Update utils/sample_swim.py

utils/sample_swim.py

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+"""
+sample_swim.py
+
+Streams and saves a sample of paired images and labels from a Hugging Face dataset repository.
+
+Default configuration:
+- Repo: "JeffreyJsam/SWiM-SpacecraftWithMasks"
+- Image subdir: "Baseline/images/val/000"
+- Label subdir: "Baseline/labels/val/000"
+- Saves the first 500 matched image/txt files by default.
+
+This script is useful for quick local inspection, prototyping, or lightweight evaluation
+without downloading the full dataset.
+
+Usage:
+    python utils/sample_swim.py --output-dir ./samples --count 100
+
+Arguments:
+    --repo-id          Hugging Face dataset repository ID
+    --image-subdir     Path to image subdirectory inside the dataset repo
+    --label-subdir     Path to corresponding label subdirectory
+    --output-dir       Directory to save downloaded files
+    --count            Number of samples to download
+"""
+
+import argparse
+from io import BytesIO
+from pathlib import Path
+from huggingface_hub import list_repo_tree, hf_hub_url
+from huggingface_hub.hf_api import RepoFile
+import fsspec
+from PIL import Image
+from tqdm import tqdm
+
+def sample_dataset(
+    repo_id: str,
+    image_subdir: str,
+    label_subdir: str,
+    output_dir: str,
+    max_files: int = 500,
+):
+
+
+    
+    image_files = list_repo_tree(
+        repo_id=repo_id,
+        path_in_repo=image_subdir,
+        repo_type="dataset",
+        recursive=True
+    )
+
+    count = 0
+    for img_file in tqdm(image_files, desc="Downloading samples"):
+        if not isinstance(img_file, RepoFile) or not img_file.path.lower().endswith((".png")):
+            continue
+
+        # Relative path after the image_subdir (e.g., img_0001.png)
+        rel_path = Path(img_file.path).relative_to(image_subdir)
+        label_path = f"{label_subdir}/{rel_path.with_suffix('.txt')}"  # Change extension to .txt
+
+        image_url = hf_hub_url(repo_id=repo_id, filename=img_file.path, repo_type="dataset")
+        label_url = hf_hub_url(repo_id=repo_id, filename=label_path, repo_type="dataset")
+
+        local_image_path = Path(output_dir) / img_file.path
+        local_label_path = Path(output_dir) / label_path
+
+        local_image_path.parent.mkdir(parents=True, exist_ok=True)
+        local_label_path.parent.mkdir(parents=True, exist_ok=True)
+
+        try:
+            # Download and save the image
+            with fsspec.open(image_url) as f:
+                image = Image.open(BytesIO(f.read()))
+                image.save(local_image_path)
+
+            # Download and save the corresponding .txt label
+            with fsspec.open(label_url) as f:
+                txt_content = f.read()
+                with open(local_label_path, "wb") as out_f:
+                    out_f.write(txt_content)
+
+#            print(f"[{count+1}]  {rel_path} and {rel_path.with_suffix('.txt')}")
+            count += 1
+        except Exception as e:
+            print(f" Failed {rel_path}: {e}")
+
+        if count >= max_files:
+            break
+
+    print(f" Downloaded {count} image/txt pairs.")
+    print(f" Saved under: {Path(output_dir).resolve()}")
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="Stream and sample paired images + txt labels from a Hugging Face folder-structured dataset.")
+    parser.add_argument("--repo-id", required=False, default = "JeffreyJsam/SWiM-SpacecraftWithMasks",help="Hugging Face dataset repo ID.")
+    parser.add_argument("--image-subdir", required=False, default = "Baseline/images/val/000", help="Subdirectory path for images.")
+    parser.add_argument("--label-subdir", required=False, default="Baseline/labels/val/000", help="Subdirectory path for txt masks.")
+    parser.add_argument("--output-dir", default="./Sampled-SWiM", help="Where to save sampled data.")
+    parser.add_argument("--count", type=int, default=500, help="How many samples to download.")
+    return parser.parse_args()
+
+if __name__ == "__main__":
+    args = parse_args()
+    sample_dataset(
+        repo_id=args.repo_id,
+        image_subdir=args.image_subdir,
+        label_subdir=args.label_subdir,
+        output_dir=args.output_dir,
+        max_files=args.count,
+    )