[update] update README for two types of retargeting

README.md

@@ -24,51 +24,8 @@ pip3 install -e ".[example]"
 
 ### Retargeting from human hand video
 
-1. **Generate the robot joint pose trajectory from our pre-recorded video.**
+[Tutorial on retargeting from human hand video](example/vector_retargeting/README.md)
 
-```shell
-cd example/vector_retargeting
-python3 detect_from_video.py \
-  --robot-name allegro \
-  --video-path data/human_hand_video.mp4 \
-  --retargeting-type vector \
-  --hand-type right \
-  --output-path data/allegro_joints.pkl 
-```
-
-This command will output the joint trajectory as a pickle file at the `output_path`.
-
-The pickle file is a python dictionary with two keys: `meta_data` and `data`. `meta_data`, a dictionary, includes
-details about the robot, while `data`, a list, contains the robotic joint positions for each frame. For additional
-options, refer to the help information. Note that the time cost here includes both the hand pose detection from video,
-and the hand pose retargeting in single process mode.
-
-```shell
-python3 detect_from_video.py --help
-```
-
-2. **Utilize the pickle file to produce a video of the robot**
-
-```shell
-python3 render_robot_hand.py \
-  --pickle-path data/allegro_joints.pkl \
-  --output-video-path data/retargeted_allegro.mp4 \
-  --headless
-```
-
-This command uses the data saved from the previous step to create a rendered video.
-
-3. **Record a video of your own hand**
-
-```bash
-python3 capture_webcam.py --video-path example/vector_retargeting/data/my_human_hand_video.mp4
-
-```
-
-This command will access your webcam (which should be connected to your computer) and record the video stream in mp4
-format. To end video recording, press `q` on the keyboard.
-
-### Retargeting from hand-object pose trajectory
+### Retarget from hand object pose dataset
 
-Here we use the [DexYCB]() dataset to show that how can we retarget the human hand-object interaction trajectory to
-robot hand-object interaction trajectory. After 
+[Tutorial on retargeting from hand-object pose dataset](example/position_retargeting/README.md)

example/vector_retargeting/README.md

@@ -0,0 +1,50 @@
+## Retarget Robot Motion from Human Hand Video
+
+### Generate the robot joint pose trajectory from our pre-recorded video
+
+```shell
+cd example/vector_retargeting
+python3 detect_from_video.py \
+  --robot-name allegro \
+  --video-path data/human_hand_video.mp4 \
+  --retargeting-type vector \
+  --hand-type right \
+  --output-path data/allegro_joints.pkl 
+```
+
+This command will output the joint trajectory as a pickle file at the `output_path`.
+
+The pickle file is a python dictionary with two keys: `meta_data` and `data`. `meta_data`, a dictionary, includes
+details about the robot, while `data`, a list, contains the robotic joint positions for each frame. For additional
+options, refer to the help information. Note that the time cost here includes both the hand pose detection from video,
+and the hand pose retargeting in single process mode.
+
+```shell
+python3 detect_from_video.py --help
+```
+
+### Utilize the pickle file to produce a video of the robot
+
+```shell
+python3 render_robot_hand.py \
+  --pickle-path data/allegro_joints.pkl \
+  --output-video-path data/retargeted_allegro.mp4 \
+  --headless
+```
+
+This command uses the data saved from the previous step to create a rendered video.
+
+### Record a video of your own hand
+
+```bash
+python3 capture_webcam.py --video-path example/vector_retargeting/data/my_human_hand_video.mp4
+
+```
+
+This command will access your webcam (which should be connected to your computer) and record the video stream in mp4
+format. To end video recording, press `q` on the keyboard.
+
+### Retargeting from hand-object pose trajectory
+
+Here we use the [DexYCB]() dataset to show that how can we retarget the human hand-object interaction trajectory to
+robot hand-object interaction trajectory. After