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Added logging for interventions to monitor the rate of interventions through time
Added an s keyboard command to force success in the case the reward classifier fails Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com>
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@@ -245,10 +245,18 @@ if __name__ == "__main__":
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images = {k: v.cpu().permute(1, 2, 0).numpy() for k, v in images.items()}
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images = {k: (v * 255).astype("uint8") for k, v in images.items()}
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rois = select_square_roi_for_images(images)
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# rois = select_square_roi_for_images(images)
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rois = {
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"observation.images.front": [102, 43, 358, 523],
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"observation.images.side": [92, 123, 379, 349],
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}
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# rois = {
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# "observation.images.front": [126, 43, 329, 518],
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# "observation.images.side": [93, 69, 381, 434],
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# "observation.images.side": (92, 123, 379, 349),
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# "observation.images.front": (109, 37, 361, 557),
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# }
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# rois = {
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# "observation.images.front": [109, 37, 361, 557],
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# "observation.images.side": [94, 161, 372, 315],
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# }
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# Print the selected rectangular ROIs
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