Inference on video

inference.py

# Infer on live video
from math import ceil
import subprocess
import cv2

TEST_FRAMES = 500

# Initialize camera
cap = cv2.VideoCapture(0)
# Check if camera opened successfully
if (cap.isOpened() == False): 
    print("Unable to read camera feed")
    TEST_FRAMES = 0

# Start processing video
for i in range(TEST_FRAMES):
    ret, frame = cap.read()
    if not ret: continue
    x_pred = frame_preprocessor.process(frame)
    y_pred = model.predict(x_pred)[0]
    conf_negative = y_pred[NEG_IDX]
    conf_positive = y_pred[POS_IDX]
    cla = CLASSES[np.argmax(y_pred)]
    if cla == CLASSES[POS_IDX]:
        subprocess.call(['say',  CLASSES[POS_IDX]])
    progress = int(100 * (i / TEST_FRAMES))
    message = 'testing {}%  conf_neg = {:.02f} conf_pos = {:.02f}   class = {}         \r'.format(progress, conf_negative, conf_positive, cla)
    sys.stdout.write(message)
    sys.stdout.flush()

cap.release()