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| PHASES = [ | |
| {"label": "Dev (test-dev2024)", "codename": "test-dev2024"}, | |
| {"label": "Standard (test-standard2024)", "codename": "test-standard2024"}, | |
| {"label": "Challenge (test-challenge2024)", "codename": "test-challenge2024"}, | |
| ] | |
| CHALLENGE_TYPES = ["Object Detection", "Instance Segmentation"] | |
| LEADERBOARD_METRICS = ["bbox_mAP", "bbox_AP50", "segm_mAP", "segm_AP50"] | |
| DEFAULT_SORT_METRIC = "segm_AP50" | |
| LEADERBOARD_FILE = "leaderboard.jsonl" | |
| CHALLENGE_PHASE = "test-challenge2024" | |
| EVAL_DETAILS_MD = """ | |
| ### How is the Score Calculated? | |
| Your submission is evaluated automatically against hidden ground-truth annotations using **pycocotools**. | |
| | Metric | Description | | |
| |--------|-------------| | |
| | `bbox_mAP` | Bounding box mean average precision | | |
| | `bbox_AP50` | Bounding box AP at IoU = 0.50 | | |
| | `segm_mAP` | Segmentation mean average precision | | |
| | `segm_AP50` | Segmentation AP at IoU = 0.50 *(default ranking metric)* | | |
| """ | |
| FORMAT_MD = """ | |
| ### Submission Format | |
| Your JSON file must be a **list of annotation objects**, each containing: | |
| ```json | |
| [ | |
| { | |
| "image_id": 123, | |
| "category_id": 101, | |
| "score": 0.95, | |
| "area": 1024.0, | |
| "bbox": [x, y, width, height], | |
| "segmentation": [[x1, y1, x2, y2, ...]] | |
| }, | |
| ... | |
| ] | |
| ``` | |
| """ | |