Comments (1)
Thank you for your interest. We have included predefined keypoints, so there's no need to provide a keypoint text prompt. You can proceed with the image inference using the following command:
python inference_on_a_image.py -c config/UniPose_SwinT.py -p weights/unipose_swint.pth -i image_you_want_to_test.jpg -o "dir you want to save the output" -t "person"
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Related Issues (17)
- Code Release HOT 2
- 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 3
- VS. OpenPose HOT 1
- 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?
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