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---
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
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