- Offline analysis: Analyze model performance in a Jupyter notebook, Excel, or other data analysis tools.
- Integration with other systems: Feed predictions into downstream applications or custom MLOps pipelines.
- Custom reporting: Create detailed reports and visualizations on model accuracy and behavior.
| Location | Use case |
|---|---|
| Catalog | Best for when you want to search for and select specific data rows that have predictions you want to export. |
| Model | Ideal for when you need to export predictions from a particular model run. |
| Annotate | Use this when you want to export predictions for data rows that are part of a specific project. |
Step-by-step instructions
Follow these simple steps to export your predictions:Step 1: Select your data
First, navigate to the Catalog, Model, or Annotate section and select the data rows with the predictions you want to export.Step 2: Start the export
From the Manage selection menu that appears, choose Export data. This will open the Export panel where you can customize your export.Step 3: Choose your export options
In the Export panel, you can select what information you want to include in your export file. Depending on where you export your data from (i.e., Catalog, Annotate, Model), you can choose to include these details in your export:- Data row details
- Metadata
- Attachments
- MMC code executions
- Project details
- Performance details
- Label details
- Interpolated frames
- Model run details
- Predictions
- Embeddings
- Model type override
- Export labels from projects
- Export labels and predictions from model runs
Step 4: Generate the export file
Once you’ve selected your options, click Export JSON. Labelbox will then start building your export file.Step 5: Download your results
When your export is ready, you’ll see a Download link in the Notifications Center. Clicking this will give you two options for downloading your results:| Download method | Description |
|---|---|
| Browser download | This is the quickest way to get your file. Click the Download button to save the results directly to your computer. Important: Don’t close your browser until the download is complete, or the file will be incomplete. |
| Python SDK script | For large datasets, it’s better to download using a Python script. The download panel will provide you with a sample script you can copy. This allows the download to happen in the background, so you don’t have to worry about closing your browser. You’ll need a Labelbox API key to run the script. Click the Code sample button to view a sample Python script to download your export results based on the selected options. |