| --- |
| license: other |
| license_name: flux-1-dev-non-commercial-license |
| license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md |
| task_categories: |
| - text-to-image |
| language: |
| - en |
| tags: |
| - flux |
| - lora |
| - peft |
| - personalization |
| - dreambooth |
| - llm-as-a-judge |
| - evaluation |
| pretty_name: LITHE evaluation images and judge outputs |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: |
| - metadata.csv |
| - images/**/*.jpg |
| --- |
| |
| # LITHE evaluation images and per-image judge outputs |
|
|
| This dataset contains every generated image behind Table 1 (`tab:db30-pareto`) and the multi-seed |
| appendix tables of the LITHE paper. Each image comes with the raw output of the three LLM judges that |
| scored it (GPT-5.1, Claude Sonnet 4.6, Gemini 2.5 Flash): the integer score for each rubric dimension |
| and the free-text `reason` (and, on SC-40, `description`) fields the judge returned. With these files |
| the paper's judge-based numbers can be audited image by image, and the images can be rescored with a |
| different judge. |
|
|
| Code, prompts, judge prompt templates and the per-prompt score tables: |
| https://github.com/JianJiang1995/LITHE (`artifacts/`). Pretrained LITHE adapters: |
| https://huggingface.co/Fanjue/LITHE. |
|
|
| ## Contents |
|
|
| | benchmark | images | methods x runs | prompts per concept | |
| |---|---:|---|---| |
| | DreamBooth-30 (`dreambooth30`) | 4,650 | 10 x 3, plus vanilla FLUX x 1 | 5 | |
| | CC101-20 (`cc101_20`) | 3,100 | 10 x 3, plus vanilla FLUX x 1 | 5 | |
| | SCIdentity (`scidentity`) | 3,100 | 10 x 3, plus vanilla FLUX x 1 | 5 | |
| | SC-40 (`sc40`) | 5,720 | 10 x 3, plus vanilla FLUX x 1 | 5 (DyLoRA and LoRA-FA: 3) | |
| | total | 16,570 | | | |
|
|
| Methods (`method`): `lora`, `lithe`, `dora`, `vera`, `adalora`, `qlora_nf4`, `dylora`, `lora_fa`, |
| `loraxs`, `tlora`, and `vanilla_flux` (FLUX.1-dev without an adapter). `seed` is the training seed of |
| the run: 42, 1 and 7 for LoRA and LITHE; 42, 43 and 44 for the other adapters; 42 for vanilla FLUX. |
| All adapters are rank 16 on FLUX.1-dev. |
|
|
| ``` |
| images/<benchmark>/<method>/seed_<seed>/<concept_id>__p<prompt_idx>.jpg |
| judges/<benchmark>.jsonl |
| metadata.csv |
| SHA256SUMS |
| ``` |
|
|
| The row set is identical to `artifacts/results/*_per_prompt.csv` in the code repository: one image per |
| (benchmark, method, seed, concept_id, prompt_idx) row, and every row there has an image here. |
|
|
| ### Images |
|
|
| All images are FLUX.1-dev outputs at 1024 x 1024. They were re-encoded to JPEG (quality 92) from the |
| original output files, writing the pixels only, so no EXIF, XMP, ICC or other metadata is carried |
| over. The original files were JPEGs as well; `original_sha256` in `metadata.csv` is the SHA256 of the |
| original file as it was evaluated, and `sha256` is the SHA256 of the file in this dataset. Because of |
| the re-encoding, pixel values differ slightly from the evaluated files, so a rescore of these JPEGs is |
| close to but not bit-identical with what the judges saw. |
|
|
| No training or reference images are included. Images are generated outputs only. |
|
|
| * DreamBooth-30 and CC101-20 subjects come from the public DreamBooth and CustomConcept101 datasets; |
| their reference images are available from the original authors. |
| * SCIdentity subjects are synthetic, rare animal-like individuals. |
| * SC-40 covers five axes (outfit, lighting, pose, painter style, anime style). The people shown in |
| SC-40 images (in particular on the outfit and pose axes) are synthetic and were generated by |
| FLUX.1-dev; they do not depict real persons. |
| * The SCIdentity and SC-40 training/reference images are not part of this release; their |
| construction is described in the paper appendix. |
|
|
| ### `judges/<benchmark>.jsonl` |
|
|
| One JSON object per image: |
|
|
| | field | meaning | |
| |---|---| |
| | `benchmark`, `method`, `seed`, `concept_id`, `prompt_idx` | row key, as in the code repository | |
| | `prompt_set` | prompt list the image was generated from (see `artifacts/results/README.md`) | |
| | `group` | SC-40 axis, `null` elsewhere | |
| | `prompt` | the generation prompt, including the trigger token | |
| | `image` | relative path of the image in this dataset | |
| | `rubric` | `identity` (SI, PF, VQ, SBD, CN), `sc40` (TF, PF, VQ), or `identity_legacy_si_pf_vq` (see below) | |
| | `judges` | one entry per judge: `gpt51`, `claude`, `gemini` | |
|
|
| Each judge entry has: |
|
|
| | field | meaning | |
| |---|---| |
| | `model` | GPT-5.1, Claude Sonnet 4.6 or Gemini 2.5 Flash | |
| | `scores` | integer 1-5 score per rubric dimension | |
| | `description` | SC-40 only: the judge's description of references vs. generated image | |
| | `reason` | the judge's justification text, verbatim | |
| | `raw_response` | the complete reply text as returned by the API (Claude and Gemini), including any Markdown code fence; `null` for GPT-5.1 | |
| | `followup_fields` | present when the first reply omitted these score fields; their values come from the single score-only follow-up request (Claude, 154 images) | |
|
|
| GPT-5.1 was run in JSON output mode and its reply was stored as the parsed JSON fields (`scores`, |
| `description`, `reason`); the reply string itself was not kept, so `raw_response` is `null` for |
| GPT-5.1. One Claude reply (`scidentity`, `loraxs`, seed 43, `glass_gill_axolotl_cat`, prompt 4) |
| contained scores but no reason; its `reason` is the empty string. |
|
|
| Rubric dimensions. Identity benchmarks: `SI` subject identity, `PF` prompt following, `VQ` visual |
| quality, `SBD` subject-background disentanglement, `CN` class naturalness. SC-40: `TF` target |
| fidelity, `PF` prompt following, `VQ` visual quality. |
|
|
| Vanilla FLUX is scored by GPT-5.1 only. On DreamBooth-30 and CC101-20 its images were generated from |
| the `vanilla_sks` prompts and scored with an earlier GPT-5.1 rubric that returned SI, PF and VQ plus |
| `description` and `reason` (`rubric = identity_legacy_si_pf_vq`); on SCIdentity and SC-40 it uses the |
| same rubrics as the adapters. |
|
|
| Each judge entry is the call whose scores enter the paper tables, taken from the same result files |
| as `artifacts/results/*_per_prompt.csv`, and `raw_response` is the reply of that same call. For 706 |
| images (GPT-5.1 44, Claude 642, Gemini 20 judge entries) the evaluation logs also hold earlier or |
| partial re-runs with the same scores and different text; those are not included. |
|
|
| ### `metadata.csv` |
|
|
| One row per image: the row key, `prompt`, `file_name` (image path), `width`, `height`, |
| `original_sha256`, `sha256`, `rubric`, all per-judge rubric scores and averages (`gpt51_*`, |
| `claude_*`, `gemini_*`, `llm_avg`) and the embedding metrics (`dreamsim`, `clip_i`, `clip_t`), with |
| the same values as `artifacts/results/*_per_prompt.csv`. Columns that do not apply to a row are |
| empty. `artifacts/results/aggregate.py` in the code repository reproduces Table 1 and the appendix |
| tables from these values. |
|
|
| ## Judging protocol |
|
|
| GPT-5.1 was called through the OpenAI chat-completions API at temperature 0 with JSON output mode, |
| image detail `high`, and `max_completion_tokens` 300 (identity) / 400 (SC-40). Claude Sonnet 4.6 and |
| Gemini 2.5 Flash were called through an OpenAI-compatible endpoint at temperature 0 with the same |
| prompt text and image order, without JSON mode; when a reply omitted a score field, the missing |
| fields were requested once more with a short score-only follow-up on the same images. |
|
|
| The identity rubric shows the judge the subject's first training image (`REFERENCE:`) and the |
| generated image (`GENERATED:`). The SC-40 rubric shows two reference images of the concept and the |
| generated image. Per-image LLM-avg is the mean of the three judges' dimension means. |
|
|
| ## Rescoring with another judge |
|
|
| The judge prompt templates and a minimal judge script are in `artifacts/judge/` of |
| https://github.com/JianJiang1995/LITHE. The script talks to any OpenAI-compatible chat-completions |
| endpoint, configured through `OPENAI_API_KEY` and `OPENAI_BASE_URL`: |
|
|
| ```bash |
| git clone https://github.com/JianJiang1995/LITHE && cd LITHE/artifacts/judge |
| export OPENAI_API_KEY=... # and OPENAI_BASE_URL for a non-OpenAI endpoint |
| # identity benchmarks: one reference image (the subject's first training image) |
| python judge.py --rubric identity --model <judge-model> \ |
| --image <dataset>/images/dreambooth30/lithe/seed_42/db_cat__p0.jpg \ |
| --ref <dreambooth>/cat/00.jpg --prompt "a photo of a <v_sub_001> cat" --class-name cat |
| # SC-40: two reference images of the concept |
| python judge.py --rubric sc40 --model <judge-model> --image <image> --ref <ref1> --ref <ref2> \ |
| --group anime_style --concept candy_glass_cyber_cel --prompt "<prompt from the jsonl>" |
| ``` |
|
|
| Take `prompt` from `judges/<benchmark>.jsonl`, the class word and trigger from |
| `artifacts/prompts/<benchmark>.csv`, and pass `--no-json-mode --detail ''` for endpoints that reject |
| JSON mode. Reference images are needed for the identity and target-fidelity dimensions and are not |
| part of this dataset (see Images above). Prompt following and visual quality can be rescored from the |
| prompt and image alone with a rubric of your own. |
|
|
| ## License |
|
|
| The images are outputs of FLUX.1-dev and are released under the FLUX.1 [dev] Non-Commercial License |
| (https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md). The judge texts are |
| model outputs released for research use under the same non-commercial terms. DreamBooth and |
| CustomConcept101 subjects remain subject to the terms of their original datasets. |
|
|
