mnist_cnn_cam.py

import numpy as np
import cv2
import tensorflow as tf
import tensorflow.keras as keras

model = keras.models.load_model('models/mnist_cnn.h5')

cap = cv2.VideoCapture(0)
ret, frame = cap.read()
print(frame.shape)

while True:
    ret, frame = cap.read()
    img = cv2.flip(frame, 0) # vertical flip	
    x,y,w,h  = 200,100,200,200		
    roi = img[y:y+h, x:x+w]	
    roi_gray= cv2.cvtColor(roi, cv2.COLOR_RGB2GRAY)		
    ret,roi_thresh = cv2.threshold(roi_gray,130,255,cv2.THRESH_BINARY_INV)
    roi_thresh = cv2.dilate(roi_thresh, (3, 3))
    roi_small = cv2.resize(roi_thresh, (28, 28), interpolation=cv2.INTER_CUBIC)
    x_test=roi_small/255.0
    x_test=x_test.reshape(-1,28,28,1)

    pred=model.predict(x_test)
    ans =np.argmax(pred[0])

    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 3)	
    cv2.putText(img, str(ans), (x, y), cv2.FONT_HERSHEY_DUPLEX, 2, (0, 255, 255), 3)
    cv2.imshow('Cam', img)
    cv2.imshow('Thresh', roi_thresh)	
    keypress = cv2.waitKey(1) & 0xFF # keypress by user 
    if keypress == ord("q"): # press q to quit
        break
		
# free up memory
cap.release()
cv2.destroyAllWindows()