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bone_fracture / app.py

nisharg nargund

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378363a 10 months ago

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	import os
	from flask import Flask, request, render_template
	from tensorflow.keras.models import load_model
	from tensorflow.keras.preprocessing import image
	import numpy as np

	app = Flask(__name__)

	# Load the trained model
	model = load_model('bone_fracture/bone_model.h5') # Update with your model's file path

	# Define class labels
	class_labels = ['Not Fractured', 'Fractured']

	@app.route('/', methods=['GET', 'POST'])
	def index():
	if request.method == 'POST':
	# Get the uploaded file from the form
	file = request.files['file']
	if file:
	# Save the file temporarily
	temp_path = 'temp.jpg'
	file.save(temp_path)

	# Load and preprocess the image
	img = image.load_img(temp_path, target_size=(224, 224))
	img_array = image.img_to_array(img)
	img_array = np.expand_dims(img_array, axis=0)
	img_array /= 255.0

	# Make a prediction
	prediction = model.predict(img_array)
	predicted_class = int(np.round(prediction)[0][0])
	predicted_label = class_labels[predicted_class]

	# Delete the temporary file
	os.remove(temp_path)

	return render_template('result.html', prediction=predicted_label)

	return render_template('index.html')

	if __name__ == '__main__':
	app.run(debug=True)