Comments (1)
Hi @GloryyrolG,
From our experiment, UniPose has a better generalization than OpenPose on multi-person, artificial human, heavy occlusion scenes due to the fully end-to-end training pipeline on diverse datasets. You can simply use this link to try the performance. For the person keypoint detection, input "person" in the "Instance Prompt" and leave "Keypoint Example" alone. If you find multiple redundant outputs, please decrease the "IoU Threshold" in "Advanced options" to 0.1.
from unipose.
Related Issues (20)
- Code Release HOT 2
- only input images HOT 1
- LOOKING FORWARD TO YOUR OUTSTANDING WORK released on October 30th !!!!!!!! HOT 1
- error loading the checkpoint HOT 2
- error in ms_deformable_im2col_cuda: no kernel image is available for execution on the device HOT 6
- how can I convert model to onnx format. HOT 1
- Method name is copied from CVPR published Pose Estimation paper HOT 1
- about train? HOT 4
- Regarding Licence HOT 2
- How to distinguish which dataset the image belongs to in unikpt annotation HOT 1
- Does the online demo support image prompt?
- Does this code can use visual prompts? HOT 1
- How can I build the UniKPT dataset based on the annotation files you provided?
- About sketch style images
- There are errors in the same place here and behind
- How much GPU memory space is required to run this demonstration code?
- is there a simple way to reproduce visual prompting results?
- Had you tried Transformers's MSDA implementation?
- when release vit model for inference_on_a_image.py
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from unipose.