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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. |