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Method __call__

data/coco.py:49–72  ·  view source on GitHub ↗

Args: target (dict): COCO target json annotation as a python dict height (int): height width (int): width Returns: a list containing lists of bounding boxes [bbox coords, class idx]

(self, target, width, height)

Source from the content-addressed store, hash-verified

47 self.label_map = get_label_map(osp.join(COCO_ROOT, 'coco_labels.txt'))
48
49 def __call__(self, target, width, height):
50 """
51 Args:
52 target (dict): COCO target json annotation as a python dict
53 height (int): height
54 width (int): width
55 Returns:
56 a list containing lists of bounding boxes [bbox coords, class idx]
57 """
58 scale = np.array([width, height, width, height])
59 res = []
60 for obj in target:
61 if 'bbox' in obj:
62 bbox = obj['bbox']
63 bbox[2] += bbox[0]
64 bbox[3] += bbox[1]
65 label_idx = self.label_map[obj['category_id']] - 1
66 final_box = list(np.array(bbox)/scale)
67 final_box.append(label_idx)
68 res += [final_box] # [xmin, ymin, xmax, ymax, label_idx]
69 else:
70 print("no bbox problem!")
71
72 return res # [[xmin, ymin, xmax, ymax, label_idx], ... ]
73
74
75class COCODetection(data.Dataset):

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