// ------------------------- OpenPose Library Tutorial - Real Time Pose Estimation ------------------------- // If the user wants to learn to use the OpenPose library, we highly recommend to start with the `examples/tutorial_*/` folders. // This example summarizes all the funcitonality of the OpenPose library: // 1. Read folder of images / video / webcam (`producer` module) // 2. Extract and render body keypoint / heatmap / PAF of that image (`pose` module) // 3. Extract and render face keypoint / heatmap / PAF of that image (`face` module) // 4. Save the results on disk (`filestream` module) // 5. Display the rendered pose (`gui` module) // Everything in a multi-thread scenario (`thread` module) // Points 2 to 5 are included in the `wrapper` module // In addition to the previous OpenPose modules, we also need to use: // 1. `core` module: // For the Array class that the `pose` module needs // For the Datum struct that the `thread` module sends between the queues // 2. `utilities` module: for the error & logging functions, i.e. op::error & op::log respectively // This file should only be used for the user to take specific examples. // C++ std library dependencies #include // `std::chrono::` functions and classes, e.g. std::chrono::milliseconds #include // std::this_thread // Other 3rdparty dependencies // GFlags: DEFINE_bool, _int32, _int64, _uint64, _double, _string #include // Allow Google Flags in Ubuntu 14 #ifndef GFLAGS_GFLAGS_H_ namespace gflags = google; #endif // OpenPose dependencies #include // See all the available parameter options withe the `--help` flag. E.g. `build/examples/openpose/openpose.bin --help` // Note: This command will show you flags for other unnecessary 3rdparty files. Check only the flags for the OpenPose // executable. E.g. for `openpose.bin`, look for `Flags from examples/openpose/openpose.cpp:`. // Debugging/Other DEFINE_int32(logging_level, 3, "The logging level. Integer in the range [0, 255]. 0 will output any log() message, while" " 255 will not output any. Current OpenPose library messages are in the range 0-4: 1 for" " low priority messages and 4 for important ones."); DEFINE_bool(disable_multi_thread, false, "It would slightly reduce the frame rate in order to highly reduce the lag. Mainly useful" " for 1) Cases where it is needed a low latency (e.g. webcam in real-time scenarios with" " low-range GPU devices); and 2) Debugging OpenPose when it is crashing to locate the" " error."); DEFINE_int32(profile_speed, 1000, "If PROFILER_ENABLED was set in CMake or Makefile.config files, OpenPose will show some" " runtime statistics at this frame number."); // Producer DEFINE_int32(camera, -1, "The camera index for cv::VideoCapture. Integer in the range [0, 9]. Select a negative" " number (by default), to auto-detect and open the first available camera."); DEFINE_string(camera_resolution, "1280x720", "Size of the camera frames to ask for."); DEFINE_double(camera_fps, 30.0, "Frame rate for the webcam (only used when saving video from webcam). Set this value to the" " minimum value between the OpenPose displayed speed and the webcam real frame rate."); DEFINE_string(video, "", "Use a video file instead of the camera. Use `examples/media/video.avi` for our default" " example video."); DEFINE_string(image_dir, "", "Process a directory of images. Use `examples/media/` for our default example folder with 20" " images. Read all standard formats (jpg, png, bmp, etc.)."); DEFINE_string(ip_camera, "", "String with the IP camera URL. It supports protocols like RTSP and HTTP."); DEFINE_uint64(frame_first, 0, "Start on desired frame number. Indexes are 0-based, i.e. the first frame has index 0."); DEFINE_uint64(frame_last, -1, "Finish on desired frame number. Select -1 to disable. Indexes are 0-based, e.g. if set to" " 10, it will process 11 frames (0-10)."); DEFINE_bool(frame_flip, false, "Flip/mirror each frame (e.g. for real time webcam demonstrations)."); DEFINE_int32(frame_rotate, 0, "Rotate each frame, 4 possible values: 0, 90, 180, 270."); DEFINE_bool(frames_repeat, false, "Repeat frames when finished."); DEFINE_bool(process_real_time, false, "Enable to keep the original source frame rate (e.g. for video). If the processing time is" " too long, it will skip frames. If it is too fast, it will slow it down."); // OpenPose DEFINE_string(model_folder, "models/", "Folder path (absolute or relative) where the models (pose, face, ...) are located."); DEFINE_string(output_resolution, "-1x-1", "The image resolution (display and output). Use \"-1x-1\" to force the program to use the" " input image resolution."); DEFINE_int32(num_gpu, -1, "The number of GPU devices to use. If negative, it will use all the available GPUs in your" " machine."); DEFINE_int32(num_gpu_start, 0, "GPU device start number."); 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)" " coordinates that will be saved with the `write_keypoint` & `write_keypoint_json` flags." " Select `0` to scale it to the original source resolution, `1`to scale it to the net output" " size (set with `net_resolution`), `2` to scale it to the final output size (set with" " `resolution`), `3` to scale it in the range [0,1], and 4 for range [-1,1]. Non related" " with `scale_number` and `scale_gap`."); DEFINE_bool(identification, false, "Whether to enable people identification across frames. Not available yet, coming soon."); // OpenPose Body Pose DEFINE_bool(body_disable, false, "Disable body keypoint detection. Option only possible for faster (but less accurate) face" " keypoint detection."); DEFINE_string(model_pose, "COCO", "Model to be used. E.g. `COCO` (18 keypoints), `MPI` (15 keypoints, ~10% faster), " "`MPI_4_layers` (15 keypoints, even faster but less accurate)."); DEFINE_string(net_resolution, "-1x368", "Multiples of 16. If it is increased, the accuracy potentially increases. If it is" " decreased, the speed increases. For maximum speed-accuracy balance, it should keep the" " closest aspect ratio possible to the images or videos to be processed. Using `-1` in" " any of the dimensions, OP will choose the optimal aspect ratio depending on the user's" " input value. E.g. the default `-1x368` is equivalent to `656x368` in 16:9 resolutions," " e.g. full HD (1980x1080) and HD (1280x720) resolutions."); DEFINE_int32(scale_number, 1, "Number of scales to average."); DEFINE_double(scale_gap, 0.3, "Scale gap between scales. No effect unless scale_number > 1. Initial scale is always 1." " If you want to change the initial scale, you actually want to multiply the" " `net_resolution` by your desired initial scale."); // OpenPose Body Pose Heatmaps and Part Candidates DEFINE_bool(heatmaps_add_parts, false, "If true, it will fill op::Datum::poseHeatMaps array with the body part heatmaps, and" " analogously face & hand heatmaps to op::Datum::faceHeatMaps & op::Datum::handHeatMaps." " If more than one `add_heatmaps_X` flag is enabled, it will place then in sequential" " memory order: body parts + bkg + PAFs. It will follow the order on" " POSE_BODY_PART_MAPPING in `src/openpose/pose/poseParameters.cpp`. Program speed will" " considerably decrease. Not required for OpenPose, enable it only if you intend to" " explicitly use this information later."); DEFINE_bool(heatmaps_add_bkg, false, "Same functionality as `add_heatmaps_parts`, but adding the heatmap corresponding to" " background."); DEFINE_bool(heatmaps_add_PAFs, false, "Same functionality as `add_heatmaps_parts`, but adding the PAFs."); DEFINE_int32(heatmaps_scale, 2, "Set 0 to scale op::Datum::poseHeatMaps in the range [-1,1], 1 for [0,1]; 2 for integer" " rounded [0,255]; and 3 for no scaling."); DEFINE_bool(part_candidates, false, "Also enable `write_json` in order to save this information. If true, it will fill the" " op::Datum::poseCandidates array with the body part candidates. Candidates refer to all" " the detected body parts, before being assembled into people. Note that the number of" " candidates is equal or higher than the number of final body parts (i.e. after being" " assembled into people). The empty body parts are filled with 0s. Program speed will" " slightly decrease. Not required for OpenPose, enable it only if you intend to explicitly" " use this information."); // OpenPose Face DEFINE_bool(face, false, "Enables face keypoint detection. It will share some parameters from the body pose, e.g." " `model_folder`. Note that this will considerable slow down the performance and increse" " the required GPU memory. In addition, the greater number of people on the image, the" " slower OpenPose will be."); DEFINE_string(face_net_resolution, "368x368", "Multiples of 16 and squared. Analogous to `net_resolution` but applied to the face keypoint" " detector. 320x320 usually works fine while giving a substantial speed up when multiple" " faces on the image."); // OpenPose Hand DEFINE_bool(hand, false, "Enables hand keypoint detection. It will share some parameters from the body pose, e.g." " `model_folder`. Analogously to `--face`, it will also slow down the performance, increase" " the required GPU memory and its speed depends on the number of people."); DEFINE_string(hand_net_resolution, "368x368", "Multiples of 16 and squared. Analogous to `net_resolution` but applied to the hand keypoint" " detector."); DEFINE_int32(hand_scale_number, 1, "Analogous to `scale_number` but applied to the hand keypoint detector. Our best results" " were found with `hand_scale_number` = 6 and `hand_scale_range` = 0.4"); DEFINE_double(hand_scale_range, 0.4, "Analogous purpose than `scale_gap` but applied to the hand keypoint detector. Total range" " between smallest and biggest scale. The scales will be centered in ratio 1. E.g. if" " scaleRange = 0.4 and scalesNumber = 2, then there will be 2 scales, 0.8 and 1.2."); DEFINE_bool(hand_tracking, false, "Adding hand tracking might improve hand keypoints detection for webcam (if the frame rate" " is high enough, i.e. >7 FPS per GPU) and video. This is not person ID tracking, it" " simply looks for hands in positions at which hands were located in previous frames, but" " it does not guarantee the same person ID among frames"); // OpenPose Rendering DEFINE_int32(part_to_show, 0, "Prediction channel to visualize (default: 0). 0 for all the body parts, 1-18 for each body" " part heat map, 19 for the background heat map, 20 for all the body part heat maps" " together, 21 for all the PAFs, 22-40 for each body part pair PAF"); DEFINE_bool(disable_blending, false, "If enabled, it will render the results (keypoint skeletons or heatmaps) on a black" " background, instead of being rendered into the original image. Related: `part_to_show`," " `alpha_pose`, and `alpha_pose`."); // OpenPose Rendering Pose DEFINE_double(render_threshold, 0.05, "Only estimated keypoints whose score confidences are higher than this threshold will be" " rendered. Generally, a high threshold (> 0.5) will only render very clear body parts;" " while small thresholds (~0.1) will also output guessed and occluded keypoints, but also" " more false positives (i.e. wrong detections)."); DEFINE_int32(render_pose, 2, "Set to 0 for no rendering, 1 for CPU rendering (slightly faster), and 2 for GPU rendering" " (slower but greater functionality, e.g. `alpha_X` flags). If rendering is enabled, it will" " render both `outputData` and `cvOutputData` with the original image and desired body part" " to be shown (i.e. keypoints, heat maps or PAFs)."); DEFINE_double(alpha_pose, 0.6, "Blending factor (range 0-1) for the body part rendering. 1 will show it completely, 0 will" " hide it. Only valid for GPU rendering."); DEFINE_double(alpha_heatmap, 0.7, "Blending factor (range 0-1) between heatmap and original frame. 1 will only show the" " heatmap, 0 will only show the frame. Only valid for GPU rendering."); // OpenPose Rendering Face DEFINE_double(face_render_threshold, 0.4, "Analogous to `render_threshold`, but applied to the face keypoints."); DEFINE_int32(face_render, -1, "Analogous to `render_pose` but applied to the face. Extra option: -1 to use the same" " configuration that `render_pose` is using."); DEFINE_double(face_alpha_pose, 0.6, "Analogous to `alpha_pose` but applied to face."); DEFINE_double(face_alpha_heatmap, 0.7, "Analogous to `alpha_heatmap` but applied to face."); // OpenPose Rendering Hand DEFINE_double(hand_render_threshold, 0.2, "Analogous to `render_threshold`, but applied to the hand keypoints."); DEFINE_int32(hand_render, -1, "Analogous to `render_pose` but applied to the hand. Extra option: -1 to use the same" " configuration that `render_pose` is using."); DEFINE_double(hand_alpha_pose, 0.6, "Analogous to `alpha_pose` but applied to hand."); DEFINE_double(hand_alpha_heatmap, 0.7, "Analogous to `alpha_heatmap` but applied to hand."); // Display DEFINE_bool(fullscreen, false, "Run in full-screen mode (press f during runtime to toggle)."); DEFINE_bool(no_gui_verbose, false, "Do not write text on output images on GUI (e.g. number of current frame and people). It" " does not affect the pose rendering."); DEFINE_bool(no_display, false, "Do not open a display window. Useful if there is no X server and/or to slightly speed up" " the processing if visual output is not required."); // Result Saving DEFINE_string(write_images, "", "Directory to write rendered frames in `write_images_format` image format."); DEFINE_string(write_images_format, "png", "File extension and format for `write_images`, e.g. png, jpg or bmp. Check the OpenCV" " function cv::imwrite for all compatible extensions."); DEFINE_string(write_video, "", "Full file path to write rendered frames in motion JPEG video format. It might fail if the" " final path does not finish in `.avi`. It internally uses cv::VideoWriter."); DEFINE_string(write_json, "", "Directory to write OpenPose output in JSON format. It includes body, hand, and face pose" " keypoints, as well as pose candidates (if `--part_candidates` enabled)."); DEFINE_string(write_coco_json, "", "Full file path to write people pose data with JSON COCO validation format."); DEFINE_string(write_heatmaps, "", "Directory to write body pose heatmaps in PNG format. At least 1 `add_heatmaps_X` flag" " must be enabled."); DEFINE_string(write_heatmaps_format, "png", "File extension and format for `write_heatmaps`, analogous to `write_images_format`." " For lossless compression, recommended `png` for integer `heatmaps_scale` and `float` for" " floating values."); DEFINE_string(write_keypoint, "", "(Deprecated, use `write_json`) Directory to write the people pose keypoint data. Set format" " with `write_keypoint_format`."); DEFINE_string(write_keypoint_format, "yml", "(Deprecated, use `write_json`) File extension and format for `write_keypoint`: json, xml," " yaml & yml. Json not available for OpenCV < 3.0, use `write_keypoint_json` instead."); DEFINE_string(write_keypoint_json, "", "(Deprecated, use `write_json`) Directory to write people pose data in JSON format," " compatible with any OpenCV version."); int openPoseDemo() { // logging_level op::check(0 <= FLAGS_logging_level && FLAGS_logging_level <= 255, "Wrong logging_level value.", __LINE__, __FUNCTION__, __FILE__); op::ConfigureLog::setPriorityThreshold((op::Priority)FLAGS_logging_level); op::Profiler::setDefaultX(FLAGS_profile_speed); // // For debugging // // Print all logging messages // op::ConfigureLog::setPriorityThreshold(op::Priority::None); // // Print out speed values faster // op::Profiler::setDefaultX(100); op::log("Starting pose estimation demo.", op::Priority::High); const auto timerBegin = std::chrono::high_resolution_clock::now(); // Applying user defined configuration - Google flags to program variables // outputSize const auto outputSize = op::flagsToPoint(FLAGS_output_resolution, "-1x-1"); // netInputSize const auto netInputSize = op::flagsToPoint(FLAGS_net_resolution, "-1x368"); // faceNetInputSize const auto faceNetInputSize = op::flagsToPoint(FLAGS_face_net_resolution, "368x368 (multiples of 16)"); // handNetInputSize const auto handNetInputSize = op::flagsToPoint(FLAGS_hand_net_resolution, "368x368 (multiples of 16)"); // producerType const auto producerSharedPtr = op::flagsToProducer(FLAGS_image_dir, FLAGS_video, FLAGS_ip_camera, FLAGS_camera, FLAGS_camera_resolution, FLAGS_camera_fps); // poseModel const auto poseModel = op::flagsToPoseModel(FLAGS_model_pose); // JSON saving const auto writeJson = (!FLAGS_write_json.empty() ? FLAGS_write_json : FLAGS_write_keypoint_json); if (!FLAGS_write_keypoint.empty() || !FLAGS_write_keypoint_json.empty()) op::log("Flags `write_keypoint` and `write_keypoint_json` are deprecated and will eventually be removed." " Please, use `write_json` instead.", op::Priority::Max); // keypointScale const auto keypointScale = op::flagsToScaleMode(FLAGS_keypoint_scale); // heatmaps to add const auto heatMapTypes = op::flagsToHeatMaps(FLAGS_heatmaps_add_parts, FLAGS_heatmaps_add_bkg, FLAGS_heatmaps_add_PAFs); const auto heatMapScale = op::flagsToHeatMapScaleMode(FLAGS_heatmaps_scale); // Enabling Google Logging const bool enableGoogleLogging = true; // Logging op::log("", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__); // OpenPose wrapper op::log("Configuring OpenPose wrapper.", op::Priority::Low, __LINE__, __FUNCTION__, __FILE__); op::Wrapper> opWrapper; // Pose configuration (use WrapperStructPose{} for default and recommended configuration) const op::WrapperStructPose wrapperStructPose{!FLAGS_body_disable, netInputSize, outputSize, keypointScale, FLAGS_num_gpu, FLAGS_num_gpu_start, FLAGS_scale_number, (float)FLAGS_scale_gap, op::flagsToRenderMode(FLAGS_render_pose), poseModel, !FLAGS_disable_blending, (float)FLAGS_alpha_pose, (float)FLAGS_alpha_heatmap, FLAGS_part_to_show, FLAGS_model_folder, heatMapTypes, heatMapScale, FLAGS_part_candidates, (float)FLAGS_render_threshold, enableGoogleLogging, FLAGS_identification}; // Face configuration (use op::WrapperStructFace{} to disable it) const op::WrapperStructFace wrapperStructFace{FLAGS_face, faceNetInputSize, op::flagsToRenderMode(FLAGS_face_render, FLAGS_render_pose), (float)FLAGS_face_alpha_pose, (float)FLAGS_face_alpha_heatmap, (float)FLAGS_face_render_threshold}; // Hand configuration (use op::WrapperStructHand{} to disable it) const op::WrapperStructHand wrapperStructHand{FLAGS_hand, handNetInputSize, FLAGS_hand_scale_number, (float)FLAGS_hand_scale_range, FLAGS_hand_tracking, op::flagsToRenderMode(FLAGS_hand_render, FLAGS_render_pose), (float)FLAGS_hand_alpha_pose, (float)FLAGS_hand_alpha_heatmap, (float)FLAGS_hand_render_threshold}; // Producer (use default to disable any input) const op::WrapperStructInput wrapperStructInput{producerSharedPtr, FLAGS_frame_first, FLAGS_frame_last, FLAGS_process_real_time, FLAGS_frame_flip, FLAGS_frame_rotate, FLAGS_frames_repeat}; // Consumer (comment or use default argument to disable any output) const op::WrapperStructOutput wrapperStructOutput{!FLAGS_no_display, !FLAGS_no_gui_verbose, FLAGS_fullscreen, FLAGS_write_keypoint, op::stringToDataFormat(FLAGS_write_keypoint_format), writeJson, FLAGS_write_coco_json, FLAGS_write_images, FLAGS_write_images_format, FLAGS_write_video, FLAGS_write_heatmaps, FLAGS_write_heatmaps_format}; // Configure wrapper opWrapper.configure(wrapperStructPose, wrapperStructFace, wrapperStructHand, wrapperStructInput, wrapperStructOutput); // Set to single-thread running (to debug and/or reduce latency) if (FLAGS_disable_multi_thread) opWrapper.disableMultiThreading(); // Start processing // Two different ways of running the program on multithread environment op::log("Starting thread(s)", op::Priority::High); // Option a) Recommended - Also using the main thread (this thread) for processing (it saves 1 thread) // Start, run & stop threads opWrapper.exec(); // It blocks this thread until all threads have finished // // Option b) Keeping this thread free in case you want to do something else meanwhile, e.g. profiling the GPU // memory // // VERY IMPORTANT NOTE: if OpenCV is compiled with Qt support, this option will not work. Qt needs the main // // thread to plot visual results, so the final GUI (which uses OpenCV) would return an exception similar to: // // `QMetaMethod::invoke: Unable to invoke methods with return values in queued connections` // // Start threads // opWrapper.start(); // // Profile used GPU memory // // 1: wait ~10sec so the memory has been totally loaded on GPU // // 2: profile the GPU memory // const auto sleepTimeMs = 10; // for (auto i = 0 ; i < 10000/sleepTimeMs && opWrapper.isRunning() ; i++) // std::this_thread::sleep_for(std::chrono::milliseconds{sleepTimeMs}); // op::Profiler::profileGpuMemory(__LINE__, __FUNCTION__, __FILE__); // // Keep program alive while running threads // while (opWrapper.isRunning()) // std::this_thread::sleep_for(std::chrono::milliseconds{sleepTimeMs}); // // Stop and join threads // op::log("Stopping thread(s)", op::Priority::High); // opWrapper.stop(); // Measuring total time const auto now = std::chrono::high_resolution_clock::now(); const auto totalTimeSec = (double)std::chrono::duration_cast(now-timerBegin).count() * 1e-9; const auto message = "Real-time pose estimation demo successfully finished. Total time: " + std::to_string(totalTimeSec) + " seconds."; op::log(message, op::Priority::High); return 0; } int main(int argc, char *argv[]) { // Parsing command line flags gflags::ParseCommandLineFlags(&argc, &argv, true); // Running openPoseDemo return openPoseDemo(); }