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Runtime error
| from tensorflow.keras.models import load_model | |
| from PIL import Image | |
| import numpy as np | |
| from flask import Flask, render_template, request | |
| from werkzeug.utils import secure_filename | |
| import os | |
| model = load_model('Trained.h5') | |
| def return_prediction(model, image): | |
| # Preprocess image | |
| img = Image.open(image).convert('RGB').resize((83, 83)) | |
| img = np.array(img).reshape(1, 83, 83, 3) / 255 | |
| # Predict the class | |
| classes = ['laptop', 'phone'] | |
| pred = model.predict(img) | |
| class_ind = round(pred[0][0]) | |
| # return prediction | |
| return classes[class_ind] | |
| ####### Start of the App | |
| app = Flask(__name__) | |
| def index(): | |
| return render_template('upload.html') | |
| def upload_file(): | |
| if request.method == 'POST': | |
| # storing file | |
| #f = request.files['file'] | |
| #fname = secure_filename(f.filename) | |
| #f.save("assests/" + fname) | |
| # prediction | |
| result = return_prediction(model, | |
| request.files['file']) #"assests/" + fname) | |
| return result | |
| return "nothing" | |
| if __name__ == "__main__": | |
| app.run(host="0.0.0.0", port=7860) | |