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46 lines
1.5 KiB
46 lines
1.5 KiB
from pathlib import Path
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from lightning import Callback
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from check import create_circle
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class SaveImageCallback(Callback):
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def __init__(self, save_interval=1, final_dir: str = None):
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self.save_interval = save_interval
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self.final_dir = final_dir
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def on_train_epoch_end(self, trainer, pl_module):
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epoch = trainer.current_epoch
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if self.save_interval <= 0:
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return None
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if epoch % self.save_interval == 0:
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# Set the model to eval mode for generating the image
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pl_module.eval()
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# Save the image
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# if pl_module.trainer.logger:
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#
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# else:
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# version = 0
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fname = Path(pl_module.trainer.logger.log_dir) / Path(f"e{epoch:04d}")
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create_circle(pl_module, fname=fname)
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# Make sure to set it back to train mode
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pl_module.train()
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def on_train_end(self, trainer, pl_module):
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if self.final_dir:
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version = pl_module.trainer.logger.version
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fname = Path(f"{self.final_dir}") / Path(f"v{version}")
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pl_module.eval()
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create_circle(pl_module, fname=fname)
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if self.save_interval > 0:
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import os
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log_dir = str(Path(pl_module.trainer.logger.log_dir))
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fps = 12
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os.system(
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f'ffmpeg -i {log_dir}/e%04d.png -c:v libx264 -vf "fps={fps},format=yuv420p,pad=ceil(iw/2)*2:ceil(ih/2)*2" {log_dir}/a{version}.mp4'
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)
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