目录

coco转h36m人体关键点

opencv 2d关键点可视化

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coco转h36m人体关键点

mhformer中有

def h36m_coco_format(keypoints, scores):assert len(keypoints.shape) == 4 and len(scores.shape) == 3h36m_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

opencv 2d关键点可视化

import numpy as npimport cv2
import numpy as np
import jsonkpt_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 = pointkpt_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)