Comments (2)
They're actually completely different models, so I'm not surprised to see that the results don't line up perfectly. The online demo model was trained several years ago, and the model weights released alongside the project were obtained via fine-tuning with data collected from the online demo.
If the returned detection is clipping the extremities of your character, this can result in very bad segmentations maps. If you want to be certain to avoid this, I would recommend you pad the detected bounding box (e.g. add 15 pixels to each side) and use that in the downstream segmentation and pose estimation steps.
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Thank you for providing this information, it's better with padding now. 😄
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Related Issues (20)
- Error on image_to_animation.py
- Issue when running image_to_animation HOT 1
- A rendering performance issue HOT 3
- Same image different results (demo vs local) HOT 6
- FFMPEG deal with mp4 ERROR
- I would like to ask if it is necessary to use docker HOT 5
- many joints " not inside or on edge of any triangle in mesh. Skipping it" HOT 1
- Failed to build Docker HOT 2
- Source code of fixing bounding box missing HOT 2
- ERROR: failed to solve: process "/bin/sh -c mim install mmcv-full==1.7.0" did not complete successfully: exit code: 1 HOT 2
- Failed to get bounding box HOT 14
- AttributeError: 'NoneType' object has no attribute 'decode' HOT 3
- Exception: Failed to get bounding box, please check if the 'docker_torchserve' is running and healthy, resp: <Response [500]>
- docker start fail HOT 6
- torchserve docker build fail HOT 2
- Selecting the Correct YAML File for Wave_Hello.bvh HOT 4
- GARLIC error HOT 8
- ModuleError: No module named "ts.torch_handler.mmdet_handler" HOT 1
- When docker build, stuck on Connecting to objects.githubusercontent.com (objects.githubusercontent => => # .com)|::ffff:185.199.109.133|:443... HOT 2
- call the server in docker,raise error.Then the server turn to unhealthy,the memory is 16GB HOT 8
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