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| from flask import Flask, render_template, request, send_file, make_response | |
| # Import your attendance model and processing functions | |
| from run import predict_and_show | |
| import pandas as pd | |
| app = Flask("Ogs") | |
| def index(): | |
| return render_template('index.html') | |
| def upload(): | |
| if 'file' not in request.files: | |
| return "No file part" | |
| file = request.files['file'] | |
| if file.filename == '': | |
| return "No selected file" | |
| # Process the image using your attendance model | |
| data = predict_and_show(file) | |
| html_content = "<html><body><h1>Attendance Report</h1><ul>" | |
| for item in data: | |
| html_content += f"<li>{item}</li>" | |
| html_content += "</ul></body></html>" | |
| # Create a response object with the generated HTML | |
| response = make_response(html_content) | |
| response.headers['Content-Type'] = 'text/html' | |
| return response | |
| if __name__ == '__main__': | |
| app.run(debug=True, host='0.0.0.0', port=7860) | |