metadata.jsonl, the omission manifest and the dataset card

README.md

@@ -1,3 +1,113 @@
 ---
-license: mit
+license: other
+license_name: web-collected-images
+pretty_name: Mega Liminal
+task_categories:
+- text-to-image
+- image-to-text
+language:
+- en
+tags:
+- liminal
+- liminal-spaces
+- captioned
+- lora-training
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path:
+    - "data/**/*.jpg"
+    - "data/**/*.jpeg"
+    - "data/**/*.png"
+    - "data/**/*.webp"
+    - "data/metadata.jsonl"
 ---
+
+# Mega Liminal
+
+1,873 captioned images of liminal spaces: empty malls, fog-bound roads, parking garages, suburbs at night,
+vacant theatres and hallways, sorted into 10 classes and curated for training image models. The
+[Mega Liminal LoRA](https://huggingface.co/AbstractPhil/mega-liminal-lora) was trained on it.
+
+## Contents
+
+| Class | Files |
+|---|---|
+| mega liminal | 870 |
+| landscape | 766 |
+| suburban | 111 |
+| simulacrum | 36 |
+| vanishing point | 21 |
+| empty mall | 20 |
+| hand sourced | 18 |
+| parking garage | 13 |
+| cityscape | 10 |
+| movie theatre | 8 |
+| **total** | **1,873 files, 1,060 unique images** |
+
+The classes overlap. The mega liminal class gathers most of the landscape images and some suburban ones,
+so 813 files are byte-identical copies filed under a second class. Each copy has its own caption. The
+`also_in` column names the other copies; keep one row per `sha256` for a deduplicated set.
+
+The captioner labeled 1,680 images as photographs, 122 as 3D renders, 69 as digital paintings and 2 as
+drawings. 55 images carry a visible watermark (`watermark` column).
+
+## Layout
+
+```
+data/<class>/<image>            the image (jpg, jpeg, png or webp)
+data/<class>/<image stem>.txt   its caption
+data/metadata.jsonl             one row per image: file_name, text, class, width, height, medium, watermark, sha256, also_in
+omitted_manifest.csv            the 202 source images removed during curation, with the reason
+```
+
+## Loading
+
+With the `datasets` library:
+
+```python
+from datasets import load_dataset
+ds = load_dataset("AbstractPhil/mega-liminal", split="train")
+```
+
+For trainers that read image and `.txt` pairs (kohya, ai-toolkit, diffusion-pipe, OneTrainer), download the
+files and point the trainer at `mega-liminal/data/<class>`:
+
+```bash
+hf download AbstractPhil/mega-liminal --repo-type dataset --local-dir mega-liminal
+```
+
+## Captions
+
+Every caption has the form `liminal, <class>, <description>`. Qwen3.5-9B wrote the descriptions, one
+structured pass per image: two to four sentences covering the kind of image, the place and its layout,
+the camera position, the architecture and materials, and the lighting and colors. The prompt ruled out
+mood words and sentences about what is absent, and a cleanup pass removed any that slipped through. Some
+captions mention visible text or a watermark.
+
+## Curation
+
+202 of the 2,075 source images were removed:
+
+| Reason | Images |
+|---|---|
+| under 512x512 pixels (262,144) | 63 |
+| video-game screenshots (Garry's Mod and similar engines) | 74 |
+| low-resolution 3D render | 33 |
+| cartoon or toy render | 17 |
+| low-poly or untextured 3D | 10 |
+| pixel art | 3 |
+| framed collage | 2 |
+
+Every removal except the pixel-count rule was checked by eye. Clean, high-resolution renders were kept.
+
+## Licensing
+
+The images were gathered from public liminal-space collections on the web. Their rights stay with their
+original creators, and some carry the creator's watermark. The dataset is shared for research and
+non-commercial use. To have an image removed, open a discussion on this repo.
+
+The captions were written by Qwen3.5-9B for this dataset.