def __getitem__(self, index): img = ImageHelper.pil_open_rgb(self.img_list[index]) if os.path.exists(self.mask_list[index]): maskmap = ImageHelper.pil_open_p(self.mask_list[index]) else: maskmap = ImageHelper.np2img(np.ones((img.size[1], img.size[0]), dtype=np.uint8)) kpts, bboxes = self.__read_json_file(self.json_list[index]) if self.aug_transform is not None and len(bboxes) > 0: img, maskmap, kpts, bboxes = self.aug_transform(img, mask=maskmap, kpts=kpts, bboxes=bboxes) elif self.aug_transform is not None: img, maskmap, kpts = self.aug_transform(img, mask=maskmap, kpts=kpts) width, height = maskmap.size maskmap = ImageHelper.resize(maskmap, (width // self.configer.get('network', 'stride'), height // self.configer.get('network', 'stride')), Image.NEAREST) maskmap = np.expand_dims(np.array(maskmap, dtype=np.float32), axis=2) heatmap = self.pose_data_utilizer.generate_heatmap(kpts=kpts, mask=maskmap) vecmap = self.pose_data_utilizer.generate_paf(kpts=kpts, mask=maskmap) if self.img_transform is not None: img = self.img_transform(img) if self.label_transform is not None: heatmap = self.label_transform(heatmap) vecmap = self.label_transform(vecmap) maskmap = self.label_transform(maskmap) return img, heatmap, maskmap, vecmap
def __getitem__(self, index): img = ImageHelper.pil_open_rgb(self.img_list[index]) label = ImageHelper.pil_open_p(self.label_list[index]) if self.aug_transform is not None: img, label = self.aug_transform(img, label=label) if self.img_transform is not None: img = self.img_transform(img) if self.label_transform is not None: label = self.label_transform(label) return img, label