Update README.md

README.md

@@ -7,4 +7,101 @@ datasets:
 - DannyLuna/recaptcha-57k-images-dataset
 tags:
 - code
----
+---
+
+# recaptcha-classification-57k
+
+YOLO based image classification model for reCAPTCHA images. This
+model is used by [`vision-ai-recaptcha-solver`](https://github.com/DannyLuna17/VisionAIRecaptchaSolver) to solve reCAPTCHA challenges.
+
+## Model summary
+
+- Task: image classification
+- Format: ONNX (`recaptcha_classification_57k.onnx`) and PyTorch (`recaptcha_classification_57k.pt`)
+- Architecture: Ultralytics YOLO classification
+- Labels: 14 classes (13 target classes + `other`)
+- Trained on a [57k images dataset](https://huggingface.co/datasets/DannyLuna/recaptcha-57k-images-dataset).
+
+## Labels
+
+Target classes in this model:
+
+- bicycle
+- bridge
+- bus
+- car
+- chimney
+- crosswalk
+- fire hydrant
+- motorcycle
+- mountain
+- palm tree
+- stairs
+- tractor
+- traffic light
+
+The `other` class represents non-target/background tiles and is intentionally
+not treated as a match by the solver.
+
+## Intended use
+
+- Classifying individual reCAPTCHA tile images as part of research or testing
+  workflows.
+- Integrated use with the [`vision-ai-recaptcha-solver`](https://github.com/DannyLuna17/VisionAIRecaptchaSolver) package.
+
+## Training data
+
+Trained on the dataset:
+[`DannyLuna/recaptcha-57k-images-dataset`](https://huggingface.co/datasets/DannyLuna/recaptcha-57k-images-dataset).
+
+## Training procedure
+
+Trained with Ultralytics YOLO classification and exported to ONNX with dynamic
+input shapes.
+
+## How to use
+
+### Ultralytics (recommended)
+
+```python
+from ultralytics import YOLO
+
+model = YOLO("recaptcha_classification_57k.onnx", task="classify")
+results = model("tile.jpg")
+
+probs = results[0].probs
+top1_idx = int(probs.top1)
+print(model.names[top1_idx], float(probs.top1conf))
+```
+
+### vision-ai-recaptcha-solver
+
+```python
+from vision_ai_recaptcha_solver import RecaptchaSolver, SolverConfig
+
+with RecaptchaSolver(SolverConfig()) as solver:
+    result = solver.solve(
+        website_key="your_site_key",
+        website_url="https://example.com/your-page-with-recaptcha",
+    )
+    print(result.token)
+```
+
+## Model files
+
+- `recaptcha_classification_57k.onnx`
+- `recaptcha_classification_57k.pt`
+
+## Limitations
+
+- The reCAPTCHA system changes over time; accuracy may degrade on new variants.
+- False positives are possible on visually similar objects.
+
+## Ethical considerations
+
+Use this model only for lawful, authorized purposes such as research, benchmarking, or
+testing in controlled environments.
+
+## License
+
+MIT License. See the repository `LICENSE` file for details.