Connect Base64.ai and Roboflow to Build Intelligent Automations
Enable Integrations or automations with these events of Base64.ai and Roboflow
Enable Integrations or automations with these events of Base64.ai and Roboflow
Actions
Scan a document by URL
Scans a document that is provided by a URL or Hydrate File. File can be an image (jpeg, png etc.), PDF, zip or an office document (.doc, .docx, etc.).
Scan a Document by Bytes
Scans a document that is provided by a string of bytes (e.g. data:image/png;base64,iVBORw0KGgoAAAANSUhEU...). File can be an image (jpeg, png etc.), PDF, zip or an office document (.doc, .docx, etc.).
Compute CLIP Similarity
Compute how closely an image matches a text prompt using Roboflow's CLIP model.
Create Classification Prediction
Generate class predictions for an image.
Run Instance Segmentation
Create instance segmentation predictions (masks and labels) for a given image.
Detect Objects in Image
Detect objects in an image and return their labels and bounding boxes.
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Frequently Asked Questions
To start, connect both your Base64.ai and Roboflow accounts to viaSocket. Once connected, you can set up a workflow where an event in Base64.ai triggers actions in Roboflow (or vice versa).
Absolutely. You can customize how Base64.ai data is recorded in Roboflow. This includes choosing which data fields go into which fields of Roboflow, setting up custom formats, and filtering out unwanted information.
The data sync between Base64.ai and Roboflow typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Base64.ai and Roboflow. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Roboflow
Roboflow is a leading platform for computer vision and AI model development, offering tools to streamline the process of building, training, and deploying machine learning models.
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