Add dataset card

README.md

@@ -1,24 +1,47 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 101267047
-    num_examples: 10000
-  - name: test
-    num_bytes: 24984555
-    num_examples: 2000
-  download_size: 125317198
-  dataset_size: 126251602
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+license: apache-2.0
+task_categories:
+- image-to-text
+tags:
+- captcha
+- ocr
+- synthetic
+- vision-language
+size_categories:
+- 10K<n<100K
 ---
+
+# Synthetic CAPTCHA Dataset
+
+Synthetic distorted-text CAPTCHA images with exact character-string labels, used
+to fine-tune [`Hansda/minicpm-v4_6-captcha-lora`](https://huggingface.co/Hansda/minicpm-v4_6-captcha-lora).
+
+## Contents
+
+- **Format:** HuggingFace `imagefolder` (`image`, `text` columns), with
+  `metadata.jsonl` per split.
+- **Splits:** `train` (10,000) and `test` (2,000) — 12,000 images total.
+- **Labels:** 4–7 characters from `ABCDEFGHJKLMNPQRSTUVWXYZabcdefghjkmnpqrstuvwxyz23456789`
+  (visually ambiguous `I O 0 1 l` are excluded).
+
+## Generation
+
+Images are procedurally generated (Pillow + PyTorch) with per-character random
+font / size / rotation / shear / stretch, wave & bezier warping, background
+gradients and noise, random lines, curves and arcs, and varied colours — to
+mimic classic distorted-text CAPTCHAs.
+
+## Load
+
+```python
+from datasets import load_dataset
+ds = load_dataset("Hansda/captcha-dataset")
+print(ds["train"][0]["text"], ds["train"][0]["image"].size)
+```
+
+## Note
+
+The per-character size is randomized independently, so upper/lower case is not
+always visually separable for ambiguous glyphs (`c/C`, `s/S`, `v/V`, …). This
+makes strict case-sensitive scoring inherently hard; case-insensitive reading is
+the more reliable target.