def extend_with_flipped_entries(roidb, dataset): """Flip each entry in the given roidb and return a new roidb that is the concatenation of the original roidb and the flipped entries. "Flipping" an entry means that that image and associated metadata (e.g., ground truth boxes and object proposals) are horizontally flipped. """ flipped_roidb = [] for entry in roidb: width = entry['width'] boxes = entry['boxes'].copy() oldx1 = boxes[:, 0].copy() oldx2 = boxes[:, 2].copy() boxes[:, 0] = width - oldx2 - 1 boxes[:, 2] = width - oldx1 - 1 assert (boxes[:, 2] >= boxes[:, 0]).all() flipped_entry = {} dont_copy = ('boxes', 'segms', 'gt_keypoints', 'flipped') for k, v in entry.items(): if k not in dont_copy: flipped_entry[k] = v flipped_entry['boxes'] = boxes flipped_entry['segms'] = segm_utils.flip_segms(entry['segms'], entry['height'], entry['width']) if dataset.keypoints is not None: flipped_entry['gt_keypoints'] = keypoint_utils.flip_keypoints( dataset.keypoints, dataset.keypoint_flip_map, entry['gt_keypoints'], entry['width']) flipped_entry['flipped'] = True flipped_roidb.append(flipped_entry) roidb.extend(flipped_roidb)
def extend_with_flipped_entries(roidb, dataset): """Flip each entry in the given roidb and return a new roidb that is the concatenation of the original roidb and the flipped entries. "Flipping" an entry means that that image and associated metadata (e.g., ground truth boxes and object proposals) are horizontally flipped. """ flipped_roidb = [] for entry in roidb: width = entry['width'] boxes = entry['boxes'].copy() oldx1 = boxes[:, 0].copy() oldx2 = boxes[:, 2].copy() boxes[:, 0] = width - oldx2 - 1 boxes[:, 2] = width - oldx1 - 1 assert (boxes[:, 2] >= boxes[:, 0]).all() flipped_entry = {} dont_copy = ('boxes', 'segms', 'gt_keypoints', 'flipped') for k, v in entry.items(): if k not in dont_copy: flipped_entry[k] = v flipped_entry['boxes'] = boxes flipped_entry['segms'] = segm_utils.flip_segms( entry['segms'], entry['height'], entry['width'] ) if dataset.keypoints is not None: flipped_entry['gt_keypoints'] = keypoint_utils.flip_keypoints( dataset.keypoints, dataset.keypoint_flip_map, entry['gt_keypoints'], entry['width'] ) flipped_entry['flipped'] = True flipped_roidb.append(flipped_entry) roidb.extend(flipped_roidb)
def extend_with_flipped_entries(roidb, dataset): """Flip each entry in the given roidb and return a new roidb that is the concatenation of the original roidb and the flipped entries. "Flipping" an entry means that that image and associated metadata (e.g., ground truth boxes and object proposals) are horizontally flipped. """ flipped_roidb = [] for entry in roidb: width = entry['width'] boxes = entry['boxes'].copy() oldx1 = boxes[:, 0].copy() oldx2 = boxes[:, 2].copy() boxes[:, 0] = width - oldx2 - 1 boxes[:, 2] = width - oldx1 - 1 assert (boxes[:, 2] >= boxes[:, 0]).all() flipped_entry = {} dont_copy = ('boxes', 'segms', 'gt_keypoints', 'flipped') # original if not cfg.Ignore_left: # when filpped, the right is changed to left dont_copy = ('boxes', 'gt_keypoints', 'flipped', 'gt_classes', 'max_classes', 'gt_overlaps') gt_classes_ = copy.deepcopy(entry['gt_classes']) gt_classes = copy.deepcopy(entry['gt_classes']) max_classes = copy.deepcopy(entry['max_classes']) gt_overlaps = copy.deepcopy(entry['gt_overlaps']) dataset_name = cfg.TRAIN.DATASETS[0] if 'LIP' in dataset_name: orig_class_2_flipped = { 14: 15, 15: 14, 16: 17, 17: 16, 18: 19, 19: 18 } if 'ATR' in dataset_name: orig_class_2_flipped = { 9: 10, 10: 9, 12: 13, 13: 12, 14: 15, 15: 14 } for i in orig_class_2_flipped.keys(): idx = np.where(gt_classes_ == i)[0] if len(idx) == 0: continue gt_classes[idx] = orig_class_2_flipped[i] max_classes[idx] = orig_class_2_flipped[i] gt_overlaps[idx, i] = 0 gt_overlaps[idx, orig_class_2_flipped[i]] = 1 flipped_entry['gt_classes'] = gt_classes flipped_entry['max_classes'] = max_classes flipped_entry['gt_overlaps'] = gt_overlaps for k, v in entry.items(): if k not in dont_copy: flipped_entry[k] = v flipped_entry['boxes'] = boxes # flipped_entry['segms'] = segm_utils.flip_segms( # entry['segms'], entry['height'], entry['width'] # ) if dataset.keypoints is not None: flipped_entry['gt_keypoints'] = keypoint_utils.flip_keypoints( dataset.keypoints, dataset.keypoint_flip_map, entry['gt_keypoints'], entry['width']) flipped_entry['flipped'] = True flipped_roidb.append(flipped_entry) roidb.extend(flipped_roidb)