hrnet代码详解关键点生成热图

hrnet代码详解关键点生成热图

AI界扛把子: 主要就是这个方法def decode(self, img_metas, output, **kwargs):

hrnet代码详解关键点生成热图

AI界扛把子: 这是原代码里面的，你按照代码把heatmap输入进去就有热图，具体的代码你要自己抽出来

hrnet代码详解关键点生成热图

不爱吃香菜 爱看论文: 请问是把这些代码放到哪个地方实现呢

rknn量化hrnet流程【人体骨架点检测】

AI界扛把子: 看这篇博客吧，我给你总结了https://blog.csdn.net/qq_16792139/article/details/129701933?csdn_share_tail=%7B%22type%22%3A%22blog%22%2C%22rType%22%3A%22article%22%2C%22rId%22%3A%22129701933%22%2C%22source%22%3A%22qq_16792139%22%7D

rknn量化hrnet流程【人体骨架点检测】

AI界扛把子: def decode(self, img_metas, output, **kwargs): """Decode keypoints from heatmaps. Args: img_metas (list(dict)): Information about data augmentation By default this includes: - "image_file: path to the image file - "center": center of the bbox - "scale": scale of the bbox - "rotation": rotation of the bbox - "bbox_score": score of bbox output (np.ndarray[N, K, H, W]): model predicted heatmaps. """ batch_size = len(img_metas) if 'bbox_id' in img_metas[0]: bbox_ids = [] else: bbox_ids = None c = np.zeros((batch_size, 2), dtype=np.float32) s = np.zeros((batch_size, 2), dtype=np.float32) image_paths = [] score = np.ones(batch_size) for i in range(batch_size): c[i, :] = img_metas[i]['center'] s[i, :] = img_metas[i]['scale']