                                        "occur. Generally this should be left off except for "
                                        "during 'fit training'."})
          argument_list.append({"opts": ("-tia", "--timelapse-input-A"),
                                "action": DirFullPaths,
                                "dest": "timelapse_input_a",
                                "default": None,
                                "help": "For if you want a timelapse: "
                                        "The input folder for the timelapse. "
 
</s> remove         logger.debug("Loading batch: (image_count: %s, side: '%s', is_timelapse: %s, "
                     "do_shuffle: %s)", len(images), side, is_timelapse, do_shuffle)
 </s> add         logger.debug("Loading batch: (image_count: %s, side: '%s', is_display: %s, "
                     "do_shuffle: %s)", len(images), side, is_display, do_shuffle) </s> remove                      "training_image_size, %s, alignments_paths: %s, preview_scale: %s, "
                     "input_shape: %s, encoder_dim: %s, trainer: %s, pingpong: %s, "
                     "memory_saving_gradients: %s, predict: %s)",
                     self.__class__.__name__, model_dir, gpus, no_logs, training_image_size,
                     alignments_paths, preview_scale, input_shape, encoder_dim, trainer,
                     pingpong, memory_saving_gradients, predict)
 </s> add                      "warp_to_landmarks: %s, augment_color: %s, no_flip: %s, training_image_size, "
                     "%s, alignments_paths: %s, preview_scale: %s, input_shape: %s, encoder_dim: "
                     "%s, trainer: %s, pingpong: %s, memory_saving_gradients: %s, predict: %s)",
                     self.__class__.__name__, model_dir, gpus, no_logs, warp_to_landmarks,
                     augment_color, no_flip, training_image_size, alignments_paths, preview_scale,
                     input_shape, encoder_dim, trainer, pingpong, memory_saving_gradients, predict) </s> remove     def load_batches(self, mem_gen, images, side, is_timelapse,
 </s> add     def load_batches(self, mem_gen, images, side, is_display, </s> remove         self.samples = batch[0] if do_preview else None
 </s> add  </s> remove         logger.debug("Launching minibatch generator for queue (side: '%s', is_timelapse: %s)",
                     side, is_timelapse)
 </s> add         logger.debug("Launching minibatch generator for queue (side: '%s', is_display: %s)",
                     side, is_display)
        argument_list.append({"opts": ("-ac", "--augment-color"),
                              "action": "store_true",
                              "dest": "augment_color",
                              "default": False,
                              "help": "Perform color augmentation on training images. This has "
                                      "a 50%% chance of performing Contrast Limited Adaptive "
                                      "Histogram Equilization on the image. Then it randomly "
                                      "shifts the color balance +/- 8%% and the lighting +/- 30%% "
                                      "on each face fed to the model. Should help make the model "
                                      "less susceptible to color differences between the A and B "
                                      "set, but may increase training time."})
                                        "occur. Generally this should be left off except for "
                                        "during 'fit training'."})
        argument_list.append({"opts": ("-ac", "--augment-color"),
                              "action": "store_true",
                              "dest": "augment_color",
                              "default": False,
                              "help": "Perform color augmentation on training images. This has "
                                      "a 50%% chance of performing Contrast Limited Adaptive "
                                      "Histogram Equilization on the image. Then it randomly "
                                      "shifts the color balance +/- 8%% and the lighting +/- 30%% "
                                      "on each face fed to the model. Should help make the model "
                                      "less susceptible to color differences between the A and B "
                                      "set, but may increase training time."})
          argument_list.append({"opts": ("-tia", "--timelapse-input-A"),
                                "action": DirFullPaths,
                                "dest": "timelapse_input_a",
                                "default": None,
                                "help": "For if you want a timelapse: "
                                        "The input folder for the timelapse. "
keep add keep keep keep keep keep keep
 Color Augmentation method (#752)

* Color Augmentation: Implement testing code

* Tweak Contrast and Lighting augmentation amounts

* Prevent color augmentation from entering timelapse

* Remove all augmentations from preview images 
lib/cli.py