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# import subprocess
import os
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from pathlib import Path
from lightning import Callback
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from check import create_circle_nonblocking as create_circle
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class SaveImageCallback(Callback):
def __init__(
self,
save_interval=1,
final_dir: str = None,
radius: float = 0.5,
dpi: int = 300,
figsize=(15, 15), # 4k is at 14.4
):
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self.save_interval = save_interval
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self.final_dir = final_dir
self.radius = radius
self.dpi = dpi
self.figsize = figsize
self.processes = []
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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:
return None
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if epoch % self.save_interval == 0:
# Set the model to eval mode for generating the image
pl_module.eval()
# Save the image
fname = Path(pl_module.trainer.logger.log_dir) / Path(f"e{epoch:04d}")
p = create_circle(
pl_module,
fname=fname,
dpi=self.dpi,
figsize=self.figsize,
radius=self.radius,
)
self.processes.append(p)
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# Make sure to set it back to train mode
pl_module.train()
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def on_train_end(self, trainer, pl_module):
if self.final_dir:
version = pl_module.trainer.logger.version
fname = Path(f"{self.final_dir}") / Path(f"v{version}")
pl_module.eval()
p = create_circle(
pl_module,
fname=fname,
dpi=self.dpi,
figsize=self.figsize,
radius=self.radius,
)
self.processes.append(p)
# Wait for all subprocesses to finish
for p in self.processes:
p.join()
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if self.save_interval > 0:
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log_dir = str(Path(pl_module.trainer.logger.log_dir))
fps = 12
# w, h = self.figsize[0] * self.dpi, self.figsize[1] * self.dpi
w, h = 7680, 4320
_cmd = f'ffmpeg -r {fps} -f image2 -i {log_dir}/e%04d.png -vcodec libx264 -crf 25 -pix_fmt yuv420p -vf "scale={w}:{h}:force_original_aspect_ratio=decrease,pad={w}:{h}:(ow-iw)/2:(oh-ih)/2:color=white" {log_dir}/a{version}.mp4'
# _ = subprocess.Popen(_cmd, shell=True)
os.system(_cmd)