The LVM-Image-Aesthetic Filter (DLC) component is used to filter the data of an image that has a low aesthetic score.
Supported computing resources
Algorithm
The LVM-Image-Aesthetic Filter (DLC) component calculates aesthetic scores of images and filters the data of an image that has an excessively low aesthetic score to ensure the quality of the image. In most cases, the component is used for the subsequent training of image generation models.
Inputs and outputs
Input ports
The Read File Data component is used to read the Object Storage Service (OSS) path in which the training data is stored.
You can configure the Image Data OSS Path parameter to select the OSS directory where the image data is stored or select the image metadata file. For more information, see the parameter description in the following section.
You can use any component for image data preprocessing as the input.
Output port
The filtering results. For more information, see the parameter description in the following section.
Configure the component
You can configure the parameters of the LVM-Image-Aesthetic Filter (DLC) component in Machine Learning Designer. The following table describes the parameters.
Tab | Parameter | Required | Description | Default value | |
Field Settings | Image Data OSS Path | No | If no upstream component exists the first time you run this component, you must manually select the OSS directory in which the image data is stored. When the component runs, the image metadata file meta.jsonl is generated in the upper-level directory of the directory specified by this parameter. When you use the component to process the image data later, you can directly select the file meta.jsonl. | No default value | |
Output File OSS Path | Yes | The OSS directory in which the filtering results are stored. The results include the following files:
| No default value | ||
Output Filename | Yes | The file name of the filtering results. | result.jsonl | ||
Parameter Settings | Minimum Aesthetic Score | Yes | The minimum aesthetic score. | 0.3 | |
Maximum Aesthetic Score | Yes | The maximum aesthetic score. | 1 | ||
Execution Tuning | Number of Processes | Yes | The number of processes. | 4 | |
Select Resource Group | Public Resource Group | No | The instance type (CPU or GPU) and virtual private cloud (VPC) that you want to use. You must select the GPU instance type for the algorithm. | No default value | |
Dedicated resource group | No | The number of vCPUs, memory, shared memory, and number of GPUs that you want to use. | No default value | ||
Maximum Running Duration (seconds) | No | The maximum period of time for which the component can run. If the specified period of time is exceeded, the job is terminated. | No default value | ||