Make predictions for document data - Amazon SageMaker AI
Single predictionsBatch predictions

Make predictions for document data

The following procedures describe how to make both single and batch predictions for document datasets. Each Ready-to-use model supports both Single predictions and Batch predictions for your dataset. A Single prediction is when you only need to make one prediction. For example, you have one image from which you want to extract text, or one paragraph of text for which you want to detect the dominant language. A Batch prediction is when you’d like to make predictions for an entire dataset. For example, you might have a CSV file of customer reviews for which you’d like to analyze the customer sentiment, or you might have image files in which you’d like to detect objects.

You can use these procedures for the following Ready-to-use model types: expense analysis, identity document analysis, and document analysis.

Note

For document queries, only single predictions are currently supported.

Single predictions

To make a single prediction for Ready-to-use models that accept document data, do the following:

  1. In the left navigation pane of the Canvas application, choose Ready-to-use models.

  2. On the Ready-to-use models page, choose the Ready-to-use model for your use case. For document data, it should be one of the following: Expense analysis, Identity document analysis, or Document analysis.

  3. On the Run predictions page for your chosen Ready-to-use model, choose Single prediction.

  4. If your Ready-to-use model is identity document analysis or document analysis, complete the following actions. If you’re doing expense analysis or document queries, skip this step and go to Step 5 or Step 6, respectively.

    1. Choose Upload document.

    2. You are prompted to upload a PDF, JPG, or PNG file from your local computer. Select the document from your local files, and then the prediction results will generate.

  5. If your Ready-to-use model is expense analysis, do the following:

    1. Choose Upload invoice or receipt.

    2. You are prompted to upload a PDF, JPG, PNG, or TIFF file from your local computer. Select the document from your local files, and then the prediction results will generate.

  6. If your Ready-to-use model is document queries, do the following:

    1. Choose Upload document.

    2. You are prompted to upload a PDF file from your local computer. Select the document from your local files. Your PDF must be 1–100 pages long.

      Note

      If you're in the Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), or Europe (Frankfurt) regions, then the maximum PDF size for document queries is 20 pages.

    3. In the right side pane, enter queries to search for information in the document. The number of characters you can have in a single query is from 1–200. You can add up to 15 queries at a time.

    4. Choose Submit queries, and then the results generate with answers to your queries. You are billed once for each submissions of queries you make.

In the right pane Prediction results, you’ll receive an analysis of your document.

The following information describes the results for each type of solution:

  • For expense analysis, the results are categorized into Summary fields, which include fields such as the total on a receipt, and Line item fields, which include fields such as individual items on a receipt. The identified fields are highlighted on the document image in the output.

  • For identity document analysis, the output shows you the fields that the Ready-to-use model identified, such as first and last name, address, or date of birth. The identified fields are highlighted on the document image in the output.

  • For document analysis, the results are categorized into Raw text, Forms, Tables, and Signatures. Raw text includes all of the extracted text, while Forms, Tables, and Signatures only include information on the form that falls into those categories. For example, Tables only includes information extracted from tables in the document. The identified fields are highlighted on the document image in the output.

  • For document queries, Canvas returns answers to each of your queries. You can open the collapsible query dropdown to view a result, along with a confidence score for the prediction. If Canvas finds multiple answers in the document, then you might have more than one result for each query.

The following screenshot shows the results for a single prediction using the document analysis solution.

Screenshot of the results of a single prediction with the document analysis Ready-to-use model.

Batch predictions

To make batch predictions for Ready-to-use models that accept document data, do the following:

  1. In the left navigation pane of the Canvas application, choose Ready-to-use models.

  2. On the Ready-to-use models page, choose the Ready-to-use model for your use case. For image data, it should be one of the following: Expense analysis, Identity document analysis, or Document analysis.

  3. On the Run predictions page for your chosen Ready-to-use model, choose Batch prediction.

  4. Choose Select dataset if you’ve already imported your dataset. If not, choose Import new dataset, and then you are directed through the import data workflow.

  5. From the list of available datasets, select your dataset and choose Generate predictions. If your use case is document analysis, continue to Step 6.

  6. (Optional) If your use case is Document analysis, another dialog box called Select features to include in batch prediction appears. You can select Forms, Tables, and Signatures to group the results by those features. Then, choose Generate predictions.

After the prediction job finishes running, on the Run predictions page, you see an output dataset listed under Predictions. This dataset contains your results, and if you select the More options icon ( Vertical ellipsis icon representing a menu or more options. ), you can choose View prediction results to preview the analysis of your document data.

The following information describes the results for each type of solution:

  • For expense analysis, the results are categorized into Summary fields, which include fields such as the total on a receipt, and Line item fields, which include fields such as individual items on a receipt. The identified fields are highlighted on the document image in the output.

  • For identity document analysis, the output shows you the fields that the Ready-to-use model identified, such as first and last name, address, or date of birth. The identified fields are highlighted on the document image in the output.

  • For document analysis, the results are categorized into Raw text, Forms, Tables, and Signatures. Raw text includes all of the extracted text, while Forms, Tables, and Signatures only include information on the form that falls into those categories. For example, Tables only includes information extracted from tables in the document. The identified fields are highlighted on the document image in the output.

After previewing your results, you can choose Download prediction and download the results as a ZIP file.