In the process of data cleaning and processing, image data collection and processing also play a crucial role. The Supametas.AI platform offers a convenient local image import feature, enabling you to efficiently upload and manage image data. This article will guide you step by step on how to create an image import task and explain each step in detail to help you get started quickly.
1. Create a New Task
First, in the dataset detail page, select the "Local Image Import" option from the "Import Data Source" menu, and then click the "New Task" button.
- Task Naming: Enter a task name with no more than 20 characters to facilitate quick identification and management in the task list.
2. Upload Local Image Files
After naming the task, proceed to the image file upload stage:
- Upload Methods:
- You can drag and drop local images into the upload area or click the upload button to select files.
- Supported File Formats:
- The platform supports
.jpgand.pngimage formats.
- The platform supports
- File Limits:
- A maximum of 50 image files can be uploaded per task;
- The size of each file must not exceed 200MB.
- Helpful Tip:
- Ensure that the images uploaded within the same task have similar content, as this will help improve the accuracy of parameter retrieval and output processing.
3. Task Settings
The task settings stage is similar to other data import tasks, with the main goal being to ensure the system can correctly process the uploaded images:
- Parsing Method: Choose the appropriate parsing method based on the image type to ensure the system can accurately extract information from the images.
4. Retrieve Parameters
In the parameter retrieval stage, you need to configure how the system will extract data from the images:
- Default Fields:
- Image Text: The system will automatically attempt to recognize and extract text information from the image.
- Custom Fields:
- If you need to capture specific information from the image (such as nicknames), you can enable the custom field feature.
- When adding custom fields, use English for the field names and provide detailed descriptions to improve extraction accuracy.
5. Output Settings
After configuring the parameter retrieval, you need to set the output method to determine the format in which the extracted data will be saved:
- Output Format Selection:
- You can choose to save the data in JSON format, which is convenient for subsequent API calls and processing;
- Or choose Markdown format, which is more suitable for building knowledge bases and displaying documents.
6. Save or Execute the Task Immediately
Finally, based on your needs, choose one of the following execution methods:
- Save and Execute Later:
- Save the task to the task list for future manual execution.
- Execute Task Immediately:
- If the configuration is correct and you are ready, click the "Execute Task Now" button, and the system will start processing the uploaded images and import the extracted data into the specified dataset.
The image import feature is not only intuitive to operate but also offers flexible task settings and data output options to help you efficiently manage and integrate image data. Whether you are batch processing product images or need to extract text from images, the platform provides reliable technical support.
