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Perform Human Pose Estimation in OpenCV Using OpenPose MobileNet
| Date | Stars |
|---|---|
| 2026-07-24 | 384 |
| 2026-07-25 | 384 |
| 2026-07-28 | 384 |
| 2026-07-30 | 384 |
| 2026-08-06 | 384 |
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# human-pose-estimation-opencv Perform Human Pose Estimation in OpenCV Using OpenPose MobileNet  # How to use - Test with webcam ``` python openpose.py ``` - Test with image ``` python openpose.py --input image.jpg ``` - Use `--thr` to increase confidence threshold ``` python openpose.py --input image.jpg --thr 0.5 ``` # Notes: - I modified the [OpenCV DNN Example](https://github.com/opencv/opencv/blob/master/samples/dnn/openpose.py) to use the `Tensorflow MobileNet Model`, which is provided by [ildoonet/tf-pose-estimation](https://github.com/ildoonet/tf-pose-estimation/tree/master/models/graph/mobilenet_thin), instead of `Caffe Model` from CMU OpenPose. The original `openpose.py` from `OpenCV example` only uses `Caffe Model` which is more than 200MB while the `Mobilenet` is only 7MB. - Basically, we need to change the `cv.dnn.blobFromImage` and use `out = out[:, :19, :, :]` to get only the first 19 rows in the `out` variable.
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:0c68f5850fcb6aad, topic:computer-vision, topic:opencv, topic:pose-estimation