Accuracy check YML #277
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,110 @@ | ||
| import os | ||
| from datasets import load_dataset | ||
| from huggingface_hub import login | ||
| from PIL import Image | ||
| from collections import defaultdict | ||
|
|
||
| hf_token = os.environ.get('HF_TOKEN') | ||
| if hf_token: | ||
| print("Авторизация на Hugging Face Hub...") | ||
| login(token=hf_token) | ||
| else: | ||
| print("Внимание: HF_TOKEN не найден, могут быть ограничения rate limiting") | ||
|
|
||
| base_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) | ||
| output_dir = os.path.join(base_dir, 'docs', 'ImageNet', 'test') | ||
| os.makedirs(output_dir, exist_ok=True) | ||
|
|
||
| print("Загрузка датасета helenqu/ImageNet-Paste...") | ||
| ds = load_dataset( | ||
| "helenqu/ImageNet-Paste", | ||
| split="validation", | ||
| token=hf_token | ||
| ) | ||
|
|
||
| print(f"Датасет загружен. Всего записей: {len(ds)}") | ||
|
|
||
| print(f"Ключи первой записи: {ds[0].keys()}") | ||
| if 'label' in ds[0]: | ||
| print(f"Пример метки: {ds[0]['label']}") | ||
| print(f"Тип метки: {type(ds[0]['label'])}") | ||
|
|
||
| print("\nСоздание папок для классов 00000-00999 в test/...") | ||
| for i in range(1000): | ||
| class_folder = os.path.join(output_dir, f"{i:05d}") | ||
| os.makedirs(class_folder, exist_ok=True) | ||
| print("Папки созданы!") | ||
|
|
||
| counters = defaultdict(int) | ||
|
|
||
| total_images = len(ds) | ||
| images_per_class = 50 | ||
| max_images = 1000 * images_per_class | ||
|
|
||
| print(f"\nНачинаем сохранение {min(total_images, max_images)} изображений...") | ||
| print(f"По {images_per_class} изображений в каждой из 1000 папок") | ||
| print(f"Путь: {output_dir}/00000/ ... /00999/") | ||
|
|
||
| saved_count = 0 | ||
| skipped_count = 0 | ||
|
|
||
| for i, item in enumerate(ds): | ||
| if saved_count >= max_images: | ||
| print(f"\nДостигнут лимит в {max_images} изображений") | ||
| break | ||
|
|
||
| try: | ||
| image = item['image'] | ||
| if 'label' in item: | ||
| class_id = item['label'] | ||
| elif 'labels' in item: | ||
| class_id = item['labels'] | ||
| else: | ||
| skipped_count += 1 | ||
| if skipped_count % 100 == 0: | ||
| print(f"Пропущено {skipped_count} изображений: нет метки класса") | ||
| continue | ||
|
|
||
| if not isinstance(class_id, (int, float)) or class_id < 0 or class_id >= 1000: | ||
| skipped_count += 1 | ||
| if skipped_count % 100 == 0: | ||
| print(f"Пропущено {skipped_count} изображений: некорректный class_id {class_id}") | ||
| continue | ||
|
|
||
| class_id_int = int(class_id) | ||
|
|
||
| if counters[class_id_int] >= images_per_class: | ||
| continue | ||
|
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| class_folder = os.path.join(output_dir, f"{class_id_int:05d}") | ||
| filename = f"image_{counters[class_id_int]}.jpg" | ||
| output_path = os.path.join(class_folder, filename) | ||
|
|
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| image.save(output_path, 'JPEG') | ||
| counters[class_id_int] += 1 | ||
| saved_count += 1 | ||
|
|
||
| except Exception as e: | ||
| print(f"Ошибка при сохранении изображения {i}: {e}") | ||
| continue | ||
|
|
||
| print(f"\n{'=' * 50}") | ||
| print(f"ГОТОВО!") | ||
| print(f"{'=' * 50}") | ||
| print(f"Всего сохранено: {saved_count} изображений") | ||
| print(f"Пропущено: {skipped_count} изображений") | ||
| print(f"Распределение по первым 10 классам:") | ||
| for class_id in range(10): | ||
| print(f" Класс {class_id:05d}: {counters[class_id]} изображений") | ||
|
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||
| classes_with_50 = sum(1 for c in range(1000) if counters[c] == 50) | ||
| print(f"\nКлассов с ровно 50 изображениями: {classes_with_50}/1000") | ||
|
|
||
| if classes_with_50 < 1000: | ||
| print("\nКлассы с недостаточным количеством:") | ||
| for class_id in range(1000): | ||
| if counters[class_id] < 50 and counters[class_id] > 0: | ||
| print(f" Класс {class_id:05d}: только {counters[class_id]} изображений") | ||
|
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||
| print(f"\nПуть к данным: {output_dir}") | ||
| print(f"Пример: {output_dir}/00042/image_0.jpg") |
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SIGTERM catching mechanism also can be removed already