Keras make prediction on image sequence

make_prediction.py

from IPython.display import HTML, display
import cv2 as cv
import os
import matplotlib.pyplot as plt

def make_prediction(model, movie, nframe, classes, shape=(224, 224), nchan=3):
    video = cv.VideoCapture(movie)
    frames = []
    while True:
        grabbed, frame = video.read()
        if not grabbed:
            break
        frame = cv.cvtColor(frame, cv.COLOR_BGR2RGB)
        frame = cv.resize(frame, shape)
        frames.append(frame)
        
    jump = len(frames)//nframe
    frames = frames[::jump][:nframe]

    checking = movie.split(os.path.sep)[-2]
    display(HTML('<b>Checking %s</b>' % checking))    
    
    plt.figure(figsize=(18, 10))
    for i, frame in enumerate(frames[::2]):
        plt.subplot(1, nframe//2, i+1)
        plt.imshow(frame)
    plt.show()

    seq = np.array(frames)
    seq = np.reshape(seq, (1, nframe,) + shape + (nchan,))
    res = model.predict(seq)
    cl = np.argmax(res).astype('int')
    cl = classes[cl]
    
    style='color: green'
    response = "CORRECT"
    if cl != checking:
        style='color: red'
        response="WRONG"
        
    display(HTML('Result:  <b style="%s">%s : %s</b>' % (style, response, cl)))