(self)
| 132 | self.assertEqual(output.shape, img.shape) |
| 133 | |
| 134 | def test_draw_no_metadata(self): |
| 135 | img, boxes, _, _, masks = self._random_data() |
| 136 | num_inst = len(boxes) |
| 137 | inst = Instances((img.shape[0], img.shape[1])) |
| 138 | inst.pred_classes = torch.randint(0, 80, size=(num_inst,)) |
| 139 | inst.scores = torch.rand(num_inst) |
| 140 | inst.pred_boxes = torch.from_numpy(boxes) |
| 141 | inst.pred_masks = torch.from_numpy(np.asarray(masks)) |
| 142 | |
| 143 | v = Visualizer(img, MetadataCatalog.get("asdfasdf")) |
| 144 | v.draw_instance_predictions(inst) |
| 145 | |
| 146 | def test_draw_binary_mask(self): |
| 147 | img, boxes, _, _, masks = self._random_data() |
nothing calls this directly
no test coverage detected