Download scripts/download_examples from Pro-Coder/skin_ai: direct link, hf CLI and curl.
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https://huggingface.co/spaces/Pro-Coder/skin_ai/resolve/main/scripts/download_examples
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hf download hf://spaces/Pro-Coder/skin_ai/scripts/download_examples
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curl -L -o download_examples https://huggingface.co/spaces/Pro-Coder/skin_ai/resolve/main/scripts/download_examples
1.64 kB
| """ | |
| Run this ONCE, locally, before you deploy the Space, to populate the | |
| examples/ folder with a handful of sample skin-lesion images so users | |
| have something to click on without needing their own photo. | |
| Usage: | |
| pip install datasets pillow | |
| python scripts/download_examples.py | |
| This pulls a few images (streaming, no full download) from the public | |
| "marmal88/skin_cancer" dataset on the Hugging Face Hub and saves them as | |
| JPEGs into ../examples/. You can also just drop your own sample images | |
| into that folder instead — any .jpg/.jpeg/.png works. | |
| """ | |
| import os | |
| from datasets import load_dataset | |
| OUT_DIR = os.path.join(os.path.dirname(__file__), "..", "examples") | |
| NUM_EXAMPLES = 6 | |
| DATASET_ID = "marmal88/skin_cancer" | |
| def main(): | |
| os.makedirs(OUT_DIR, exist_ok=True) | |
| print(f"Streaming a few samples from {DATASET_ID} ...") | |
| ds = load_dataset(DATASET_ID, split="test", streaming=True) | |
| seen_labels = set() | |
| count = 0 | |
| for example in ds: | |
| if count >= NUM_EXAMPLES: | |
| break | |
| img = example.get("image") | |
| label = str(example.get("dx", example.get("label", count))) | |
| if img is None: | |
| continue | |
| # try to get a spread of different classes rather than duplicates | |
| if label in seen_labels and len(seen_labels) < NUM_EXAMPLES: | |
| continue | |
| seen_labels.add(label) | |
| path = os.path.join(OUT_DIR, f"example_{count:02d}_{label}.jpg") | |
| img.convert("RGB").save(path, "JPEG") | |
| print(f" saved {path}") | |
| count += 1 | |
| print(f"Done — {count} example image(s) saved to {OUT_DIR}") | |
| if __name__ == "__main__": | |
| main() |