| { | |
| "name": "TextCaps", | |
| "release_date": "2020-03-24", | |
| "subsets": { | |
| "main": { | |
| "language": [ | |
| "en" | |
| ], | |
| "modalities": [ | |
| "single_image_start" | |
| ], | |
| "task_type": "captioning", | |
| "score_pipeline": { | |
| "unsupported": "caption-metrics", | |
| "reason": "requires corpus-level caption metrics (CIDEr/BLEU/ROUGE/BERTScore); use the benchmark's own evaluator" | |
| }, | |
| "score_params": { | |
| "metrics": [ | |
| "cider", | |
| "bleu4", | |
| "meteor", | |
| "rouge_l" | |
| ] | |
| }, | |
| "score_protocol": { | |
| "reference": "lmms-eval@lmms_eval/tasks/textcaps/textcaps_val.yaml:19-27 + utils.py (same pycocoevalcap scorer set: Bleu1-4, METEOR, ROUGE_L, CIDEr; SPICE commented out) — TextCaps paper headline is CIDEr over 5 references.", | |
| "note": "Corpus-level metrics; no per-sample correctness. SPICE disabled in frameworks, excluded here. mm-eval copy stores 5 reference captions per image (rows verified). mm-eval prompt uses VLMEvalKit one-sentence caption prompt while the source question column carries lmms-eval's 'come up with a caption' phrasing." | |
| }, | |
| "prompt_template": "<image>Provide a one-sentence caption for the provided image.", | |
| "mapping_from_source": { | |
| "media": { | |
| "from": "image", | |
| "type": "list", | |
| "min_items": 1, | |
| "max_items": 1 | |
| }, | |
| "id": { | |
| "from": "question_id" | |
| }, | |
| "question": { | |
| "from": "question" | |
| }, | |
| "answer": { | |
| "from": "reference_strs", | |
| "optional": true | |
| }, | |
| "extra": { | |
| "image_id": { | |
| "from": "image_id" | |
| }, | |
| "image_classes": { | |
| "from": "image_classes" | |
| } | |
| }, | |
| "source": { | |
| "format": "huggingface", | |
| "url": { | |
| "val": "https://huggingface.co/datasets/lmms-lab/TextCaps" | |
| } | |
| } | |
| }, | |
| "prompt_template_source": { | |
| "origin": "official", | |
| "reference": "https://github.com/open-compass/VLMEvalKit/blob/main/vlmeval/dataset/image_caption.py (ImageCaptionDataset canonical caption prompt)", | |
| "notes": "Tier 3: VLMEvalKit ImageCaptionDataset canonical TextCaps captioning prompt." | |
| } | |
| } | |
| } | |
| } |