clean/video/fakestormer/datasets/df40.py

# -*- coding: utf-8 -*-
import os
from glob import glob

import numpy as np

from .builder import DATASETS
from .common import CommonDataset


@DATASETS.register_module()
class DF40(CommonDataset):
    def __init__(self, cfg, **kwargs):
        super().__init__(cfg, **kwargs)

    def _load_from_path(self, split):
        # Check if the root directory exists.
        root_dir = self._cfg.DATA[self.split.upper()].ROOT
        assert os.path.exists(root_dir), "Root path to dataset cannot be None!"

        data = self._cfg["DATA"]
        data_type = data.TYPE
        fake_types = self._cfg.DATA[split.upper()]["FAKETYPE"]
        img_paths, labels, mask_paths, ot_props = [], [], [], []

        # Load image data for each type of fake technique.
        for ft in fake_types:
            # Construct path: ROOT/split/fake_type (skipping data_type)
            data_dir = os.path.join(root_dir, self.split, data_type, ft)
            if not os.path.exists(data_dir):
                raise ValueError("Data Directory is invalid!")

            # Define common image extensions.
            extensions = ["jpg", "jpeg", "png", "tif", "webp"]
            img_paths_ = []
            # Recursively search for images in the fake type directory.
            for ext in extensions:
                pattern = os.path.join(data_dir, "**", f"*.{ext}")
                img_paths_.extend(glob(pattern, recursive=True))

            # Extend the main lists with the images and corresponding labels.
            img_paths.extend(img_paths_)
            labels.extend(np.full(len(img_paths_), int(ft != "real_videos")))

        print("{} image paths have been loaded from DF40!".format(len(img_paths)))
        return img_paths, labels, mask_paths, ot_props