---
license: mit
language:
- en
pipeline_tag: image-classification
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.