@@ -11,7 +11,7 @@ In order to learn how to use it, run `./build/examples/openpose/openpose.bin --h
Each flag is divided into flag name, default value, and description.
1. Debugging
- 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_int32(logging_level, 4, "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.");
2. Producer
- DEFINE_int32(camera, 0, "The camera index for cv::VideoCapture. Integer in the range [0, 9].");
- DEFINE_string(camera_resolution, "1280x720", "Size of the camera frames to ask for.");
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@@ -42,12 +42,13 @@ Each flag is divided into flag name, default value, and description.
- DEFINE_string(face_net_resolution, "368x368", "Multiples of 16. 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.");
6. OpenPose Hand
- DEFINE_bool(hand, false, "Enables hand keypoint detection. It will share some parameters from the body pose, e.g. `model_folder`.");
- DEFINE_string(hand_net_resolution, "368x368", "Multiples of 16. Analogous to `net_resolution` but applied to the hand keypoint detector. 320x320 usually works fine while giving a substantial speed up when multiple hands on the image.");
- DEFINE_string(hand_net_resolution, "368x368", "Multiples of 16. Analogous to `net_resolution` but applied to the hand keypoint detector. 320x320 usually works fine while giving a substantial speed up when multiple hands on the image.");t_resolution` but applied to the hand keypoint detector.");
- DEFINE_int32(hand_detection_mode, -1, "Set to 0 to perform 1-time keypoint detection (fastest), 1 for iterative detection (recommended for images and fast videos, slow method), 2 for tracking (recommended for webcam if the frame rate is >10 FPS per GPU used and for video, in practice as fast as 1-time detection), 3 for both iterative and tracking (recommended for webcam if the resulting frame rate is still >10 FPS and for video, ideally best result but slower), or -1 (default) for automatic selection (fast method for webcam, tracking for video and iterative for images).");
7. OpenPose Rendering
- DEFINE_int32(part_to_show, 0, "Part to show from the start.");
- DEFINE_bool(disable_blending, false, "If blending is enabled, it will merge the results with the original frame. If disabled, it will only display the results.");
8. OpenPose Rendering Pose
- DEFINE_int32(render_pose, 1, "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_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.");
9. OpenPose Rendering Face
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@@ -109,15 +110,63 @@ Please, in order to check all the real time pose demo options and their details,
## Hands
Very important note, use `hand_detection_mode` accordingly.
The following example runs the demo video `video.avi`, renders image frames on `output/result.avi`, and outputs JSON files in `output/`. It parallelizes over 2 GPUs, GPUs 1 and 2. Note that it will skip GPU 0:
## Basic Output Saving
The following example runs the demo video `video.avi`, renders image frames on `output/result.avi`, and outputs JSON files in `output/`. It parallelizes over 2 GPUs, GPUs 1 and 2 (note that it will skip GPU 0):
There are 2 alternatives to save the **(x,y,score) body part locations**. The `write_keypoint` flag uses the OpenCV cv::FileStorage default formats (JSON, XML and YML). However, the JSON format is only available after OpenCV 3.0. Hence, `write_keypoint_json` saves the people pose data using a custom JSON writer. For the latter, each JSON file has a `people` array of objects, where each object has an array `body_parts` containing the body part locations and detection confidence formatted as `x1,y1,c1,x2,y2,c2,...`. The coordinates `x` and `y` can be normalized to the range [0,1], [-1,1], [0, source size], [0, output size], etc., depending on the flag `keypoint_scale`. In addition, `c` is the confidence in the range [0,1].
There are 2 alternatives to save the **(x,y,score) body part locations**. The `write_keypoint` flag uses the OpenCV cv::FileStorage default formats (JSON, XML and YML). However, the JSON format is only available after OpenCV 3.0. Hence, `write_keypoint_json` saves the people pose data using a custom JSON writer. For the latter, each JSON file has a `people` array of objects, where each object has an array `pose_keypoints` containing the body part locations and detection confidence formatted as `x1,y1,c1,x2,y2,c2,...`. The coordinates `x` and `y` can be normalized to the range [0,1], [-1,1], [0, source size], [0, output size], etc., depending on the flag `keypoint_scale`. In addition, `c` is the confidence in the range [0,1].
