src/pixparse/task/task_cruller_eval_ocr.py [116:146]:
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        img_mean = self.model.image_encoder.trunk.pretrained_cfg["mean"]
        img_std = self.model.image_encoder.trunk.pretrained_cfg["std"]

        self.img_mean = (
            sum(img_mean) / len(img_mean)
            if cfg.model.image_encoder.image_fmt == "L"
            else img_mean
        )
        self.img_std = (
            sum(img_std) / len(img_std)
            if cfg.model.image_encoder.image_fmt == "L"
            else img_std
        )

        # preprocessors cross both the task/model & dataset domain,
        # created within task here and passed to data loaders
        self.image_preprocess_eval = transforms.Compose(
            [
                transforms.ToTensor(),
                transforms.Resize(
                    cfg.model.image_encoder.image_size,
                    interpolation=transforms.InterpolationMode.BICUBIC,
                    antialias=True,
                ),
                # transforms.CenterCrop(448),  # FIXME need better aspect preserving resize & pad
                transforms.Normalize(
                    mean=self.img_mean,
                    std=self.img_std,
                ),
            ]
        )
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src/pixparse/task/task_cruller_eval_rvlcdip.py [146:176]:
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        img_mean = self.model.image_encoder.trunk.pretrained_cfg["mean"]
        img_std = self.model.image_encoder.trunk.pretrained_cfg["std"]

        self.img_mean = (
            sum(img_mean) / len(img_mean)
            if cfg.model.image_encoder.image_fmt == "L"
            else img_mean
        )
        self.img_std = (
            sum(img_std) / len(img_std)
            if cfg.model.image_encoder.image_fmt == "L"
            else img_std
        )

        # preprocessors cross both the task/model & dataset domain,
        # created within task here and passed to data loaders
        self.image_preprocess_eval = transforms.Compose(
            [
                transforms.ToTensor(),
                transforms.Resize(
                    cfg.model.image_encoder.image_size,
                    interpolation=transforms.InterpolationMode.BICUBIC,
                    antialias=True,
                ),
                # transforms.CenterCrop(448),  # FIXME need better aspect preserving resize & pad
                transforms.Normalize(
                    mean=self.img_mean,
                    std=self.img_std,
                ),
            ]
        )
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