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readme.me
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Argument list:
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# Testing exported model
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The following script creates an MP4 video of interpolated frames between 2 input images:
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```
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python inference.py "model_path" "img1" "img2" [--save_path SAVE_PATH] [--gpu] [--fp16] [--frames FRAMES] [--fps FPS]
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```
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Argument list:
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* `model_path` Path to the TF SavedModel
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* `save_path` Path to save the PyTorch state dict
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* `--statedict` Export to state dict instead of TorchScript
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* `--fp32` Save weights at full precision
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* `--skiptest` Skip testing and save model immediately instead
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* `--gpu` Whether to attempt to use GPU for testing
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# Testing exported model
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The following script creates an MP4 video of interpolated frames between 2 input images:
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```
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python inference.py "model_path" "img1" "img2" [--save_path SAVE_PATH] [--gpu] [--fp16] [--frames FRAMES] [--fps FPS]
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```
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* `model_path` Path to the exported TorchScript checkpoint
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* `img1` Path to the first image
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* `img2` Path to the second image
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* `--save_path SAVE_PATH` Path to save the interpolated frames as a video, if absent it will be saved in the same directory as ```img1``` is located and named ```output.mp4```
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* `--gpu` Whether to attempt to use GPU for predictions
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* `--fp16` Whether to use fp16 for calculations, speeds inference up on GPUs with tensor cores
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* `--frames FRAMES` Number of frames to interpolate between the input images
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* `--fps FPS` FPS of the output video
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