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nazlicanto/defectdetection

sourceHugging Facemitupdated 3y agoView on Hugging Face
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App README

๐Ÿ› ๏ธ PCB Defect Detection App

This app allows users to upload PCB images and detect defects using state-of-the-art machine learning models.

๐ŸŒŸ Features

  • โ€”Image Upload: Easily upload your PCB images and get instant defect predictions.
  • โ€”Visualization: Visualize the detected defects on the PCB image.
  • โ€”Defect Types: The app can identify multiple types of defects and highlight them uniquely for easy identification.

๐Ÿš€ Usage

1๏ธโƒฃ Uploading an Image:

  • โ€”Click on the "Browse files" button.
  • โ€”Select a PCB image from your device.
  • โ€”Sit back and relax! Let the model churn through the image and present its findings.

2๏ธโƒฃ Interpreting Results:

  • โ€”It will display the original image alongside the predicted defect mask.
  • โ€”Different defect types will be highlighted using unique grayscale values.

Model Details

The app utilzes the Segformer model trained on a custom PCB dataset. The model has been fine-tuned to detect:

  • โ€”Incorrect Installation
  • โ€”Short Circuit
  • โ€”Dry Joints

... commonly found defects in PCBs.

๐Ÿ“œ Requirements

The app is built using Streamlit and leverages the Hugging Face Transformers library for model inference. For a full list of requirements, refer to the requirements.txt file.

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference