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title: SVHN Recognition
emoji: 🚪
colorFrom: yellow
colorTo: purple
sdk: gradio
sdk_version: 4.12.0
app_file: app.py
pinned: false
license: mit
The Doorplate Recognition model is implemented using a deep convolutional neural network in PyTorch, with the objective of discerning multi-digit doorplate numbers from street view images. Utilizing the SVHN dataset extracted from Google Street View house numbers, the model is trained to identify sets of Arabic digits (0-9) within each image. The PyTorch implementation exhibits a commendable level of accuracy, achieving a tested precision of up to 89%. When users upload images containing doorplate numbers and submit them, the system yields precise recognition results for the digits present in the doorplate. This implementation provides a robust and user-friendly solution for doorplate number identification, demonstrating practical applications in the realm of image-based digit recognition.