| from PIL import Image | |
| import numpy as np | |
| from tensorflow import keras | |
| import os | |
| def check(image): | |
| # Load the image | |
| # Preprocess the image | |
| image = image.resize((300, 300)) # Resize the image to the desired dimensions | |
| image = np.array(image) # Convert the image to a numpy array | |
| image = image.astype('float32') / 255.0 # Normalize pixel values between 0 and 1 | |
| # Expand dimensions and create a batch | |
| image = np.expand_dims(image, axis=0) | |
| model = keras.models.load_model('.\\image_classify.keras') | |
| # Make predictions | |
| predictions = model.predict(image) | |
| return predictions | |