This repository contains examples and best practice guidelines for building keypoint detection systems. It also shows how to use a pre-trained model for human pose estimation.
Keypoints are defined as points-of-interests on objects. For example, one might be interested in finding the position of the lid on a bottle. Another example is to find body joints (hands, shoulders, etc.) for human pose estimation.
We use an extension of Mask R-CNN which simultaneously detects objects and their keypoints. The underlying technology is very similar to our approach for object detection, ie. based on Torchvision's Mask R-CNN. The example notebook for keypoint localization is therefore in the detection folder.
| Detecting the top and bottom on our fridge objects | Detecting various keypoints on milk bottles | Human pose estimation using the provided pre-trained model |
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See the FAQ.md in the object detection folder.
| Notebook name | Description |
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| 03_keypoint_rcnn.ipynb | Notebook which shows how to (i) run a pre-trained model for human pose estimation; and (ii) train a custom keypoint detection model. |
See the contribution guidelines in the root folder.