Update README.md

README.md

@@ -1,47 +1,233 @@
----
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: difficulty
-    dtype: string
-  - name: code
-    dtype: string
-  - name: render_light
-    dtype: image
-  - name: render_dark
-    dtype: image
-  - name: photo
-    dtype: image
-  splits:
-  - name: easy
-    num_bytes: 3086674334
-    num_examples: 700
-  - name: medium
-    num_bytes: 902595780
-    num_examples: 200
-  - name: hard
-    num_bytes: 500128560
-    num_examples: 100
-  download_size: 4485774053
-  dataset_size: 4489398674
-configs:
-- config_name: default
-  data_files:
-  - split: easy
-    path: data/easy-*
-  - split: medium
-    path: data/medium-*
-  - split: hard
-    path: data/hard-*
-license: mit
-task_categories:
-- image-to-text
-- text-generation
-tags:
-- code
-- ocr
-pretty_name: CodeOCR
-size_categories:
-- 1K<n<10K
----
+---
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: difficulty
+    dtype: string
+  - name: code
+    dtype: string
+  - name: render_light
+    dtype: image
+  - name: render_dark
+    dtype: image
+  - name: photo
+    dtype: image
+  splits:
+  - name: easy
+    num_bytes: 3086674334
+    num_examples: 700
+  - name: medium
+    num_bytes: 902595780
+    num_examples: 200
+  - name: hard
+    num_bytes: 500128560
+    num_examples: 100
+  download_size: 4485774053
+  dataset_size: 4489398674
+configs:
+- config_name: default
+  data_files:
+  - split: easy
+    path: data/easy-*
+  - split: medium
+    path: data/medium-*
+  - split: hard
+    path: data/hard-*
+license: mit
+task_categories:
+- image-to-text
+- text-generation
+tags:
+- code
+- ocr
+pretty_name: CodeOCR
+size_categories:
+- 1K<n<10K
+---
+
+---
+pretty_name: "CodeOCR Dataset (Python Code Images + Ground Truth)"
+license: mit
+language:
+  - en
+task_categories:
+  - image-to-text
+tags:
+  - ocr
+  - code
+  - python
+  - leetcode
+  - synthetic
+  - computer-vision
+size_categories:
+  - 1K<n<10K
+---
+
+# CodeOCR Dataset (Python Code Images + Ground Truth)
+
+This dataset is designed for **Optical Character Recognition (OCR) of source code**.  
+Each example pairs **Python code (ground-truth text)** with **image renderings** of that code (light/dark themes) and a **real photo**.
+
+## Dataset Summary
+
+- **Language:** Python (text ground truth), images of code
+- **Splits:** `easy`, `medium`, `hard`
+- **Total examples:** 1,000  
+  - `easy`: 700  
+  - `medium`: 200  
+  - `hard`: 100  
+- **Modalities:** image + text
+
+### What is “ground truth” here?
+
+The `code` field is **exactly the content of `gt.py`** used to generate the synthetic renderings.  
+During dataset creation, code is normalized to ensure stable GT properties:
+
+- UTF-8 encoding  
+- newline normalization to **LF (`\n`)**  
+- tabs expanded to **4 spaces**  
+- syntax checked with Python `compile()` (syntax/indentation correctness)
+
+This makes the dataset suitable for training/evaluating OCR models that output **plain code text**.
+
+---
+
+## Data Fields
+
+Each row contains:
+
+- `id` *(string)*: sample identifier (e.g., `easy_000123`)
+- `difficulty` *(string)*: `easy` / `medium` / `hard`
+- `code` *(string)*: **ground-truth Python code**
+- `render_light` *(image)*: synthetic rendering (light theme)
+- `render_dark` *(image)*: synthetic rendering (dark theme)
+- `photo` *(image)*: real photo of the code
+
+---
+
+## How to Use
+
+### Load with 🤗 Datasets
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("maksonchek/codeocr-dataset")
+print(ds)
+print(ds["easy"][0].keys())
+```
+
+### Access code and images
+
+```python
+ex = ds["easy"][0]
+
+# Ground-truth code
+print(ex["code"][:500])
+
+# Images are stored as `datasets.Image` features.
+render = ex["render_light"]
+print(render)
+```
+
+If your environment returns image dicts with local paths:
+
+```python
+from PIL import Image
+
+img = Image.open(ex["render_light"]["path"])
+img.show()
+```
+
+Real photo (always present in this dataset):
+
+```python
+from PIL import Image
+
+photo = Image.open(ex["photo"]["path"])
+photo.show()
+```
+
+---
+
+## Dataset Creation
+
+### 1) Code selection
+Python solutions were collected from an open-source repository of LeetCode solutions (MIT licensed).
+
+### 2) Normalization to produce stable GT
+The collected code is written into `gt.py` after:
+
+- newline normalization to LF
+- tab expansion to 4 spaces
+- basic cleanup (no hidden control characters)
+- Python syntax check via `compile()`
+
+### 3) Synthetic rendering
+Synthetic images are generated from the normalized `gt.py` in:
+
+- light theme (`render_light`)
+- dark theme (`render_dark`)
+
+### 4) Real photos
+Real photos are manually captured and linked **for every sample**.
+
+---
+
+## Statistics (high-level)
+
+Average code length by difficulty (computed on this dataset):
+
+- `easy`: ~27 lines, ~669 chars
+- `medium`: ~36 lines, ~997 chars
+- `hard`: ~55 lines, ~1767 chars
+
+(Exact values may vary if the dataset is extended.)
+
+---
+
+## Intended Use
+
+- OCR for programming code
+- robust text extraction from screenshot-like renders and real photos
+- benchmarking OCR pipelines for code formatting / indentation preservation
+
+### Not Intended Use
+
+- generating or re-distributing problem statements
+- competitive programming / cheating use-cases
+
+---
+
+## Limitations
+
+- Code is checked for **syntax correctness**, but not necessarily for runtime correctness.
+- Rendering style is controlled and may differ from real-world photos.
+
+---
+
+## License & Attribution
+
+This dataset is released under the **MIT License**.
+
+The included solution code is derived from **kamyu104/LeetCode-Solutions** (MIT License):  
+https://github.com/kamyu104/LeetCode-Solutions
+
+If you use this dataset in academic work, please cite the dataset and credit the original solution repository.
+
+---
+
+## Citation
+
+### BibTeX
+
+```bibtex
+@dataset{codeocr_leetcode_2025,
+  author       = {Maksonchek},
+  title        = {CodeOCR Dataset (Python Code Images + Ground Truth)},
+  year         = {2025},
+  publisher    = {Hugging Face},
+  url          = {https://huggingface.co/datasets/maksonchek/codeocr-dataset}
+}
+```