74 lines
2.0 KiB
Markdown
74 lines
2.0 KiB
Markdown
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<!--
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* @Date: 2021-06-04 15:56:55
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* @Author: Qing Shuai
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* @LastEditors: Qing Shuai
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* @LastEditTime: 2021-06-04 17:11:48
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* @FilePath: /EasyMocapRelease/doc/realtime_visualization.md
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-->
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# EasyMoCap -> Real-time Visualization
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We are the first one to release a real-time visualization tool for both skeletons and SMPL/SMPL+H/SMPL-X/MANO models.
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## Install
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Please install `EasyMocap` first. This part requires `Open3D==0.9.0`:
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```bash
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python3 -m pip install open3d==0.9.0
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```
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## Open the server
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Before any visualization, you should run a server:
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```bash
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python3 apps/vis/vis_server.py --cfg config/vis/o3d_scene.yml host <your_ip_address> port <set_a_port>
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```
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This step will open the visualization window:
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You can alternate the viewpoints free. The configuration file `config/vis/o3d_scene.yml` defines the scene and other properties. In the default setting, we define the xyz-axis in the origin, the bounding box of the scene and a chessboard in the ground.
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## Send the data
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If you are success to open the server, you can visualize your 3D data anywhere. We provide an example code:
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```bash
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python3 apps/vis/vis_client.py --path <path/to/your/keypoints3d> --host <previous_ip_address> --port <previous_port>
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```
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Take the `zju-ls-feng` results as example, you can show the skeleton in the main window:
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## Embed this feature to your code
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To add this visualization to your other code, you can follow these steps:
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```bash
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# 1. import the base client
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from easymocap.socket.base_client import BaseSocketClient
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# 2. set the ip address and port
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client = BaseSocketClient(host, port)
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# 3. send the data
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client.send(data)
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```
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The format of data is:
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```python
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data = [
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{
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'id': 0,
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'keypoints3d': numpy.ndarray # (nJoints, 4) , (x, y, z, c) for each joint
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},
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{
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'id': 1,
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'keypoints3d': numpy.ndarray # (nJoints, 4)
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}
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]
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```
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## Define your scene
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In the configuration file, we main define the `body_model` and `scene`. You can replace them for your data.
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