add aditional files for data augmentation

src/plasticorigins/training/data/DA_for_GenData.py

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+from pathlib import Path
+import argparse
+from argparse import Namespace
+import os
+
+
+#############
+# COPY AND RENAME OLD TRAIN AND VAL TXT
+# FILL NEW TRAIN TXT by excuting :
+# python src/plasticorigins/training/data/DA_for_GenData.py --data-dir /datadrive/data/data_20062022 --artificial-data /datadrive/data/artificial_data
+# RENAME WITH _DA SUFFIX AFTER
+#############
+
+
+def main(args: Namespace) -> None:
+    """Main Function to write new images paths for training.
+
+    Args:
+        args (argparse): list of arguments to build dataset for label mapping and training
+    """
+
+    data_dir = Path(args.data_dir)
+
+    # use data augmentation for artificial data only if original data have been processed
+    artificial_data_dir = Path(args.artificial_data)
+    artificial_train_files = [Path(path).as_posix() for path in os.listdir(artificial_data_dir / "images")]
+
+    # concatenate original images and artificial data
+    with open(data_dir / "train.txt", "w") as f:
+        for path in artificial_train_files:
+            f.write(path + "\n")
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser(description="Build dataset")
+    parser.add_argument("--data-dir", type=str, help="path to main data folder")
+    parser.add_argument("--artificial-data", type=str, help="path to artificial data folder")
+
+    args = parser.parse_args()
+    main(args)

src/plasticorigins/training/data/remove_img.py

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+from pathlib import Path
+import argparse
+from argparse import Namespace
+import os
+from tqdm import tqdm
+
+
+#############
+# remove  by excuting :
+# python src/plasticorigins/training/data/remove_img.py --artificial-data /datadrive/data/artificial_data/
+#############
+
+
+def main(args: Namespace) -> None:
+    """Main Function to remove data augmentation from Artificial Data.
+
+    Args:
+        args (argparse): list of arguments to build dataset for label mapping and training
+    """
+
+    # use data augmentation for artificial data only if original data have been processed
+    artificial_data_dir = Path(args.artificial_data)
+    artificial_train_files = [(artificial_data_dir / "images" / path).as_posix() for path in os.listdir(artificial_data_dir / "images")]
+    original_data = [(artificial_data_dir / "images" / path).as_posix() for path in os.listdir(artificial_data_dir / "images") if len(path.split('/')[-1].split('_')) < 3]
+    data_to_remove = list(set(artificial_train_files) - set(original_data))
+
+    # remove data augmentation files
+    for file in tqdm(data_to_remove):
+        os.remove(file)
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser(description="Build dataset")
+    parser.add_argument("--artificial-data", type=str, help="path to artificial data folder")
+
+    args = parser.parse_args()
+    main(args)