Generate script

generate_webdataset.py

@@ -0,0 +1,110 @@
+"""
+Script to generate WebDataset tar shards from images.
+"""
+
+import argparse
+import pickle
+import json
+import tarfile
+from pathlib import Path
+from io import BytesIO
+
+import torch
+from torch.utils.data import DataLoader
+from torchvision.transforms import ToPILImage
+from PIL import Image
+from tqdm import tqdm
+
+from custom_datasets import OnlineFontSquare, TextSampler
+
+def parse_arguments():
+    """Parses command-line arguments."""
+    parser = argparse.ArgumentParser(description='Generate WebDataset tar shards from images')
+    parser.add_argument('--output_dir', type=str, default='/home/vpippi/font-square-v2/tars/fine_tune', help='Output directory')
+    parser.add_argument('--fonts', type=str, default='files/font_square/clean_fonts', help='Fonts path')
+    parser.add_argument('--backgrounds', type=str, default='files/font_square/backgrounds', help='Backgrounds path')
+    parser.add_argument('--renderers', type=str, help='Renderers path')
+    parser.add_argument('--db_multiplier', type=int, default=1, help='Dataset multiplier')
+    parser.add_argument('--dataloader_num_workers', type=int, default=15, help='Dataloader num workers')
+    parser.add_argument('--shard_size', type=int, default=4000, help='Samples per tar shard')
+    return parser.parse_args()
+
+def setup_dataset(args):
+    """Initializes dataset and sampler."""
+    sampler = TextSampler(4, 128, (1, 32))
+    
+    renderers = None
+    if args.renderers:
+        with open(args.renderers, 'rb') as f:
+            renderers = pickle.load(f)
+
+    dataset = OnlineFontSquare(args.fonts, args.backgrounds, sampler, renderers=renderers)
+    dataset.length *= args.db_multiplier
+    return dataset
+
+def add_bytes_to_tar(tar, filename, data_bytes):
+    """Adds a file to the tar archive."""
+    ti = tarfile.TarInfo(name=filename)
+    ti.size = len(data_bytes)
+    tar.addfile(ti, BytesIO(data_bytes))
+
+def process_samples(loader, args):
+    """Processes dataset samples and writes them into tar shards."""
+    output_dir = Path(args.output_dir)
+    output_dir.mkdir(parents=True, exist_ok=True)
+    to_pil = ToPILImage()
+
+    shard_idx, sample_in_shard, total_samples = 0, 0, 0
+    tar_path = output_dir / f'{shard_idx:06d}.tar'
+    tar = tarfile.open(tar_path, mode='w')
+
+    try:
+        for sample in tqdm(loader, desc="Processing samples"):
+            text = sample['text'][0].strip()
+            rgb_img_tensor = sample['img'][0]
+            bw_img_tensor = sample['text_img'][0]
+            writer_id = sample['writer'][0].item()
+
+            key = f'{sample_in_shard:06d}'
+            rgb_pil = to_pil((rgb_img_tensor + 1) / 2)
+            bw_pil = to_pil((bw_img_tensor + 1) / 2)
+
+            rgb_bytes_io = BytesIO()
+            rgb_pil.save(rgb_bytes_io, format='PNG')
+            rgb_bytes = rgb_bytes_io.getvalue()
+
+            bw_bytes_io = BytesIO()
+            bw_pil.save(bw_bytes_io, format='PNG')
+            bw_bytes = bw_bytes_io.getvalue()
+
+            metadata = json.dumps({"text": text, "writer_id": writer_id}).encode('utf-8')
+
+            add_bytes_to_tar(tar, f'{key}.rgb.png', rgb_bytes)
+            add_bytes_to_tar(tar, f'{key}.bw.png', bw_bytes)
+            add_bytes_to_tar(tar, f'{key}.json', metadata)
+
+            sample_in_shard += 1
+            total_samples += 1
+
+            if sample_in_shard >= args.shard_size:
+                tar.close()
+                shard_idx += 1
+                sample_in_shard = 0
+                tar_path = output_dir / f'{shard_idx:06d}.tar'
+                tar = tarfile.open(tar_path, mode='w')
+    
+    except KeyboardInterrupt:
+        print("Interrupted by user.")
+    finally:
+        tar.close()
+
+    print(f"Finished writing {total_samples} samples in {shard_idx+1} tar shards into {output_dir}")
+
+def main():
+    args = parse_arguments()
+    dataset = setup_dataset(args)
+    loader = DataLoader(dataset, batch_size=1, shuffle=False, num_workers=args.dataloader_num_workers)
+    process_samples(loader, args)
+
+if __name__ == '__main__':
+    main()