[Feature] Support 300VW Dataset #2998
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xiexinch
reviewed
Apr 1, 2024
Comment on lines
148
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170
| def test_annotation(self): | ||
| dataset = self.build_face_300vw_dataset( | ||
| data_mode='topdown', test_mode=True) | ||
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| meta = { | ||
| 'keypoint_id2name': None, | ||
| 'keypoint_name2id': None, | ||
| 'keypoint_colors': [(255, 255, 255)], | ||
| 'skeleton_links': None, | ||
| 'skeleton_link_colors': None | ||
| } | ||
| visualizer = FastVisualizer(meta, radius=1) | ||
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| vis_dir = os.path.join(os.path.dirname(dataset.ann_file), 'vis') | ||
| os.makedirs(vis_dir, exist_ok=True) | ||
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| for i in range(len(dataset)): | ||
| instance = dataset.prepare_data(i) | ||
| img = cv2.imread(instance['img_path']) | ||
| visualizer.draw_points(img, instance['keypoints'][0]) | ||
| save_path = os.path.join(vis_dir, | ||
| os.path.basename(instance['img_path'])) | ||
| cv2.imwrite(save_path, img) |
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This test method has no exception checking.
| @@ -76,3 +78,63 @@ def draw_pose(self, img, instances): | |||
| color, -1) | |||
| cv2.circle(img, (int(x_coord), int(y_coord)), self.radius, | |||
| (255, 255, 255)) | |||
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| def draw_points(self, img, instances): | |||
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Hi @KeqiangSun, |
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Motivation
In Facial Landmark Detection, 300VW is a significant dataset, which contains 104 videos, which over 218k frames. We add the 300VW dataset to mmpose for training and comparison.
Modification
We add 300VW pre-processing scripts, which convert the original dataset to coco format. We also add 300vw dataset as well as the test scripts.
BC-breaking (Optional)
Use cases (Optional)
Checklist
Before PR:
After PR: