Help Center/ ModelArts/ Data Processing/ Description of Built-in Operators for Data Processing/ Data Augmentation/ Data Transfer Between Domains
Updated on 2024-06-12 GMT+08:00
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Data Transfer Between Domains

CycleGAN Operator Overview

CycleGAN operator generates images for domain transfer based on CycleGAN, that is, converts one type of images into another, or converts samples in the X space into samples in the Y space. CycleGAN can use non-paired data for training. During model training, two inputs are supported, indicating the source domain and target domain of data, respectively. After the training is complete, all images transferred from the source domain to the target domain are generated.

Table 1 Advanced parameters of the CycleGAN operator

Name

Default

Description

do_validation

True

Whether to validate data. The default value is True, which indicates that data is validated before being generated. False indicates data is generated directly.

image_channel

3

Number of channels of the image

image_height

256

Image height. The value must be 2 to the power of n.

image_width

256

Image width. The value must be 2 to the power of n.

batch_size

1

Number of samples for batch training

max_epoch

100

Number of dataset epochs during training

g_learning_rate

0.0001

Learning rate for the generator training

d_learning_rate

0.0001

Learning rate for the discriminator training

log_frequency

5

Logging frequency (counted by step)

save_frequency

5

Model save frequency (counted by epoch)

predict

False

Whether to perform inference and prediction. The default value is False. If this parameter is set to True, you need to set resume to the OBS path where the trained model is stored.

resume

empty

If predict is set to True, enter the OBS path where the TensorFlow model file is stored for inference and prediction. Currently, only models in .pb format are supported. Example: obs://xxx/xxxx.pb.

The default value is empty.

Data Input

The following two types of operator input are available:

  • Datasets: Select a dataset and its version created on the ModelArts console from the drop-down list. Ensure that the dataset type be the same as the scenario type selected in this task.
  • OBSCatalog: Operator image_generation does not require labeling information and its input supports single-level or dual-level directories, and the storage structure supports single-level or dual-level mode.

The single-level directory structure is as follows:

image_folder----0001.jpg           
            ----0002.jpg            
            ----0003.jpg            
            ...            
            ----1000.jpg

The dual-level directory structure is as follows:

image_folder----sub_folder_1----0001.jpg                            
                            ----0002.jpg                            
                            ----0003.jpg                            
                            ...                            
                            ----0500.jpg            
            ----sub_folder_2----0001.jpg                            
                            ----0002.jpg                           
                            ----0003.jpg                            
                            ...                            
                            ----0500.jpg
                            ...            
            ----sub_folder_100----0001.jpg                            
                              ----0002.jpg                            
                              ----0003.jpg                            
                              ...                            
                              ----0500.jpg

Output Description

The output directory structure is as follows: The folder model stores model frozen PB for inference, the folder samples stores the output images during training, and the folder Data stores the images generated by the training model.

train_url----model----CYcleGan_epoch_10.pb                  
                  ----CYcleGan_epoch_20.pb                  
                  ...                 
                  ----CYcleGan_epoch_1000.pb         
         ----samples----0000_0.jpg                   
                   ----0000_1.jpg                  
                   ...                   
                   ----0100_15.jpg         
         ----Data----CYcleGan_0_0.jpg                 
                 ----CYcleGan_0_1.jpg                 
                 ...                 
                 ----CYcleGan_16_8.jpg         
         ----output_0.manifest

A manifest file example is as follows:

{
	"id": "xss",
	"source": "obs://home/fc8e2688015d4a1784dcbda44d840307_14.jpg",
	"usage": "train", 
	"annotation": [
		{
			"name": "Cat", 
			"type": "modelarts/image_classification"
		}
	]
}

Parent topic: Data Augmentation