From b4cf10f7348f41be6cf3cae8fc5ade8556bb1ff8 Mon Sep 17 00:00:00 2001 From: Anantajit Subrahmanya Date: Mon, 30 Jun 2025 16:27:18 -0700 Subject: [PATCH 1/2] Fixed dependencies management (Python 3.10.12) up to training --- .gitignore | 1 + preprocessing/config.yaml | 4 +- preprocessing/rearrange.py | 2 +- pyproject.toml | 44 + training/config/detector/xception.yaml | 4 +- training/config/train_config.yaml | 6 +- training/dataset/abstract_dataset.py | 22 +- training/test.py | 2 +- training/train.py | 2 +- uv.lock | 2567 ++++++++++++++++++++++++ 10 files changed, 2637 insertions(+), 17 deletions(-) create mode 100644 pyproject.toml create mode 100644 uv.lock diff --git a/.gitignore b/.gitignore index 53a027b..10b1f82 100644 --- a/.gitignore +++ b/.gitignore @@ -5,3 +5,4 @@ *.pth *.pt *.dat +.envrc \ No newline at end of file diff --git a/preprocessing/config.yaml b/preprocessing/config.yaml index 4a74cc4..951ce56 100644 --- a/preprocessing/config.yaml +++ b/preprocessing/config.yaml @@ -24,10 +24,10 @@ rearrange: default: 'FaceForensics++' dataset_root_path: # the root path to the dataset type: str - default: '' + default: 'datasets/rgb' output_file_path: # the json path to the dataset type: str - default: '../preprocessing/dataset_json_v6' + default: 'datasets/json' comp: # the compression level of videos, only in the dataset of FaceForensics++. choices: ['raw', 'c23', 'c40'] default: 'c23' diff --git a/preprocessing/rearrange.py b/preprocessing/rearrange.py index d58b30c..53b0651 100644 --- a/preprocessing/rearrange.py +++ b/preprocessing/rearrange.py @@ -500,7 +500,7 @@ def generate_dataset_file(dataset_name, dataset_root_path, output_file_path, com if __name__ == '__main__': # from config.yaml load parameters - yaml_path = './config.yaml' + yaml_path = './preprocessing/config.yaml' # open the yaml file try: with open(yaml_path, 'r') as f: diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..06135f6 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,44 @@ +[project] +name = "deepfakebench" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.10" +dependencies = [ + "albumentations>=2.0.8", + "clip", + "dlib>=20.0.0", + "efficientnet-pytorch>=0.7.1", + "einops>=0.8.1", + "filterpy>=1.4.5", + "fvcore>=0.1.5.post20221221", + "imageio>=2.37.0", + "imgaug>=0.4.0", + "imutils>=0.5.4", + "kornia>=0.8.1", + "loralib>=0.1.2", + "numpy<2.0", + "opencv-python>=4.11.0.86", + "pandas>=2.3.0", + "pillow>=11.2.1", + "pyyaml>=6.0.2", + "requests>=2.25.0", + "scikit-image>=0.25.2", + "scikit-learn>=1.7.0", + "scipy>=1.15.3", + "seaborn>=0.13.2", + "segmentation-models-pytorch>=0.5.0", + "setuptools>=80.9.0", + "simplejson>=3.20.1", + "tensorboard>=2.19.0", + "timm>=1.0.16", + "torch>=2.7.1", + "torchaudio>=2.7.1", + "torchtoolbox>=0.1.8.2", + "torchvision>=0.22.1", + "tqdm>=4.67.1", + "transformers>=4.53.0", +] + +[tool.uv.sources] +clip = { git = "https://github.com/openai/CLIP.git" } diff --git a/training/config/detector/xception.yaml b/training/config/detector/xception.yaml index 54ba76f..888efcd 100644 --- a/training/config/detector/xception.yaml +++ b/training/config/detector/xception.yaml @@ -1,5 +1,5 @@ # log dir -log_dir: /data/home/zhiyuanyan/DeepfakeBench/logs/testing_bench +log_dir: ./logs/training/xception # model setting pretrained: ./training/pretrained/xception-b5690688.pth # path to a pre-trained model, if using one @@ -64,7 +64,7 @@ optimizer: # training config lr_scheduler: null # learning rate scheduler -nEpochs: 10 # number of epochs to train for +nEpochs: 1 # number of epochs to train for start_epoch: 0 # manual epoch number (useful for restarts) save_epoch: 1 # interval epochs for saving models rec_iter: 100 # interval iterations for recording diff --git a/training/config/train_config.yaml b/training/config/train_config.yaml index e154ea6..0c95e31 100644 --- a/training/config/train_config.yaml +++ b/training/config/train_config.yaml @@ -1,9 +1,9 @@ mode: train -lmdb: True +lmdb: False dry_run: false -rgb_dir: './datasets/rgb' +rgb_dir: '.' lmdb_dir: './datasets/lmdb' -dataset_json_folder: './preprocessing/dataset_json' +dataset_json_folder: './datasets/json' SWA: False save_avg: True log_dir: ./logs/training/ diff --git a/training/dataset/abstract_dataset.py b/training/dataset/abstract_dataset.py index 0caa644..b594715 100644 --- a/training/dataset/abstract_dataset.py +++ b/training/dataset/abstract_dataset.py @@ -14,6 +14,7 @@ import yaml import glob import json +from pathlib import Path import numpy as np from copy import deepcopy @@ -115,11 +116,11 @@ def init_data_aug_method(self): A.HorizontalFlip(p=self.config['data_aug']['flip_prob']), A.Rotate(limit=self.config['data_aug']['rotate_limit'], p=self.config['data_aug']['rotate_prob']), A.GaussianBlur(blur_limit=self.config['data_aug']['blur_limit'], p=self.config['data_aug']['blur_prob']), - A.OneOf([ - IsotropicResize(max_side=self.config['resolution'], interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC), - IsotropicResize(max_side=self.config['resolution'], interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_LINEAR), - IsotropicResize(max_side=self.config['resolution'], interpolation_down=cv2.INTER_LINEAR, interpolation_up=cv2.INTER_LINEAR), - ], p = 0 if self.config['with_landmark'] else 1), + # A.OneOf([ + # IsotropicResize(max_side=self.config['resolution'], interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_CUBIC), + # IsotropicResize(max_side=self.config['resolution'], interpolation_down=cv2.INTER_AREA, interpolation_up=cv2.INTER_LINEAR), + # IsotropicResize(max_side=self.config['resolution'], interpolation_down=cv2.INTER_LINEAR, interpolation_up=cv2.INTER_LINEAR), + # ], p = 0 if self.config['with_landmark'] else 1), A.OneOf([ A.RandomBrightnessContrast(brightness_limit=self.config['data_aug']['brightness_limit'], contrast_limit=self.config['data_aug']['contrast_limit']), A.FancyPCA(), @@ -296,7 +297,7 @@ def load_rgb(self, file_path): size = self.config['resolution'] # if self.mode == "train" else self.config['resolution'] if not self.lmdb: if not file_path[0] == '.': - file_path = f'./{self.config["rgb_dir"]}\\'+file_path + file_path = f'./{self.config["rgb_dir"]}/'+file_path assert os.path.exists(file_path), f"{file_path} does not exist" img = cv2.imread(file_path) if img is None: @@ -469,7 +470,9 @@ def __getitem__(self, index, no_norm=False): label = self.data_dict['label'][index] if not isinstance(image_paths, list): - image_paths = [image_paths] # for the image-level IO, only one frame is used + image_paths = [Path(image_paths)] # for the image-level IO, only one frame is used + + image_paths = [Path(path) for path in image_paths] # Sanitize image paths image_tensors = [] landmark_tensors = [] @@ -477,6 +480,11 @@ def __getitem__(self, index, no_norm=False): augmentation_seed = None for image_path in image_paths: + # check if this is a valid path + if not image_path.exists(): + raise ValueError(f"Image path {image_path.absolute()} does not exist.") + + image_path = str(image_path) # Initialize a new seed for data augmentation at the start of each video if self.video_level and image_path == image_paths[0]: augmentation_seed = random.randint(0, 2**32 - 1) diff --git a/training/test.py b/training/test.py index f13d641..a0c89dd 100644 --- a/training/test.py +++ b/training/test.py @@ -37,7 +37,7 @@ parser = argparse.ArgumentParser(description='Process some paths.') parser.add_argument('--detector_path', type=str, - default='/home/zhiyuanyan/DeepfakeBench/training/config/detector/resnet34.yaml', + default='config/detector/resnet34.yaml', help='path to detector YAML file') parser.add_argument("--test_dataset", nargs="+") parser.add_argument('--weights_path', type=str, diff --git a/training/train.py b/training/train.py index f3b59bc..4377062 100644 --- a/training/train.py +++ b/training/train.py @@ -38,7 +38,7 @@ parser = 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a/training/config/detector/xception.yaml +++ b/training/config/detector/xception.yaml @@ -1,5 +1,5 @@ # log dir -log_dir: ./logs/training/xception +log_dir: /data/home/zhiyuanyan/DeepfakeBench/logs/testing_bench # model setting pretrained: ./training/pretrained/xception-b5690688.pth # path to a pre-trained model, if using one @@ -64,7 +64,7 @@ optimizer: # training config lr_scheduler: null # learning rate scheduler -nEpochs: 1 # number of epochs to train for +nEpochs: 10 # number of epochs to train for start_epoch: 0 # manual epoch number (useful for restarts) save_epoch: 1 # interval epochs for saving models rec_iter: 100 # interval iterations for recording