Add dataset card

README.md

@@ -1,32 +1,158 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: image_path
-    dtype: string
-  - name: source
-    dtype: string
-  - name: split
-    dtype: string
-  - name: annotations
-    dtype: string
-  - name: num_objects
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 9212999500
-    num_examples: 30658
-  - name: val
-    num_bytes: 836584640
-    num_examples: 2764
-  download_size: 8854148134
-  dataset_size: 10049584140
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: val
-    path: data/val-*
+license: cc-by-4.0
+language:
+  - km
+task_categories:
+  - object-detection
+tags:
+  - khmer
+  - text-detection
+  - ocr
+  - document-analysis
+  - yolo
+  - synthetic
+  - scene-text
+pretty_name: Khmer Text Detection (Ultimate)
+size_categories:
+  - 10K<n<100K
 ---
+
+# Khmer Text Detection — Ultimate Dataset
+
+A large-scale, multi-source dataset for **Khmer text detection** using YOLO-format bounding box annotations.
+Combines real scene text, document layout images, and synthetically generated Khmer document images.
+
+---
+
+## Dataset Summary
+
+| Split | Images |
+|-------|--------|
+| Train | 30,658 |
+| Val   | 2,764 |
+| **Total** | **33,422** |
+
+### Classes
+
+| ID | Name | Description |
+|----|------|-------------|
+| 0 | `text_line` | A line of Khmer or mixed-script text |
+| 1 | `image` | An embedded image/figure region within a document |
+
+---
+
+## Data Sources
+
+### 1. Real Scene Text (`real_scene_text`)
+Images captured in natural environments — street signs, storefronts, billboards, and handwritten Khmer documents.
+Derived from the **DonkeySmall** base dataset (~26K images).
+
+### 2. Document Layout (`doclaynet_khmer`)
+Images from the **DocLayNet**-style multi-class document layout corpus, re-labelled for the two-class schema.
+Covers printed Khmer documents: official reports, newspapers, and books.
+
+### 3. Synthetic Khmer Documents (`synthetic_khmer_doc`)
+Programmatically generated document images using custom Khmer text rendering pipelines.
+Fonts, sizes, backgrounds, and layouts are randomised. Labels are auto-generated (zero annotation cost).
+
+---
+
+## Annotation Format
+
+Labels follow **YOLO v8** format — coordinates normalised to `[0, 1]`:
+
+```
+<class_id> <cx> <cy> <width> <height>
+```
+
+The `annotations` field is a JSON-serialised list:
+
+```json
+[
+  {"class_id": 0, "cx": 0.512, "cy": 0.234, "w": 0.310, "h": 0.045},
+  {"class_id": 1, "cx": 0.720, "cy": 0.600, "w": 0.200, "h": 0.250}
+]
+```
+
+---
+
+## Dataset Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `image` | `Image` | Decoded PIL image |
+| `image_path` | `string` | Original file path at collection time |
+| `source` | `string` | `real_scene_text` / `doclaynet_khmer` / `synthetic_khmer_doc` |
+| `split` | `string` | `train` or `val` |
+| `annotations` | `string` | JSON list of YOLO bounding boxes |
+| `num_objects` | `int32` | Number of annotated objects |
+
+---
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Darayut/Multilingual-Textline-Detection-Dataset")
+
+sample = ds["train"][0]
+print(sample["source"], sample["num_objects"])
+sample["image"].show()
+```
+
+### Convert back to YOLO label files
+
+```python
+import json
+from pathlib import Path
+
+def save_labels(split, out_dir):
+    Path(out_dir).mkdir(parents=True, exist_ok=True)
+    for row in ds[split]:
+        stem = Path(row["image_path"]).stem
+        anns = json.loads(row["annotations"])
+        with open(f"{out_dir}/{stem}.txt", "w") as f:
+            for a in anns:
+                f.write(f"{a['class_id']} {a['cx']:.6f} {a['cy']:.6f} {a['w']:.6f} {a['h']:.6f}\n")
+
+save_labels("train", "labels/train")
+save_labels("val",   "labels/val")
+```
+
+### YAML config for YOLOv8 training
+
+```yaml
+train: /path/to/images/train
+val:   /path/to/images/val
+nc: 2
+names:
+  0: text_line
+  1: image
+```
+
+---
+
+## Limitations
+
+- Synthetic images may not capture all real-world degradation (blur, skew, lighting variation).
+- Scene-text labels are semi-automatic and may have occasional missed detections.
+- Dataset is primarily Khmer script; other scripts appear only incidentally.
+
+---
+
+## License
+
+[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — free to use, share, and adapt with attribution.
+
+---
+
+## Citation
+
+```bibtex
+@dataset{khmer_text_detection_ultimate,
+  title  = {Khmer Text Detection — Ultimate Dataset},
+  year   = {2025},
+  url    = {https://huggingface.co/datasets/Darayut/Multilingual-Textline-Detection-Dataset}
+}
+```