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Browse files- app.py +51 -0
- templates/index.html +52 -0
app.py
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from flask import Flask, render_template, request
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from PIL import Image
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from io import BytesIO
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import base64
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from predict import predict_potato, predict_tomato
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from model import potato_model, tomato_model
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import torch
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app = Flask(__name__)
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# Load models
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potato_model.load_state_dict(torch.load("models\\potato_model_statedict__f.pth", map_location=torch.device('cpu')))
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tomato_model.load_state_dict(torch.load("models\\tomato_model_statedict__f.pth", map_location=torch.device('cpu')))
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# potato_model = torch.load("Models\\potato_model_statedict__f.pth", map_location=torch.device('cpu'))
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# potato_model.load_state_dict(torch.load("Models\\potato_model_statedict__f.pth", map_location=torch.device('cpu')))
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# tomato_model = torch.load("Models\\tomato_model_statedict__f.pth", map_location=torch.device('cpu'))
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# potato_model.load_state_dict(torch.load("Models\\tomato_model_statedict__f.pth", map_location=torch.device('cpu')))
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@app.route('/')
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def home():
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# Default to potato model
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return render_template('index.html', model_type='potato')
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@app.route('/predict', methods=['POST'])
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def predict():
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# Get the selected model type
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model_type = request.form['model_type']
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# Get the image file from the request
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file = request.files['file']
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if model_type == 'tomato':
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class_name, probability, image = predict_tomato(file, tomato_model)
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background_image = r'static\\tomato_background.jpg'
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else:
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class_name, probability, image = predict_potato(file, potato_model)
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background_image = r'static\\potato_background.webp'
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# Convert image to base64 format
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buffered = BytesIO()
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image.save(buffered, format="JPEG")
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img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
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# Pass the base64 encoded image and background image to the frontend
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return render_template('index.html', image=img_str, class_name=class_name, probability=f"{probability * 100:.2f}%", background_image=background_image)
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if __name__ == '__main__':
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app.run(debug=True)
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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>Plant Disease Classification</title>
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<style>
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body {
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background-image: url("{{ background_image }}");
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background-size: cover;
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background-position: center;
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font-family: Arial, sans-serif;
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color: #fff;
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text-align: center;
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padding: 50px;
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}
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.container {
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background-color: rgba(0, 0, 0, 0.7);
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padding: 30px;
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border-radius: 10px;
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display: inline-block;
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}
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img {
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max-width: 100%;
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height: auto;
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border-radius: 10px;
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margin-top: 20px;
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}
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</style>
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</head>
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<body>
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<div class="container">
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<h1>Plant Disease Classification</h1>
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<form method="POST" action="/predict" enctype="multipart/form-data">
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<label for="model_type">Choose a model:</label>
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<select name="model_type" id="model_type">
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<option value="potato" selected>Potato</option>
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<option value="tomato">Tomato</option>
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</select>
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<br><br>
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<input type="file" name="file" accept="image/*" required>
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<br><br>
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<button type="submit">Predict</button>
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</form>
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{% if image %}
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<h2>Prediction: {{ class_name }}</h2>
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<h3>Confidence: {{ probability }}</h3>
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<img src="data:image/jpeg;base64,{{ image }}" alt="Uploaded Image">
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{% endif %}
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</div>
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</body>
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</html>
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