c
joint_name={
'Hips(髋部)': 0,
'RightUpLeg(右大腿)': 1,
'RightLeg(右小腿)': 2,
'RightFoot(右脚)': 3,
'LeftUpLeg(左大腿)': 4,
'LeftLeg(左小腿)': 5,
'LeftFoot(左脚)': 6,
'Spine(脊柱)': 7,
'Spine1(脊柱1)': 8,
'Neck(颈部)': 9,
'Neck1(颈部1)': 10,
'LeftArm(左臂)': 11,
'LeftForeArm(左前臂)': 12,
'LeftHand(左手)': 13,
'RightArm(右臂)': 14,
'RightForeArm(右前臂)': 15,
'RightHand(右手)': 16
}
coco to h36m:
c
def h36m_coco_format(keypoints, scores):
assert len(keypoints.shape) == 4 and len(scores.shape) == 3
h36m_kpts = []
h36m_scores = []
valid_frames = []
for i in range(keypoints.shape[0]):
kpts = keypoints[i]
score = scores[i]
new_score = np.zeros_like(score, dtype=np.float32)
if np.sum(kpts) != 0.:
kpts, valid_frame = coco_h36m(kpts)
h36m_kpts.append(kpts)
valid_frames.append(valid_frame)
new_score[:, h36m_coco_order] = score[:, coco_order]
new_score[:, 0] = np.mean(score[:, [11, 12]], axis=1, dtype=np.float32)
new_score[:, 8] = np.mean(score[:, [5, 6]], axis=1, dtype=np.float32)
new_score[:, 7] = np.mean(new_score[:, [0, 8]], axis=1, dtype=np.float32)
new_score[:, 10] = np.mean(score[:, [1, 2, 3, 4]], axis=1, dtype=np.float32)
h36m_scores.append(new_score)
h36m_kpts = np.asarray(h36m_kpts, dtype=np.float32)
h36m_scores = np.asarray(h36m_scores, dtype=np.float32)
return h36m_kpts, h36m_scores, valid_frames
可视化:
c
import numpy as np
import cv2
import numpy as np
import json
kpt_color_map = {'h': {'id': 0, 'color': [255, 0, 0], 'radius': 3, 'thickness': -1}, 'tail': {'id': 1, 'color': [0, 255, 0], 'radius': 2, 'thickness': -1}}
# 点类别文字
kpt_labelstr = {'font_size': 1, # 字体大小
'font_thickness': 3, # 字体粗细
'offset_x': 20, # X 方向,文字偏移距离,向右为正
'offset_y': 10, # Y 方向,文字偏移距离,向下为正
}
labelme_path = r'E:\data\new_path\635_5225_02-1\input\0000.json'
with open(labelme_path, 'r', encoding='utf-8') as f:
labelme = json.load(f)
img_bgr=cv2.imread(r'E:\data\new_path\635_5225_02-1\input\0000.png')
for each_ann in labelme['shapes']: # 遍历每一个标注
kpt_label = each_ann['label'] # 该点的类别
for point in each_ann['points']:
kpt_xy = point
kpt_x, kpt_y = int(kpt_xy[0]), int(kpt_xy[1])
# 该点的可视化配置
kpt_color = kpt_color_map[kpt_label]['color'] # 颜色
kpt_radius = kpt_color_map[kpt_label]['radius'] # 半径
kpt_thickness = kpt_color_map[kpt_label]['thickness'] # 线宽(-1代表填充)
# 画圆:画该关键点
img_bgr = cv2.circle(img_bgr, (kpt_x, kpt_y), kpt_radius, kpt_color, kpt_thickness)
# 写该点类别文字:图片,文字字符串,文字左上角坐标,字体,字体大小,颜色,字体粗细
img_bgr = cv2.putText(img_bgr, kpt_label, (kpt_x + kpt_labelstr['offset_x'], kpt_y + kpt_labelstr['offset_y']), cv2.FONT_HERSHEY_SIMPLEX, kpt_labelstr['font_size'], kpt_color, kpt_labelstr['font_thickness'])
cv2.imshow('img',img_bgr)
cv2.waitKey(0)
参考:https://github.com/gauraviiita/Visualization-of-Human3.6M-Dataset/