A Machine Learning Tool that Converts Screenshots of UIs into HTML/CSS Code
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Screenshot to Code is a powerful tool that uses machine learning to convert screenshots of user interfaces (UIs) into front-end code (HTML/CSS). The tool processes images using deep learning techniques, providing developers with a fast and accurate way to generate responsive and customizable UI code from graphical designs.
The tool uses a Convolutional Neural Network (CNN) to analyze the image structure, followed by a sequence-to-sequence (Seq2Seq) model to generate the HTML and CSS code. The workflow is as follows:
- Upload a Screenshot: Upload a PNG or JPG file of the UI you want to convert.
- Image Preprocessing: The image is resized, normalized, and fed into the CNN model.
- Code Prediction: The model outputs the predicted HTML/CSS code.
- Download & Edit: Copy the generated code, and integrate it into your project.
- Automatic Code Generation: Convert UI screenshots directly into responsive front-end code.
- Web-Based Interface: Easily accessible through a user-friendly web interface.
- Pre-trained Model: Leverage a pre-trained deep learning model for fast predictions.
- Customizable Output: Modify and improve the generated code to suit your needs.
- Supports Common Image Formats: PNG, JPG.
Follow these steps to set up the project on your local machine.
- Python 3.x
- Pip (Python package manager)
- Recommended: Virtual Environment
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Clone the Repository:
git clone https://github.com/Techsynx/screenshot-to-code.git
cd screenshot-to-code -
Create a Virtual Environment:
python3 -m venv venv
source venv/bin/activate # For Linux/Mac.\venv\Scripts\activate # For Windows -
Install Required Dependencies:
pip install -r requirements.txt
-
Download Pre-trained Model:
wget https://path-to-your-model/trained_model.h5 -O models/trained_model.h5
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Run the Application:
python app.py
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Access the App:
Open your browser and go tohttp://127.0.0.1:5000.
Once the application is running, follow these steps:
- Step 1: Upload your screenshot.
- Step 2: Wait for the tool to process and generate the HTML/CSS code.
- Step 3: Copy and paste the code into your editor or download the result.
Sample Code Output:
<!DOCTYPE html>
<html>
<head>
<style>
body { font-family: Arial, sans-serif; }
.container { width: 80%; margin: auto; }
h1 { color: #0066cc; }
</style>
</head>
<body>
<div class="container">
<h1>Generated HTML/CSS Code</h1>
<p>This code was generated by Screenshot to Code.</p>
</div>
</body>
</html>
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The following technologies and frameworks are used to build this project:
| Technology | Purpose |
|---|---|
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Core programming language |
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Deep Learning model |
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Web framework |
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Generated code output |
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Generated code output |
This project is licensed under the MIT License. See the LICENSE file for more details.
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated!
- Fork the Project.
- Create a Branch (
git checkout -b feature/AmazingFeature). - Commit Your Changes (
git commit -m 'Add some AmazingFeature'). - Push to the Branch (
git push origin feature/AmazingFeature). - Open a Pull Request.
Have questions or suggestions? Feel free to reach out to the project maintainer:
- Email: techsynxx@gmail.com
- GitHub: @Techsynx
You can add custom SVGs and animations to further enhance the visuals of the README. Here’s an example of how to include an SVG with CSS animations:
.jpeg){kind=link}
