrapper.exec(); // It blocks this thread until all threads have finished
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// Option b) Keeping this thread free in case you want to do something else meanwhile, e.g. profiling the GPU memory
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// // VERY IMPORTANT NOTE: if OpenCV is compiled with Qt support, this option will not work. Qt needs the main thread to
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// // plot visual results, so the final GUI (which uses OpenCV) would return an exception similar to:
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// // `QMetaMethod::invoke: Unable to invoke methods with return values in queued connections`
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// // Start threads
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// opWrapper.start();
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// // Profile used GPU memory
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// // 1: wait ~10sec so the memory has been totally loaded on GPU
|
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// // 2: profile the GPU memory
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// std::this_thread::sleep_for(std::chrono::milliseconds{1000});
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// op::log("Random task here...", op::Priority::Max);
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// // Keep program alive while running threads
|
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// while (opWrapper.isRunning())
|
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// std::this_thread::sleep_for(std::chrono::milliseconds{33});
|
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// // Stop and join threads
|
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// op::log("Stopping thread(s)", op::Priority::Max);
|
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// opWrapper.stop();
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|
|
// Measuring total time
|
|
const auto now = std::chrono::high_resolution_clock::now();
|
|
const auto totalTimeSec = (double)std::chrono::duration_cast<std::chrono::nanoseconds>(now-timerBegin).count() * 1e-9;
|
|
const auto message = "Real-time pose estimation demo successfully finished. Total time: " + std::to_string(totalTimeSec) + " seconds.";
|
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op::log(message, op::Priority::Max);
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|
|
|
return 0;
|
|
}
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|
|
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int main(int argc, char *argv[])
|
|
{
|
|
// Initializing google logging (Caffe uses it for logging)
|
|
google::InitGoogleLogging("openPoseTutorialWrapper2");
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|
|
|
// Parsing command line flags
|
|
gflags::ParseCommandLineFlags(&argc, &argv, true);
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|
|
|
// Running openPoseTutorialWrapper2
|
|
return openPoseTutorialWrapper2();
|
|
}
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