基于Labelme的动物骨架绘制

文章目录

• ​​1. Labelme安装​​
• ​​2. 激活labelme​​
• ​​3. 关键点和骨架设置​​
• ​​4. 代码可视化​​

1. Labelme安装

pip install labelme

2. 激活labelme

labelme

选择创建关键点

3. 关键点和骨架设置

4. 代码可视化

import json
import matplotlib.pyplot as plt
import numpy as np
import cv2
from tqdm import tqdm
from pycocotools import coco

paf = {"nose": 1,
       "rightEar": 2,
        "leftEar": 3,
       "back": 4,
       "ass": 5,
       "rightLeg": 6,
       "leftLeg": 7}


def show_skelenton(img, kpts, color=(255, 128, 128), thr=0.01):
    kpts = np.array(kpts).reshape(-1, 3)
    # skelenton = [[16, 14], [14, 12], [17, 15], [15, 13], [12, 13], [6, 12], [7, 13], [6, 7], [6, 8], [7, 9], [8, 10],
    #                 [9, 11], [2, 3], [1, 2], [1, 3], [2, 4], [3, 5], [4, 6], [5, 7]]
    skelenton = [[1, 2], [1, 3], [2, 3], [4, 2], [4, 3], [4, 5], [4, 6], [4, 7]]

    for sk in skelenton:
        pos1 = (int(kpts[sk[0] - 1, 0]), int(kpts[sk[0] - 1, 1]))
        pos2 = (int(kpts[sk[1] - 1, 0]), int(kpts[sk[1] - 1, 1]))
        if pos1[0]>0 and pos1[1] > 0 and pos2[0] > 0 and pos2[1] > 0 and kpts[sk[0] - 1, 2] > thr and kpts[sk[1] - 1, 0] > thr:
            cv2.line(img, pos1, pos2, color, 2, 8)
    return img


if __name__ == '__main__':
    jsonPath = r"D:\2022\4\mouse_pose_v2\data\img00179.json"
    imgPath = r"D:\2022\4\mouse_pose_v2\data\img00179.png"
    img = cv2.imread(imgPath)

    with open(jsonPath) as f:
        data = json.load(f)
    shapes = data["shapes"]

    temp_keypoints = {"nose": [0, 0, 0],
           "rightEar": [0, 0, 0],
           "leftEar": [0, 0, 0],
           "back": [0, 0, 0],
           "ass": [0, 0, 0],
           "rightLeg": [0, 0, 0],
           "leftLeg": [0, 0, 0]}
    for shape in shapes:
        labelName = shape["label"]
        sub_keypoint = shape["points"][0]
        x = int(sub_keypoint[0])
        y = int(sub_keypoint[1])
        temp_keypoints[labelName] = [x, y, 2]
    keypoints = []
    for k, vs in temp_keypoints.items():
        for v in vs:
            keypoints.append(v)
    img = show_skelenton(img, keypoints, color=(255, 0, 255))
    plt.imshow(img)
    plt.show()