(pred)
| 26 | basemodel.load_weights(modelPath) |
| 27 | |
| 28 | def decode(pred): |
| 29 | char_list = [] |
| 30 | pred_text = pred.argmax(axis=2)[0] |
| 31 | for i in range(len(pred_text)): |
| 32 | if pred_text[i] != nclass - 1 and ((not (i > 0 and pred_text[i] == pred_text[i - 1])) or (i > 1 and pred_text[i] == pred_text[i - 2])): |
| 33 | char_list.append(characters[pred_text[i]]) |
| 34 | return u''.join(char_list) |
| 35 | |
| 36 | def predict(img): |
| 37 | width, height = img.size[0], img.size[1] |