from pathlib import Path

from lightning import Callback

from check import create_circle


class SaveImageCallback(Callback):
    def __init__(self, save_interval=1, final_dir: str = None):
        self.save_interval = save_interval
        self.final_dir = final_dir

    def on_train_epoch_end(self, trainer, pl_module):
        epoch = trainer.current_epoch
        if self.save_interval <= 0:
            return None

        if epoch % self.save_interval == 0:
            # Set the model to eval mode for generating the image
            pl_module.eval()

            # Save the image
            # if pl_module.trainer.logger:
            #
            # else:
            #     version = 0
            fname = Path(pl_module.trainer.logger.log_dir) / Path(f"e{epoch:04d}")
            create_circle(pl_module, fname=fname, dpi=300, figsize=(6, 6))

            # Make sure to set it back to train mode
            pl_module.train()

    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()
            create_circle(pl_module, fname=fname, dpi=300, figsize=(6, 6))
            if self.save_interval > 0:
                import os

                log_dir = str(Path(pl_module.trainer.logger.log_dir))
                fps = 12
                _cmd = f'ffmpeg -r {fps} -f image2 -i {log_dir}/e%04d.png -vcodec libx264 -crf 25 -pix_fmt yuv420p -vf "scale=1920:1080:force_original_aspect_ratio=decrease,pad=1920:1080:(ow-iw)/2:(oh-ih)/2:color=white" {log_dir}/a{version}.mp4'
                os.system(_cmd)
                # os.system(
                #     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'
                # )