Skip to content

Latest commit

 

History

History
205 lines (172 loc) · 8.42 KB

quick_start.md

File metadata and controls

205 lines (172 loc) · 8.42 KB
Raw

OpenPose - Quick Start

Contents

  1. Quick Start
    1. Running on Video
    2. Running on Webcam
    3. Running on Images
    4. Maximum Accuracy Configuration
    5. 3-D Reconstruction
    6. Tracking
  2. Expected Visual Results

Quick Start

Check that the library is working properly by running any of the following commands. Make sure that you are in the root directory of the project (i.e. in the OpenPose folder, not inside build/ nor windows/ nor bin/). In addition, examples/media/video.avi and examples/media do exist, no need to change the paths.

Running on Video

# Ubuntu and Mac
./build/examples/openpose/openpose.bin --video examples/media/video.avi
# With face and hands
./build/examples/openpose/openpose.bin --video examples/media/video.avi --face --hand

:: Windows - Portable Demo
bin\OpenPoseDemo.exe --video examples\media\video.avi
:: With face and hands
bin\OpenPoseDemo.exe --video examples\media\video.avi --face --hand

:: Windows - Library - Assuming you copied the DLLs following doc/installation.md#windows
build\x64\Release\OpenPoseDemo.exe --video examples\media\video.avi
:: With face and hands
build\x64\Release\OpenPoseDemo.exe --video examples\media\video.avi --face --hand

Running on Webcam

# Ubuntu and Mac
./build/examples/openpose/openpose.bin
# With face and hands
./build/examples/openpose/openpose.bin --face --hand

:: Windows - Portable Demo
bin\OpenPoseDemo.exe
:: With face and hands
bin\OpenPoseDemo.exe --face --hand

:: Windows - Library - Assuming you copied the DLLs following doc/installation.md#windows
build\x64\Release\OpenPoseDemo.exe
:: With face and hands
build\x64\Release\OpenPoseDemo.exe --face --hand

Running on Images

# Ubuntu and Mac
./build/examples/openpose/openpose.bin --image_dir examples/media/
# With face and hands
./build/examples/openpose/openpose.bin --image_dir examples/media/ --face --hand

:: Windows - Portable Demo
bin\OpenPoseDemo.exe --image_dir examples\media\
:: With face and hands
bin\OpenPoseDemo.exe --image_dir examples\media\ --face --hand

:: Windows - Library - Assuming you copied the DLLs following doc/installation.md#windows
build\x64\Release\OpenPoseDemo.exe --image_dir examples\media\
:: With face and hands
build\x64\Release\OpenPoseDemo.exe --image_dir examples\media\ --face --hand

Maximum Accuracy Configuration

This command provides the most accurate results we have been able to achieve for body, hand and face keypoint detection. However, this command will need ~10.5 GB of GPU memory (6.7 GB for COCO model) and runs at ~2 FPS on a Titan X for the body-foot model (1 FPS for COCO).

  • Note 1: Increasing --net_resolution will highly reduce the frame rate and increase latency, while it might increase the accuracy. However, this accuracy increase is not guaranteed in all scenarios, required a more detailed analysis for each particular scenario. E.g., it will work better for images with very small people, but usually worse for people taking a big ratio of the image. Thus, we recommend to follow the commands below for maximum accuracy in most cases for both big and small-size people.
  • Note 2: Do not use this configuration for MPII model, its accuracy might be harmed by this multi-scale setting. This configuration is optimal only for COCO and COCO-extended (e.g., the default BODY_25) models.
# Ubuntu and Mac: Body
./build/examples/openpose/openpose.bin --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25
# Ubuntu and Mac: Body + Hand + Face
./build/examples/openpose/openpose.bin --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25 --hand --hand_scale_number 6 --hand_scale_range 0.4 --face

:: Windows - Portable Demo: Body
bin\OpenPoseDemo.exe --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25
:: Windows - Portable Demo: Body + Hand + Face
bin\OpenPoseDemo.exe --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25 --hand --hand_scale_number 6 --hand_scale_range 0.4 --face

:: Windows - Library - Assuming you copied the DLLs following doc/installation.md#windows: Body
build\x64\Release\OpenPoseDemo.exe --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25
:: Windows - Library - Assuming you copied the DLLs following doc/installation.md#windows: Body + Hand + Face
build\x64\Release\OpenPoseDemo.exe --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25 --hand --hand_scale_number 6 --hand_scale_range 0.4 --face

3-D Reconstruction

  1. Real-time demo
# Ubuntu and Mac
./build/examples/openpose/openpose.bin --flir_camera --3d --number_people_max 1
# With face and hands
./build/examples/openpose/openpose.bin --flir_camera --3d --number_people_max 1 --face --hand

:: Windows - Portable Demo
bin\OpenPoseDemo.exe --flir_camera --3d --number_people_max 1
:: With face and hands
bin\OpenPoseDemo.exe --flir_camera --3d --number_people_max 1 --face --hand

:: Windows - Library - Assuming you copied the DLLs following doc/installation.md#windows
build\x64\Release\OpenPoseDemo.exe --flir_camera --3d --number_people_max 1
:: With face and hands
build\x64\Release\OpenPoseDemo.exe --flir_camera --3d --number_people_max 1 --face --hand
  1. Saving 3-D keypoints
# Ubuntu and Mac (same flags for Windows version)
./build/examples/openpose/openpose.bin --flir_camera --3d --number_people_max 1 --write_json output_folder_path/
  1. Fast stereo camera image saving (without keypoint detection) for later post-processing
# Ubuntu and Mac (same flags for Windows version)
# Saving video
# Note: saving in PNG rather than JPG will improve image quality, but slow down FPS (depending on hard disk writing speed and camera number)
./build/examples/openpose/openpose.bin --flir_camera --num_gpu 0 --write_video output_folder_path/video.avi --camera_fps 5
# Saving images
# Note: saving in PNG rather than JPG will improve image quality, but slow down FPS (depending on hard disk writing speed and camera number)
./build/examples/openpose/openpose.bin --flir_camera --num_gpu 0 --write_images output_folder_path/ --write_images_format jpg
  1. Reading and processing previouly saved stereo camera images
# Ubuntu and Mac (same flags for Windows version)
# Optionally add `--face` and/or `--hand` to include face and/or hands
# Assuming 3 cameras
# Note: We highly recommend to reduce `--output_resolution`. E.g. for 3 cameras recording at 1920x1080, the resulting image is (3x1920)x1080, so we recommend e.g. 640x360 (x3 reduction).
# Video
./build/examples/openpose/openpose.bin --video output_folder_path/video.avi --3d_views 3 --3d --number_people_max 1 --output_resolution {desired_output_resolution}
# Images
./build/examples/openpose/openpose.bin --image_dir output_folder_path/ --3d_views 3 --3d --number_people_max 1 --output_resolution {desired_output_resolution}
  1. Reconstruction when at least n visible views
# Ubuntu and Mac (same flags for Windows version)
# Assuming >=2 cameras and reconstruction when at least 2 visible views
./build/examples/openpose/openpose.bin --flir_camera --3d --number_people_max 1 --3d_min_views 2 --output_resolution {desired_output_resolution}

Tracking

  1. Runtime huge speed up by reducing the accuracy:
# Using OpenPose 1 frame, tracking the following e.g., 5 frames
./build/examples/openpose/openpose.bin --tracking 5 --number_people_max 1
  1. Runtime speed up while keeping most of the accuracy:
:: Using OpenPose 1 frame and tracking another frame
./build/examples/openpose/openpose.bin --tracking 1 --number_people_max 1
  1. Visual smoothness:
# Running both OpenPose and tracking on each frame. Note: There is no speed up/slow down
./build/examples/openpose/openpose.bin --tracking 0 --number_people_max 1

Expected Visual Results

The visual GUI should show the original image with the poses blended on it, similarly to the pose of this gif:

If you choose to visualize a body part or a PAF (Part Affinity Field) heat map with the command option --part_to_show, the result should be similar to one of the following images: