Visual Text Recognition
Work with text in images, just like you work with encoded text.
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Work with text in images, just like you work with encoded text.
Last updated
Was this helpful?
Was this helpful?
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.
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
# 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)