Comments (1)
I also wonder the units of Measurement for MotionBert. In the table 1 of the paper, all results are said to be shown as 'mm'. However, in the evaluation period of the training code, the prediction 3d keypoints are only denormalized by the code below,
n_clips = test_data.shape[0]
test_hw = self.get_hw()
data = test_data.reshape([n_clips, -1, 17, 3])
assert len(data) == len(test_hw)
# denormalize (x,y,z) coordiantes for results
for idx, item in enumerate(data):
res_w, res_h = test_hw[idx]
data[idx, :, :, :2] = (data[idx, :, :, :2] + np.array([1, res_h / res_w])) * res_w / 2
data[idx, :, :, 2:] = data[idx, :, :, 2:] * res_w / 2
where the test_wh can be (1000, 1000) or (1000, 1002). I think the code mentioned above can just be a pose-processing that transform the results in relative pixel coordinate into pixel coordinate. I wonder why the results are transformed into 'mm' after the calculation above.
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Related Issues (20)
- What is the unit of 3d keypoints HOT 3
- About real time HOT 1
- Can the model support inputs greater than 17 key points?
- Motion Path
- mesh_det_* origin
- The validation section in the training code
- Coordinate Axes Convention
- Transfer learning using dataset with different keypoints HOT 1
- NameError: name 'output' is not defined
- RuntimeError: Python 3.8 or later is required
- 求问下大神,global的指标和local的一样么 HOT 1
- save the results as txt file
- issue about preprocess amass dataset HOT 6
- keypoint_score in dataset_action.py HOT 2
- _pickle.UnpicklingError: pickle data was truncated Error Running train_action.py
- Wrong view of SMPL data in infer_wild_mesh.py
- How to obtain pre train/MB-release? thanks
- head pose orientation solution for an IP camera
- I want to infer_wild, but how to get json_path <alphapose-results.json> ? HOT 1
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from motionbert.