metadata

title: Defectdetection
emoji: 🚀
colorFrom: blue
colorTo: yellow
sdk: streamlit
sdk_version: 1.27.2
app_file: app06.py
pinned: false
license: mit

🛠️ PCB Defect Detection App

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

🌟 Features

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

🚀 Usage

1️⃣ Uploading an Image:

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

2️⃣ Interpreting Results:

It will display the original image alongside the predicted defect mask.
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:

Incorrect Installation
Short Circuit
Dry Joints

... commonly found defects in PCBs.

📜 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