Download instances.py from Cappystone/yolo_detect: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Cappystone/yolo_detect/resolve/main/instances.py
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hf download hf://datasets/Cappystone/yolo_detect/instances.py
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curl -L -o instances.py https://huggingface.co/datasets/Cappystone/yolo_detect/resolve/main/instances.py
1.74 kB
| import os | |
| from collections import Counter | |
| def count_instances(label_dir): | |
| counts = Counter() | |
| for fname in os.listdir(label_dir): | |
| if fname.endswith(".txt"): | |
| with open(os.path.join(label_dir, fname)) as f: | |
| for line in f: | |
| if line.strip(): | |
| cls_id = line.strip().split()[0] | |
| counts[cls_id] += 1 | |
| return counts | |
| # ------------------------- CONFIG (edit these) ------------------------- | |
| TRAIN_LABELS = r"C:\Users\shrey\Downloads\dataset\labels\train" | |
| VAL_LABELS = r"C:\Users\shrey\Downloads\dataset\labels\val" | |
| TEST_LABELS = r"C:\Users\shrey\Downloads\dataset\labels\test" | |
| # Map class IDs to names for readable output -- confirm against your data.yaml | |
| CLASS_NAMES = { | |
| "0": "plastic_bottle", | |
| "1": "drink_can", | |
| "2": "paper", | |
| } | |
| # ------------------------------------------------------------------------- | |
| def print_counts(label, counts): | |
| print(f"{label}:") | |
| total = sum(counts.values()) | |
| for cls_id in sorted(counts.keys()): | |
| name = CLASS_NAMES.get(cls_id, f"class_{cls_id}") | |
| pct = (counts[cls_id] / total * 100) if total else 0 | |
| print(f" {name:15s} (id {cls_id}): {counts[cls_id]:5d} ({pct:.1f}%)") | |
| print(f" {'TOTAL':15s} : {total:5d}\n") | |
| if __name__ == "__main__": | |
| for label_name, label_dir in [ | |
| ("Train", TRAIN_LABELS), | |
| ("Val", VAL_LABELS), | |
| ("Test", TEST_LABELS), | |
| ]: | |
| if os.path.isdir(label_dir): | |
| counts = count_instances(label_dir) | |
| print_counts(label_name, counts) | |
| else: | |
| print(f"Skipping {label_name} -- folder not found: {label_dir}\n") |