def _OCRerror(x):
    ''' a, b, gamma sont les curseurs du réglage du niveau '''
    assert len(x)==3
    a,b,gamma = x[0], x[1], x[2]
    assert ticket_ocr.dtype == np.uint8
    assert 0<=a<b<=255

    img = ticket_ocr
    img[img >= a] = 255*(img[img >= a]-a)/(b-a) # niveau
    img[img < a] = 0
    img = ske.adjust_gamma(img, gamma)
    ocr_data = pytesseract.image_to_data(img, output_type=pytesseract.Output.DICT)
    conf = sum([float(x) for x in ocr_data['conf']])
    return -conf # il faut maximiser la confiance, donc minimiser -conf

x0 = [0,255,1.0]
bounds = [(0,255), (0,255), (0.01,9.99)]
cons = ({'type': 'ineq',
         'fun': lambda x: x[1] - x[0] - 1}) # b >= a + 1
res = spopt.minimize(_OCRerror, x0, method='cobyla', bounds=bounds, constraints=cons)