Class MpiSintel

core/utils/datasets.py:122–160

                self.flow_list += sorted(glob(osp.join(flow_root, scene, '*.flo')))

class MpiSintel(FlowDataset):
    def __init__(self, aug_params=None, split='training', root='datasets/Sintel', dstype='clean'):
        super(MpiSintel, self).__init__(aug_params)

        root = 's3://'

        self.image_list = []
        with open("./flow_dataset/Sintel/Sintel_"+dstype+"_png.txt") as f:
            images = f.readlines()
            for img1, img2 in zip(images[0::2], images[1::2]):
                self.image_list.append([root+img1.strip(), root+img2.strip()])
        
        self.flow_list = []
        with open("./flow_dataset/Sintel/Sintel_"+dstype+"_flo.txt") as f:
            flows = f.readlines()
            for flow in flows:
                self.flow_list.append(root+flow.strip())
        
        assert (len(self.image_list) == len(self.flow_list))

        self.extra_info = []
        with open("./flow_dataset/Sintel/Sintel_"+dstype+"_extra_info.txt") as f:
            info = f.readlines()
            for scene, id in zip(info[0::2], info[1::2]):
                self.extra_info.append((scene.strip(), int(id.strip())))
        # flow_root = osp.join(root, split, 'flow')
        # image_root = osp.join(root, split, dstype)

        # if split == 'test':
        #     self.is_test = True

        # for scene in os.listdir(image_root):
        #     image_list = sorted(glob(osp.join(image_root, scene, '*.png')))
        #     for i in range(len(image_list)-1):
        #         self.image_list += [ [image_list[i], image_list[i+1]] ]
        #         self.extra_info += [ (scene, i) ] # scene and frame_id

        #     if split != 'test':
        #         self.flow_list += sorted(glob(osp.join(flow_root, scene, '*.flo')))


class FlyingChairs(FlowDataset):