(self, image)
| 151 | self.model = load_model(file_path) |
| 152 | |
| 153 | def predict(self, image): |
| 154 | if K.image_dim_ordering() == 'th' and image.shape != (1, 3, IMAGE_SIZE, IMAGE_SIZE): |
| 155 | image = resize_with_pad(image) |
| 156 | image = image.reshape((1, 3, IMAGE_SIZE, IMAGE_SIZE)) |
| 157 | elif K.image_dim_ordering() == 'tf' and image.shape != (1, IMAGE_SIZE, IMAGE_SIZE, 3): |
| 158 | image = resize_with_pad(image) |
| 159 | image = image.reshape((1, IMAGE_SIZE, IMAGE_SIZE, 3)) |
| 160 | image = image.astype('float32') |
| 161 | image /= 255 |
| 162 | result = self.model.predict_proba(image) |
| 163 | print(result) |
| 164 | result = self.model.predict_classes(image) |
| 165 | |
| 166 | return result[0] |
| 167 | |
| 168 | def evaluate(self, dataset): |
| 169 | score = self.model.evaluate(dataset.X_test, dataset.Y_test, verbose=0) |
no test coverage detected