79 lines
2.0 KiB
Python
79 lines
2.0 KiB
Python
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import cv2
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import mediapipe as mp
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import json
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# Initialize MediaPipe pose module
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mp_pose = mp.solutions.pose
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pose = mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5)
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mp_drawing = mp.solutions.drawing_utils
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# Load and process the image
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image_path = 'gerakan/Childs.jpg'
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image = cv2.imread(image_path)
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image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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image_results = pose.process(image_rgb)
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# Extract landmarks from the image
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def extract_landmarks(results):
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if not results.pose_landmarks:
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return None
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landmarks = []
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for lm in results.pose_landmarks.landmark:
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landmarks.append((lm.x, lm.y, lm.z))
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return landmarks
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image_landmarks = extract_landmarks(image_results)
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# Define mapping between landmark indices and body parts
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landmark_labels = {
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0: 'nose',
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1: 'left_eye_inner',
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2: 'left_eye',
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3: 'left_eye_outer',
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4: 'right_eye_inner',
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5: 'right_eye',
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6: 'right_eye_outer',
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7: 'left_ear',
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8: 'right_ear',
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9: 'mouth_left',
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10: 'mouth_right',
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11: 'left_shoulder',
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12: 'right_shoulder',
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13: 'left_elbow',
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14: 'right_elbow',
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15: 'left_wrist',
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16: 'right_wrist',
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17: 'left_pinky',
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18: 'right_pinky',
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19: 'left_index',
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20: 'right_index',
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21: 'left_thumb',
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22: 'right_thumb',
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23: 'left_hip',
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24: 'right_hip',
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25: 'left_knee',
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26: 'right_knee',
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27: 'left_ankle',
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28: 'right_ankle',
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29: 'left_heel',
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30: 'right_heel',
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31: 'left_foot_index',
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32: 'right_foot_index'
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}
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# Map landmark indices to descriptive labels
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descriptive_landmarks = [{'body': landmark_labels.get(idx, 'unknown'), 'coordinates': coord} for idx, coord in enumerate(image_landmarks)]
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# Prepare landmark coordinates data
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landmark_data = {
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'image_name': image_path,
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'landmarks': descriptive_landmarks
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}
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# Save landmark coordinates to a variable and print as JSON
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landmark_coordinates = json.dumps(landmark_data, indent=4)
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print(landmark_coordinates)
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# Release resources
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pose.close()
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