| --- |
| license: cc-by-4.0 |
| pretty_name: TextureADE |
| task_categories: |
| - image-segmentation |
| tags: |
| - texture-segmentation |
| - sub-semantic-segmentation |
| size_categories: |
| - n<1K |
| --- |
| |
| # TextureADE |
|
|
| Real scenes carrying several appearance transitions each, mined from the ADE20K validation split. |
|
|
| One of the four evaluation routes in the ICLR 2027 submission on sub-semantic |
| image segmentation: partitioning an image into regions that are coherent in |
| appearance and describable in language, but that need not correspond to any |
| object, part or material class. |
|
|
| - **Images:** 212 |
| - **Code:** [github.com/aviadcohz/Qwen2SAM_Detecture_Benchmark](https://github.com/aviadcohz/Qwen2SAM_Detecture_Benchmark) |
| - **Weights:** [aviadcohz/Detecture-ICLR-2027](https://huggingface.co/aviadcohz/Detecture-ICLR-2027) |
| - **All four routes in one download:** [aviadcohz/Detecture_ICLR_Benchmarking](https://huggingface.co/datasets/aviadcohz/Detecture_ICLR_Benchmarking) |
|
|
| ## Layout |
|
|
| ``` |
| ADE20k_Detecture/ |
| ├── images/ RGB images |
| ├── textures_mask/ per-texture binary masks, <id>_mask_<k>.png |
| ├── metadata.json image paths, mask paths, descriptions |
| └── summary.json dataset statistics |
| ``` |
|
|
| The three real-world routes also carry `masks/` and `overlays/`; overlays are visualisations, not ground truth. |
|
|
| The directory inside this repo is named `ADE20k_Detecture` rather than `TextureADE`, because |
| that is the name the evaluation configs resolve |
| (`fairness_baseline_suite/src/paths.py`). Paths inside `metadata.json` are relative |
| to the repository root, so the folder can be placed anywhere. |
|
|
| ## Use |
|
|
| ```bash |
| cd ~/datasets |
| git lfs install |
| git clone https://huggingface.co/datasets/aviadcohz/TextureADE |
| mv TextureADE/ADE20k_Detecture . && rm -rf TextureADE |
| ``` |
|
|
| Then, from the benchmark repo: |
|
|
| ```bash |
| cd Qwen2SAM_Detecture_Benchmark/fairness_baseline_suite |
| PYTHONPATH=src python src/run_fairness.py --model detecture --dataset TextureADE |
| ``` |
|
|
| ## Evaluation protocol |
|
|
| Every number reported on this route comes from one protocol applied identically to |
| every method: no ground-truth region count in the prompt, no inverse-mask |
| completion, no truncation of proposals to a known count, and no dropping of images |
| where a method returns nothing. The region count is inferred, never supplied. |
| Results obtained this way are **not** comparable to evaluations that supply it. |
|
|
| ## Provenance |
|
|
| Mined from the natural ADE20K validation split by a geometry-first procedure: |
| connected components are merged into at most five candidate regions each covering |
| at least 1% of image area, scored on mask structure and boundary geometry, and |
| admitted only above a fixed threshold. A frozen vision-language annotator is |
| queried afterwards, against a region that has already been accepted, so language |
| never proposes regions. |
|
|
| ## Licence |
|
|
| CC-BY-4.0 for this packaging. Upstream corpora keep their own terms: ADE20K. |
|
|
