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how to test own dataset on Demo.py #26
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I have the same problem. It seems that it is not possible to input an in-the-wild image to the network before adding to the target a significant amount of information such as the image can be transformed before it goes into the network. |
We use OpenPose keypoints to get a person's bounding box which we use to center and crop them. If you have the bounding box already, you can skip this step. To do this, in the data loader, replace kpts_to_bbox() with the bounding box information [xmin, ymin, xmax, ymax]. I still recommend running OpenPose and use the automated bounding box computation, because these bounding boxes will match the ones the model was trained with. You can follow the images and openpose structure in our demo and then run the SHAPY demo. |
@muelea Thanks for the helpful information. I will attempt to make a PR with a notebook demonstrating the complete pipeline. |
@muelea Hi, can I ask about which part of your code can change to T pose ? Could you please show me? |
@felixshing Ja, I did but I had to make a lot of changes. I'm still trying to double check because the results I obtained are really strange. |
Can you explain how to train from an image without openpose? |
Hello, I want to try my own dataset to test regressor. Which process that I need to do first before I run on regressor? Do I need to run openpose and get json format first? And also image size is only 300 450 px ?
I run my own image and got this error : ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 135 and the array at index 1 has size 131
My image is :1920 1080 px but I resize to 300 450 px to match with yours and still have that error.
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