Upload lora-scripts/sd-scripts/finetune/make_captions_by_git.py with huggingface_hub

lora-scripts/sd-scripts/finetune/make_captions_by_git.py

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+import argparse
+import os
+import re
+
+from pathlib import Path
+from PIL import Image
+from tqdm import tqdm
+
+import torch
+from library.device_utils import init_ipex, get_preferred_device
+init_ipex()
+
+from transformers import AutoProcessor, AutoModelForCausalLM
+from transformers.generation.utils import GenerationMixin
+
+import library.train_util as train_util
+from library.utils import setup_logging
+setup_logging()
+import logging
+logger = logging.getLogger(__name__)
+
+DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+PATTERN_REPLACE = [
+    re.compile(r'(has|with|and) the (words?|letters?|name) (" ?[^"]*"|\w+)( ?(is )?(on|in) (the |her |their |him )?\w+)?'),
+    re.compile(r'(with a sign )?that says ?(" ?[^"]*"|\w+)( ?on it)?'),
+    re.compile(r"(with a sign )?that says ?(' ?(i'm)?[^']*'|\w+)( ?on it)?"),
+    re.compile(r"with the number \d+ on (it|\w+ \w+)"),
+    re.compile(r'with the words "'),
+    re.compile(r"word \w+ on it"),
+    re.compile(r"that says the word \w+ on it"),
+    re.compile("that says'the word \"( on it)?"),
+]
+
+# 誤検知しまくりの with the word xxxx を消す
+
+
+def remove_words(captions, debug):
+    removed_caps = []
+    for caption in captions:
+        cap = caption
+        for pat in PATTERN_REPLACE:
+            cap = pat.sub("", cap)
+        if debug and cap != caption:
+            logger.info(caption)
+            logger.info(cap)
+        removed_caps.append(cap)
+    return removed_caps
+
+
+def collate_fn_remove_corrupted(batch):
+    """Collate function that allows to remove corrupted examples in the
+    dataloader. It expects that the dataloader returns 'None' when that occurs.
+    The 'None's in the batch are removed.
+    """
+    # Filter out all the Nones (corrupted examples)
+    batch = list(filter(lambda x: x is not None, batch))
+    return batch
+
+
+def main(args):
+    r"""
+    transformers 4.30.2で、バッチサイズ>1でも動くようになったので、以下コメントアウト
+
+    # GITにバッチサイズが1より大きくても動くようにパッチを当てる: transformers 4.26.0用
+    org_prepare_input_ids_for_generation = GenerationMixin._prepare_input_ids_for_generation
+    curr_batch_size = [args.batch_size]  # ループの最後で件数がbatch_size未満になるので入れ替えられるように
+
+    # input_idsがバッチサイズと同じ件数である必要がある：バッチサイズはこの関数から参照できないので外から渡す
+    # ここより上で置き換えようとするとすごく大変
+    def _prepare_input_ids_for_generation_patch(self, bos_token_id, encoder_outputs):
+        input_ids = org_prepare_input_ids_for_generation(self, bos_token_id, encoder_outputs)
+        if input_ids.size()[0] != curr_batch_size[0]:
+            input_ids = input_ids.repeat(curr_batch_size[0], 1)
+        return input_ids
+
+    GenerationMixin._prepare_input_ids_for_generation = _prepare_input_ids_for_generation_patch
+    """
+
+    logger.info(f"load images from {args.train_data_dir}")
+    train_data_dir_path = Path(args.train_data_dir)
+    image_paths = train_util.glob_images_pathlib(train_data_dir_path, args.recursive)
+    logger.info(f"found {len(image_paths)} images.")
+
+    # できればcacheに依存せず明示的にダウンロードしたい
+    logger.info(f"loading GIT: {args.model_id}")
+    git_processor = AutoProcessor.from_pretrained(args.model_id)
+    git_model = AutoModelForCausalLM.from_pretrained(args.model_id).to(DEVICE)
+    logger.info("GIT loaded")
+
+    # captioningする
+    def run_batch(path_imgs):
+        imgs = [im for _, im in path_imgs]
+
+        # curr_batch_size[0] = len(path_imgs)
+        inputs = git_processor(images=imgs, return_tensors="pt").to(DEVICE)  # 画像はpil形式
+        generated_ids = git_model.generate(pixel_values=inputs.pixel_values, max_length=args.max_length)
+        captions = git_processor.batch_decode(generated_ids, skip_special_tokens=True)
+
+        if args.remove_words:
+            captions = remove_words(captions, args.debug)
+
+        for (image_path, _), caption in zip(path_imgs, captions):
+            with open(os.path.splitext(image_path)[0] + args.caption_extension, "wt", encoding="utf-8") as f:
+                f.write(caption + "\n")
+                if args.debug:
+                    logger.info(f"{image_path} {caption}")
+
+    # 読み込みの高速化のためにDataLoaderを使うオプション
+    if args.max_data_loader_n_workers is not None:
+        dataset = train_util.ImageLoadingDataset(image_paths)
+        data = torch.utils.data.DataLoader(
+            dataset,
+            batch_size=args.batch_size,
+            shuffle=False,
+            num_workers=args.max_data_loader_n_workers,
+            collate_fn=collate_fn_remove_corrupted,
+            drop_last=False,
+        )
+    else:
+        data = [[(None, ip)] for ip in image_paths]
+
+    b_imgs = []
+    for data_entry in tqdm(data, smoothing=0.0):
+        for data in data_entry:
+            if data is None:
+                continue
+
+            image, image_path = data
+            if image is None:
+                try:
+                    image = Image.open(image_path)
+                    if image.mode != "RGB":
+                        image = image.convert("RGB")
+                except Exception as e:
+                    logger.error(f"Could not load image path / 画像を読み込めません: {image_path}, error: {e}")
+                    continue
+
+            b_imgs.append((image_path, image))
+            if len(b_imgs) >= args.batch_size:
+                run_batch(b_imgs)
+                b_imgs.clear()
+
+    if len(b_imgs) > 0:
+        run_batch(b_imgs)
+
+    logger.info("done!")
+
+
+def setup_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("train_data_dir", type=str, help="directory for train images / 学習画像データのディレクトリ")
+    parser.add_argument("--caption_extension", type=str, default=".caption", help="extension of caption file / 出力されるキャプションファイルの拡張子")
+    parser.add_argument(
+        "--model_id",
+        type=str,
+        default="microsoft/git-large-textcaps",
+        help="model id for GIT in Hugging Face / 使用するGITのHugging FaceのモデルID",
+    )
+    parser.add_argument("--batch_size", type=int, default=1, help="batch size in inference / 推論時のバッチサイズ")
+    parser.add_argument(
+        "--max_data_loader_n_workers",
+        type=int,
+        default=None,
+        help="enable image reading by DataLoader with this number of workers (faster) / DataLoaderによる画像読み込みを有効にしてこのワーカー数を適用する（読み込みを高速化）",
+    )
+    parser.add_argument("--max_length", type=int, default=50, help="max length of caption / captionの最大長")
+    parser.add_argument(
+        "--remove_words",
+        action="store_true",
+        help="remove like `with the words xxx` from caption / `with the words xxx`のような部分をキャプションから削除する",
+    )
+    parser.add_argument("--debug", action="store_true", help="debug mode")
+    parser.add_argument("--recursive", action="store_true", help="search for images in subfolders recursively / サブフォルダを再帰的に検索する")
+
+    return parser
+
+
+if __name__ == "__main__":
+    parser = setup_parser()
+
+    args = parser.parse_args()
+    main(args)