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# === Вот эта связка нужна для всех исполняемых скриптов внутри библиотеки, которая будет использоваться как сабмодуль ===
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import sys
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from pathlib import Path
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ROOT = Path(__file__).parent.parent
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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# === перед вмеми импортами ===
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import cv2
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import os
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import csv
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import argparse
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from skeleton.mediapipe_detector import MediaPipeDetector
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from ml_gestures.feature_extractor import normalize_landmarks
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def main():
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parser = argparse.ArgumentParser(description='Разметка изображений для обучения')
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parser.add_argument('--folder', required=True, help='Папка с изображениями')
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parser.add_argument('--classes', default='dome,cross,none',
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help='Список классов через запятую')
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parser.add_argument('--output', default='gesture_data.csv',
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help='Имя выходного CSV-файла')
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parser.add_argument('--max_display_size', default='800,600',
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help='Максимальный размер для отображения (ширина,высота)')
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args = parser.parse_args()
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classes = [c.strip() for c in args.classes.split(',')]
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key_to_class = {str(i+1): cls for i, cls in enumerate(classes)}
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print("Классы:", classes)
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detector = MediaPipeDetector()
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max_width, max_height = map(int, args.max_display_size.split(','))
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image_extensions = ('.jpg', '.jpeg', '.png', '.bmp')
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image_files = [f for f in os.listdir(args.folder) if f.lower().endswith(image_extensions)]
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image_files.sort()
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print(f"Найдено {len(image_files)} изображений.")
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csv_file = args.output
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file_exists = os.path.isfile(csv_file)
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if not file_exists:
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with open(csv_file, 'w', newline='', encoding='utf-8') as f:
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writer = csv.writer(f)
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writer.writerow(['class'] + [f'f{i}' for i in range(99)])
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for idx, filename in enumerate(image_files):
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filepath = os.path.join(args.folder, filename)
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print(f"\n[{idx+1}/{len(image_files)}] {filename}")
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image = cv2.imread(filepath)
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if image is None:
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print("Не удалось загрузить")
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continue
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result = detector.detect(image)
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if result['success']:
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landmarks = result['landmarks']
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features = normalize_landmarks(landmarks)
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vis_image = detector.draw_landmarks(image.copy(), result['pose_landmarks'])
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else:
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vis_image = image.copy()
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landmarks = None
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# Масштабирование для отображения
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h, w = vis_image.shape[:2]
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scale = min(max_width / w, max_height / h, 1.0)
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if scale < 1.0:
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new_w = int(w * scale)
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new_h = int(h * scale)
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display = cv2.resize(vis_image, (new_w, new_h))
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else:
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display = vis_image.copy()
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# Панель с инструкцией
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dh, dw = display.shape[:2]
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overlay = display.copy()
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cv2.rectangle(overlay, (0, dh-80), (dw, dh), (50,50,50), -1)
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cv2.addWeighted(overlay, 0.6, display, 0.4, 0, display)
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y = dh - 60
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for i, cls in enumerate(classes):
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cv2.putText(display, f"{i+1}:{cls}", (10 + i*120, y),
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255,255,255), 2)
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cv2.putText(display, "n:skip q:quit", (10, y+30),
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255,255,0), 2)
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cv2.imshow('Annotation', display)
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key = cv2.waitKey(0) & 0xFF
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cv2.destroyAllWindows()
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if key == ord('q'):
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break
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elif key == ord('n'):
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continue
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else:
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key_char = chr(key) if key < 256 else None
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if key_char in key_to_class:
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selected = key_to_class[key_char]
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with open(csv_file, 'a', newline='', encoding='utf-8') as f:
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writer = csv.writer(f)
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writer.writerow([selected] + features.tolist())
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print(f"Сохранено: {selected}")
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else:
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print("Неверная клавиша")
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print("Готово.")
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if __name__ == '__main__':
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main()
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