Example #1
0
def recognition_digit_image(fname, digit = 100):
    im = cv2.imread(fname)
    im = img.change_size_with_size(im, 28, 28)
    im = img.change_grayscale(im)
    im = 255. - im
    input_data = im
    input_data = input_data.astype(np.float64)
    input_data = im / im.max()
    tmp_data = np.reshape(input_data, (28*28, 1))

    neuro_obj.test(tmp_data, teach_data)
    output = neuro_obj.get_output()

    if digit >=0 and digit <= 9:
        if neuro_obj.get_max_output_index() == digit : print "judged(success):", neuro_obj.get_max_output_index()
        else                                         : print "judged(miss)   :", neuro_obj.get_max_output_index()
Example #2
0
def recognition_digit_image(fname, digit = 100):
    im = cv2.imread(fname)
    im = img.change_size_with_size(im, 28, 28)
    im = img.change_grayscale(im)
    im = 255 - im
    input_data = im
    input_data = input_data.astype(np.float64)
    input_data = im / im.max()
    input_data = np.reshape(input_data, (1, 28*28))
    neuro_obj.test(input_data, teach_data)
    output = neuro_obj.get_output()

    if digit >=0 and digit <= 9:
        print "judged:", neuro_obj.get_max_output_index(),
        print ", target order:", np.where(np.fliplr(np.argsort(output)) == digit)[1] + 1,
        print ", order array:", np.fliplr(np.argsort(output))
    else:
        print "judged:", neuro_obj.get_max_output_index(),
        print ", order array:", np.fliplr(np.argsort(output))

    cv2.imshow("input_data", im)
    cv2.waitKey(0)                                                                                                                                                 
    cv2.destroyAllWindows()