INNER CODE UNIT · Python

img

minivision-ai/Silent-Face-Anti-Spoofing · test.py:57

        img = image_cropper.crop(**param)
        start = time.time()
        prediction += model_test.predict(img, os.path.join(model_dir, model_name))
        test_speed += time.time()-start

    # draw result of prediction
    label = np.argmax(prediction)
    value = prediction[0][label]/2
    if label == 1:
        print("Image '{}' is Real Face. Score: {:.2f}.".format(image_name, value))
        result_text = "RealFace Score: {:.2f}".format(value)
        color = (255, 0, 0)
    else:
        print("Image '{}' is Fake Face. Score: {:.2f}.".format(image_name, value))
        result_text = "FakeFace Score: {:.2f}".format(value)
        color = (0, 0, 255)
    print("Prediction cost {:.2f} s".format(test_speed))
    cv2.rectangle(

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