# Visual Text Recognition

Visual text recognition helps you convert printed text in images and videos into machine-encoded text. You can input a scanned document, a photo of a document, a scene-photo (such as the text on signs and billboards), or text superimposed on an image (such as in a meme) and output the words and individual characters present in the images. VTR lets you "digitize" text so that it can be edited, searched, stored, displayed and analyzed.

![](/files/-M_0sBzUqlXHLaintrO8)

{% hint style="info" %}
Please note: The current version of our VTR model is not designed for use with handwritten text, or documents with tightly-packed text (like you might see on the page of a novel, for example).
{% endhint %}

## How VTR works

VTR works by first detecting the location of text in your photos or video frames, then cropping the region where the text is present, and then finally running a specialized classification model that will extract text from the cropped image. To accomplish these different tasks, you will need to configure a workflow. You will then add these three models to your workflow:

* **Visual Text Detection**
* **1.0 Cropper**
* **Visual Text Recognition**

## Building a VTR workflow

{% tabs %}
{% tab title="gRPC Python" %}

```python
# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

post_workflows_response = stub.PostWorkflows(
    service_pb2.PostWorkflowsRequest(
        user_app_id=resources_pb2.UserAppIDSet(
            app_id="cdd79189eb6f44049b6c5b58f14a87e6"
        ),
        workflows=[
            resources_pb2.Workflow(
                id="visual-text-recognition-id",
                nodes=[
                    resources_pb2.WorkflowNode(
                        id="detect-concept",
                        model=resources_pb2.Model(
                            id="2419e2eae04d04f820e5cf3aba42d0c7",
                            model_version=resources_pb2.ModelVersion(
                                id="75a5b92a0dec436a891b5ad224ac9170"
                            )
                        )
                    ),
                    resources_pb2.WorkflowNode(
                        id="image-crop",
                        model=resources_pb2.Model(
                            id="ce3f5832af7a4e56ae310d696cbbefd8",
                            model_version=resources_pb2.ModelVersion(
                                id="a78efb13f7774433aa2fd4864f41f0e6"
                                )
                            ),
                            node_inputs=[
                                resources_pb2.NodeInput(node_id="detect-concept")
                            ]
                        ),
                    resources_pb2.WorkflowNode(
                        id="image-to-text",
                        model=resources_pb2.Model(
                            id="9fe78b4150a52794f86f237770141b33",
                            model_version=resources_pb2.ModelVersion(
                                id="d94413e582f341f68884cac72dbd2c7b"
                                )
                            ),
                            node_inputs=[
                                resources_pb2.NodeInput(node_id="image-crop")
                            ]
                        ),
                ]
            )
        ]
    ),
    metadata=metadata
)

if post_workflows_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Post workflows failed, status: " + post_workflows_response.status.description)
```

{% endtab %}

{% tab title="gRPC Java" %}

```java
import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiWorkflowResponse postWorkflowsResponse = stub.postWorkflows(
  PostWorkflowsRequest.newBuilder()
      .setUserAppId(UserAppIDSet.newBuilder().setAppId("{YOUR_APP_ID}"))
      .addWorkflows(
          Workflow.newBuilder()
              .setId("visual-text-recognition-id")
              .addNodes(
                  WorkflowNode.newBuilder()
                      .setId("detect-concept")
                      .setModel(
                          Model.newBuilder()
                              .setId("2419e2eae04d04f820e5cf3aba42d0c7")
                              .setModelVersion(
                                  ModelVersion.newBuilder()
                                      .setId("75a5b92a0dec436a891b5ad224ac9170")
                              )
                      )
              )
              .addNodes(
                  WorkflowNode.newBuilder()
                      .setId("image-crop")
                      .setModel(
                          Model.newBuilder()
                              .setId("ce3f5832af7a4e56ae310d696cbbefd8")
                              .setModelVersion(
                                  ModelVersion.newBuilder()
                                      .setId("a78efb13f7774433aa2fd4864f41f0e6")
                              )
                      )
                      .addNodeInputs(NodeInput.newBuilder().setNodeId("detect-concept"))
              )
              .addNodes(
                  WorkflowNode.newBuilder()
                      .setId("image-to-text")
                      .setModel(
                          Model.newBuilder()
                              .setId("9fe78b4150a52794f86f237770141b33")
                              .setModelVersion(
                                  ModelVersion.newBuilder()
                                      .setId("d94413e582f341f68884cac72dbd2c7b")
                              )
                      )
                      .addNodeInputs(NodeInput.newBuilder().setNodeId("image-crop"))
              )
      )
      .build()
);

if (postWorkflowsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Post workflows failed, status: " + postWorkflowsResponse.getStatus());
}
```

{% endtab %}

{% tab title="gRPC NodeJS" %}

```javascript
// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PostWorkflows(
    {
        user_app_id: {
            app_id: "e83440590d104cee97ef84af1856837d"
        },
        workflows: [
            {
                id: "visual-text-recognition-id",
                nodes: [
                    {
                        id: "detect-concept",
                        model: {
                            id: "2419e2eae04d04f820e5cf3aba42d0c7",
                            model_version: {
                                id: "75a5b92a0dec436a891b5ad224ac9170"
                            }
                        }
                    },
                    {
                        id: "image-crop",
                        model: {
                            id: "ce3f5832af7a4e56ae310d696cbbefd8",
                            model_version: {
                                id: "a78efb13f7774433aa2fd4864f41f0e6"
                            }
                        },
                        node_inputs: [
                            {node_id: "detect-concept"}
                        ]
                    },
                    {
                        id: "image-to-text",
                        model: {
                            id: "9fe78b4150a52794f86f237770141b33",
                            model_version: {
                                id: "d94413e582f341f68884cac72dbd2c7b"
                            }
                        },
                        node_inputs: [
                            {node_id: "image-crop"}
                        ]
                    },
                ]
            }
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            console.log(response.status);
            throw new Error("Post workflows failed, status: " + response.status.description);
        }
    }
);
```

{% endtab %}

{% tab title="cURL" %}

```
curl -X POST 'https://api.clarifai.com/v2/users/me/apps/{{app}}/workflows' \
    -H 'Authorization: Key {{PAT}}' \
    -H 'Content-Type: application/json' \
    --data-raw '{
        "workflows": [
            {
                "id": "visual-text-recognition-id",
                "nodes": [
                    {
                        "id": "detect-concept",
                        "model": {
                            "id": "2419e2eae04d04f820e5cf3aba42d0c7",
                            "model_version": {
                                "id": "75a5b92a0dec436a891b5ad224ac9170"
                            }
                        }
                    },
                    {
                        "id": "image-crop",
                        "model": {
                            "id": "ce3f5832af7a4e56ae310d696cbbefd8",
                            "model_version": {
                                "id": "a78efb13f7774433aa2fd4864f41f0e6"
                            }
                        },
                        "node_inputs": [
                            {
                                "node_id": "general-concept"
                            }
                        ]
                    },
                    {
                        "id": "image-to-text",
                        "model": {
                            "id": "9fe78b4150a52794f86f237770141b33",
                            "model_version": {
                                "id": "d94413e582f341f68884cac72dbd2c7b"
                            }
                        },
                        "node_inputs": [
                            {
                                "node_id": "image-crop"
                            }
                        ]
                    },
                ]
            }
        ]
    }'
```

{% endtab %}
{% endtabs %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://old-docs.clarifai.com/guide/v7.4/api-guide/workflows/common-workflows/visual-text-recognition-walkthrough.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.