readme + models

2026-03-23 17:15:35 +03:00
parent ef0b817a74
commit 5e1c1341aa
5 changed files with 151 additions and 120 deletions
@@ -1,95 +0,0 @@
-import cv2
-import os
-import csv
-import sys
-from pathlib import Path
-import argparse
-
-sys.path.append(str(Path(__file__).parent.parent))
-from skeleton.mediapipe_detector import MediaPipeDetector
-from ml_gestures.feature_extractor import normalize_landmarks
-
-def main():
-    parser = argparse.ArgumentParser(description='Разметка изображений для обучения')
-    parser.add_argument('--folder', required=True, help='Папка с изображениями')
-    parser.add_argument('--classes', default='dome,cross,none',
-                        help='Список классов через запятую')
-    parser.add_argument('--output', default='gesture_data.csv',
-                        help='Имя выходного CSV-файла')
-    args = parser.parse_args()
-
-    classes = [c.strip() for c in args.classes.split(',')]
-    key_to_class = {str(i+1): cls for i, cls in enumerate(classes)}
-    print("Классы:", classes)
-
-    detector = MediaPipeDetector()
-
-    image_extensions = ('.jpg', '.jpeg', '.png', '.bmp')
-    image_files = [f for f in os.listdir(args.folder) if f.lower().endswith(image_extensions)]
-    image_files.sort()
-    print(f"Найдено {len(image_files)} изображений.")
-
-    csv_file = args.output
-    file_exists = os.path.isfile(csv_file)
-    if not file_exists:
-        with open(csv_file, 'w', newline='', encoding='utf-8') as f:
-            writer = csv.writer(f)
-            # 99 признаков (33 точки * 3 координаты)
-            writer.writerow(['class'] + [f'f{i}' for i in range(99)])
-
-    for idx, filename in enumerate(image_files):
-        filepath = os.path.join(args.folder, filename)
-        print(f"\n[{idx+1}/{len(image_files)}] {filename}")
-
-        image = cv2.imread(filepath)
-        if image is None:
-            continue
-
-        result = detector.detect(image)
-        if not result['success']:
-            cv2.imshow('No skeleton', image)
-            cv2.waitKey(0)
-            cv2.destroyAllWindows()
-            continue
-
-        landmarks = result['landmarks']
-        features = normalize_landmarks(landmarks)   # вектор из 99 чисел
-
-        display = detector.draw_landmarks(image, result['pose_landmarks'])
-        h, w = display.shape[:2]
-
-        # Панель с инструкцией
-        overlay = display.copy()
-        cv2.rectangle(overlay, (0, h-80), (w, h), (50,50,50), -1)
-        cv2.addWeighted(overlay, 0.6, display, 0.4, 0, display)
-
-        y = h - 60
-        for i, cls in enumerate(classes):
-            cv2.putText(display, f"{i+1}:{cls}", (10 + i*120, y),
-                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255,255,255), 2)
-        cv2.putText(display, "n:skip  q:quit", (10, y+30),
-                    cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255,255,0), 2)
-
-        cv2.imshow('Annotation', display)
-        key = cv2.waitKey(0) & 0xFF
-        cv2.destroyAllWindows()
-
-        if key == ord('q'):
-            break
-        elif key == ord('n'):
-            continue
-        else:
-            key_char = chr(key) if key < 256 else None
-            if key_char in key_to_class:
-                selected = key_to_class[key_char]
-                with open(csv_file, 'a', newline='', encoding='utf-8') as f:
-                    writer = csv.writer(f)
-                    writer.writerow([selected] + features.tolist())
-                print(f"Сохранено: {selected}")
-            else:
-                print("Неверная клавиша")
-
-    print("Готово.")
-
-if __name__ == '__main__':
-    main()