diff --git a/README.md b/README.md index 528e70f3ff8805dd4bf9687d54b089ed8a118855..0a0c45c37f97d36f024e1ea66229dc204e9bf63f 100644 --- a/README.md +++ b/README.md @@ -5,13 +5,22 @@ task_categories: size_categories: - 1M.parquet` holds, for every image of `.tar` (same order, 1,000,000 rows in total), the original caption and two new captions written by [Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct). The images are not duplicated; join on `key`. + +| Column | Content | +| --- | --- | +| `key` | example key in the tar (`.jpg`) | +| `source_shard` | tar file name | +| `orig_caption` | the original `.txt` caption | +| `recap_1`, `recap_2` | two new captions, one paragraph each | + +```python +from datasets import load_dataset + +recaps = load_dataset("IntelligenceLab/BLIP3o-Recap", "recaptions", split="train") +``` + +### Generation + +- Model: `Qwen/Qwen2.5-VL-3B-Instruct`, vLLM 0.31.0, bf16, images capped at 640×28×28 pixels. +- Both captions are two samples (`n=2`) of the same prompt: temperature 0.8, top-p 0.9, at most 160 new tokens. +- Prompt (verbatim): + +```text +System: You are an image captioner. Describe only what is visible. + +User: Describe this image in ONE paragraph of 70–90 words. +Order: main subject(s) (count, category, color, size, pose/action) → spatial relations (left/right, front/behind, near/far) → background and setting → lighting, viewpoint, and medium (photo, illustration, 3D render, etc.). +Rules: +- Start directly with the main subject. Never begin with "The image", "This picture", "In this photo", or similar. +- State only what is clearly visible. No guesses ("likely", "possibly", "suggesting", "appears to be"), no mood words ("serene", "vibrant", "charming", "picturesque"), no interpretation of purpose or meaning. +- Quote visible text only if it is legible. +- No lists, no line breaks, no concluding summary sentence. +``` + +### Constraints and filtering + +The 3B model ignores parts of the prompt (without intervention about 60% of captions start with "The image …" and about 80% contain a banned word), so the rules are also enforced while decoding and checked afterwards. + +**Banned while decoding** (every casing and leading-space token form, through vLLM `bad_words` and `logit_bias`): + +- words from the prompt: likely, possibly, appears, suggesting, serene, vibrant, charming, picturesque; +- their inflections and the substitutes the model switched to: appear(ed/ing), suggest(s/ed), seem(s/ed/ingly), indicat(e/es/ed/ing/ive), perhaps, probably, might, possible, potentially, presumably, apparently, supposedly, hint(s/ing), impl(ies/ying), impression; +- mood and interpretive words: tranquil, peaceful, idyllic, cozy, inviting, stunning, breathtaking, bustling, overall, atmosphere, ambiance, ambience, calm, lively, festive, scenic, striking, dramatic, majestic, grand, dynamic, typical, emphasiz(e/es/ed/ing), enjoy(s/ing), welcoming, relax(ed/ing), pleasant, playful, harmonious, elegant, whimsical, energetic, cheerful, celebratory, celebrating, intimate, aesthetic, iconic, mood, moody; +- phrases: "creating a", "sense of", "giving a / it / the scene / the image", "adding a", "natural beauty", "looks like", "what looks", "could be", "may be"; +- openers: "The / This / These" + image, picture, photo, photograph, scene, illustration, snapshot; "In this", "In the image / picture / photo"; and "The", "This", "These" as the first word. + +**Rejected and resampled** (up to 3 times): an opener or banned word outside quotes (quoted visible text is kept verbatim), a line break or list, fewer than 60 words, or Chinese / Japanese / Korean characters outside quotes (the model sometimes drifts into Chinese mid-sentence). A caption cut off at 160 tokens keeps its complete sentences. There is no upper word limit. + +The banned list grew in three rounds while inspecting outputs; after the main run, every caption that violated the final rules (110,176 of 2,000,000) was regenerated with the final rules. No other caption was changed. + +### Statistics + +| | | +| --- | ---: | +| captions that still violate a rule | 0.02% (439 images) | +| words per caption (p5 / median / p95) | 63 / 81 / 108 | +| recap_1 vs recap_2, same image: bigram Jaccard / ROUGE-L | 0.157 / 0.394 | +| recap_1 vs recap_2, different images: bigram Jaccard / ROUGE-L | 0.041 / 0.231 | +| recap_1 vs original caption: bigram Jaccard / ROUGE-L | 0.091 / 0.289 | + +The two captions of an image share the prompt's fixed sentence order but differ in wording and detail; on average 57% of the content words of `recap_2` do not occur in `recap_1`. + +### Known limitations + +These are small-model captions. A manual check of 16 captions found the main subject, colors, setting, medium and legible text correct in all of them, but about a third had one wrong secondary detail: left/right or front/back orientation, an object count, or an invented small object. The two captions of an image rarely make the same error. 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