Instructions to use Romey1010/captcha-solver-v3-color-agnostic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Romey1010/captcha-solver-v3-color-agnostic with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Romey1010/captcha-solver-v3-color-agnostic", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
CAPTCHA Solver v3 (Color-Agnostic)
Retrained color-agnostic CAPTCHA solver model for the excited-pascal scraper project.
Files
- captcha_model.pkl - Random Forest classifier (97.7% test accuracy)
- captcha_scaler.pkl - StandardScaler for feature normalization
Usage
from huggingface_hub import hf_hub_download
import joblib
model_path = hf_hub_download("Romey1010/captcha-solver-v3-color-agnostic", "captcha_model.pkl")
scaler_path = hf_hub_download("Romey1010/captcha-solver-v3-color-agnostic", "captcha_scaler.pkl")
model = joblib.load(model_path)
scaler = joblib.load(scaler_path)
Training
Trained on grayscale-normalized CAPTCHA character segments with structural features (pixel density, edge ratios, quadrant distributions). See the project repo for full training pipeline.
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