Allows MPS inference. Fix visualization args
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03f3c41e07
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d6df5d248f
@ -17,7 +17,7 @@ from cotracker.models.build_cotracker import (
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class CoTrackerPredictor(torch.nn.Module):
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def __init__(
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self, checkpoint="cotracker/checkpoints/cotracker_stride_4_wind_8.pth", device=None
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self, checkpoint="cotracker/checkpoints/cotracker_stride_4_wind_8.pth"
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):
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super().__init__()
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self.interp_shape = (384, 512)
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12
demo.py
12
demo.py
@ -14,6 +14,9 @@ from PIL import Image
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from cotracker.utils.visualizer import Visualizer, read_video_from_path
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from cotracker.predictor import CoTrackerPredictor
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DEFAULT_DEVICE = ('cuda' if torch.cuda.is_available() else
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'mps' if torch.backends.mps.is_available() else
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'cpu')
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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@ -55,11 +58,8 @@ if __name__ == "__main__":
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segm_mask = torch.from_numpy(segm_mask)[None, None]
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model = CoTrackerPredictor(checkpoint=args.checkpoint)
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if torch.cuda.is_available():
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model = model.cuda()
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video = video.cuda()
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else:
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print("CUDA is not available!")
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model = model.to(DEFAULT_DEVICE)
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video = video.to(DEFAULT_DEVICE)
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pred_tracks, pred_visibility = model(
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video,
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@ -73,4 +73,4 @@ if __name__ == "__main__":
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# save a video with predicted tracks
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seq_name = args.video_path.split("/")[-1]
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vis = Visualizer(save_dir="./saved_videos", pad_value=120, linewidth=3)
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vis.visualize(video, pred_tracks, query_frame=args.grid_query_frame)
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vis.visualize(video, pred_tracks, pred_visibility, query_frame=args.grid_query_frame)
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