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Browse files- outputs/Dockerfile +16 -0
- uploads/templates_index.html +60 -0
outputs/Dockerfile
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FROM python:3.10
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# Install system libraries
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RUN apt-get update && apt-get install -y libgl1 git-lfs
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# Copy your app files
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COPY . /app
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WORKDIR /app
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# Pull LFS files
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RUN cd NAFNet && git lfs install && git lfs pull
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# Install Python dependencies
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RUN pip install -r requirements.txt
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CMD ["python", "app.py"]
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uploads/templates_index.html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Image Enhancement with NAFNet</title>
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<style>
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body { font-family: Arial, sans-serif; margin: 20px; }
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.image-container { display: flex; gap: 20px; margin-top: 20px; }
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img { max-width: 300px; height: auto; border: 1px solid #ccc; }
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.hidden { display: none; }
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</style>
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</head>
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<body>
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<h1>Upload Image for AI Enhancement (NAFNet)</h1>
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<input type="file" id="fileInput" accept="image/*">
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<button id="enhanceButton">Enhance Image</button>
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<div class="image-container hidden" id="imageResults">
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<div>
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<h3>Original Image:</h3>
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<img id="beforeImage" src="" alt="Before Image">
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</div>
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<div>
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<h3>Enhanced Image:</h3>
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<img id="afterImage" src="" alt="Enhanced Image">
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</div>
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</div>
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<script>
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document.getElementById('enhanceButton').addEventListener('click', function () {
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const fileInput = document.getElementById('fileInput');
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if (!fileInput.files.length) {
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alert('Please select an image.');
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return;
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}
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const file = fileInput.files[0];
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const formData = new FormData();
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formData.append('file', file);
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fetch('/process_image', {
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method: 'POST',
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body: formData,
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})
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.then(response => response.json())
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.then(data => {
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if (data.status === 'success') {
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document.getElementById('beforeImage').src = URL.createObjectURL(file);
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document.getElementById('afterImage').src = data.output_path;
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document.getElementById('imageResults').classList.remove('hidden');
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} else {
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alert('Processing failed: ' + data.message);
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}
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})
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.catch(error => console.error('Error:', error));
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});
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</script>
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</body>
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</html>
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