(self, images, masks)
| 119 | return image, one_hot_map |
| 120 | |
| 121 | def init(self, images, masks): |
| 122 | ds = tf.data.Dataset.from_tensor_slices((images, masks)) |
| 123 | if self.opt["use_shuffle"]: |
| 124 | ds = ( |
| 125 | ds.shuffle(len(images)) |
| 126 | .map(self.parse_data, num_parallel_calls=AUTOTUNE) |
| 127 | .batch(self.opt["batch_size"], drop_remainder=True) |
| 128 | .prefetch(AUTOTUNE) |
| 129 | ) |
| 130 | else: |
| 131 | ds = ( |
| 132 | ds.map(self.parse_data, num_parallel_calls=AUTOTUNE) |
| 133 | .batch(self.opt["batch_size"], drop_remainder=True) |
| 134 | .prefetch(AUTOTUNE) |
| 135 | ) |
| 136 | return ds |
| 137 | |
| 138 | |
| 139 | class LoadClassData: |
nothing calls this directly
no outgoing calls
no test coverage detected