if masks is not None and masks.shape[0] > 0: for label, score, seg in zip(class_ids, conf, masks): # 解析分割掩码 mask = seg[0] # 取第一个对象的分割掩码 mask = mask.astype(np.uint8) # 将掩码转换为无符号整数类型 _, mask_binary = cv2.threshold(mask, 0, 255, cv2.THRESH_BINARY) # 将掩码转换为二值图像 # 获取分割多边形 contours, _ = cv2.findContours(mask_binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) contour = contours[0] if len(contours) > 0 else [] # 将分割多边形的点坐标转换为列表的点(points)形式 points = [[int(coord[0]), int(coord[1])] for coord in contour.squeeze().tolist()] if len(contour) > 0 else [] results.append({ "confidence": str(score), "label": labels.get(label, "unknown"), "points": points, "type": "polygon", "mask": mask.tolist() # 将分割掩码转换为列表形式 })mask是三维数组 改一下代码
时间: 2024-04-18 08:23:34 浏览: 10
如果mask不为None且mask的形状的第一个维度大于0:
对于label、score和seg中的每个元素进行循环:
# 解析分割掩码
mask = seg[0] # 取第一个对象的分割掩码
mask = mask.astype(np.uint8) # 将掩码转换为无符号整数类型
_, mask_binary = cv2.threshold(mask, 0, 255, cv2.THRESH_BINARY) # 将掩码转换为二值图像
# 获取分割多边形
contours, _ = cv2.findContours(mask_binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contour = contours[0] if len(contours) > 0 else []
# 将分割多边形的点坐标转换为列表的点(points)形式
points = [[int(coord[0]), int(coord[1])] for coord in contour.squeeze().tolist()] if len(contour) > 0 else []
results.append({
"confidence": str(score),
"label": labels.get(label, "unknown"),
"points": points,
"type": "polygon",
"mask": mask.tolist() # 将分割掩码转换为列表形式
})