image classifier part 5

predict.py

#importing and processing input image
import cv2
img = cv2.imread("sample_img.jpg") #loading input image
img = cv2.resize(img, (28, 28), interpolation = cv2.INTER_AREA) #resizing to input shape
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #chaging to grayscale format
img = cv2.bitwise_not(img) #the color scale was inverted, correcting inverted color scale
img = cv2.Canny(img, 50, 50) # removing noise

predict_data = np.array([img])/255 #changing image data to array
predict_data = predict_data.reshape(1,28, 28, 1) #reshaping to input shape

#predicting the input 
from tensorflow.keras import models
model = models.load_model('cnn_digitclass.model') #loading pre-savedd model
prediction = model.predict(predict_data) #gives array
predicted_number = np.argmax(prediction) #extracts predicted number