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import numpy as np |
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from mmengine.testing import assert_allclose |
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from mmdet.structures.bbox import BaseBoxes, HorizontalBoxes |
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from mmdet.structures.mask import BitmapMasks, PolygonMasks |
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def create_random_bboxes(num_bboxes, img_w, img_h): |
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bboxes_left_top = np.random.uniform(0, 0.5, size=(num_bboxes, 2)) |
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bboxes_right_bottom = np.random.uniform(0.5, 1, size=(num_bboxes, 2)) |
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bboxes = np.concatenate((bboxes_left_top, bboxes_right_bottom), 1) |
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bboxes = (bboxes * np.array([img_w, img_h, img_w, img_h])).astype( |
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np.float32) |
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return bboxes |
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def create_full_masks(gt_bboxes, img_w, img_h): |
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xmin, ymin = gt_bboxes[:, 0:1], gt_bboxes[:, 1:2] |
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xmax, ymax = gt_bboxes[:, 2:3], gt_bboxes[:, 3:4] |
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gt_masks = np.zeros((len(gt_bboxes), img_h, img_w), dtype=np.uint8) |
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for i in range(len(gt_bboxes)): |
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gt_masks[i, int(ymin[i]):int(ymax[i]), int(xmin[i]):int(xmax[i])] = 1 |
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gt_masks = BitmapMasks(gt_masks, img_h, img_w) |
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return gt_masks |
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def construct_toy_data(poly2mask, use_box_type=False): |
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img = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], |
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dtype=np.uint8) |
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img = np.stack([img, img, img], axis=-1) |
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results = dict() |
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results['img'] = img |
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results['img_shape'] = img.shape[:2] |
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if use_box_type: |
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results['gt_bboxes'] = HorizontalBoxes( |
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np.array([[1, 0, 2, 2]], dtype=np.float32)) |
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else: |
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results['gt_bboxes'] = np.array([[1, 0, 2, 2]], dtype=np.float32) |
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results['gt_bboxes_labels'] = np.array([13], dtype=np.int64) |
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if poly2mask: |
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gt_masks = np.array([[0, 1, 0, 0], [0, 1, 1, 0], [0, 1, 0, 0]], |
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dtype=np.uint8)[None, :, :] |
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results['gt_masks'] = BitmapMasks(gt_masks, 3, 4) |
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else: |
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raw_masks = [[np.array([1, 2, 1, 0, 2, 1], dtype=np.float32)]] |
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results['gt_masks'] = PolygonMasks(raw_masks, 3, 4) |
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results['gt_ignore_flags'] = np.array(np.array([1], dtype=bool)) |
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results['gt_seg_map'] = np.array( |
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[[255, 13, 255, 255], [255, 13, 13, 255], [255, 13, 255, 255]], |
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dtype=np.uint8) |
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return results |
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def check_result_same(results, pipeline_results, check_keys): |
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"""Check whether the ``pipeline_results`` is the same with the predefined |
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``results``. |
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Args: |
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results (dict): Predefined results which should be the standard |
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output of the transform pipeline. |
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pipeline_results (dict): Results processed by the transform |
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pipeline. |
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check_keys (tuple): Keys that need to be checked between |
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results and pipeline_results. |
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""" |
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for key in check_keys: |
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if results.get(key, None) is None: |
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continue |
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if isinstance(results[key], (BitmapMasks, PolygonMasks)): |
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assert_allclose(pipeline_results[key].to_ndarray(), |
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results[key].to_ndarray()) |
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elif isinstance(results[key], BaseBoxes): |
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assert_allclose(pipeline_results[key].tensor, results[key].tensor) |
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else: |
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assert_allclose(pipeline_results[key], results[key]) |
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