Connect urlbox and Roboflow to Build Intelligent Automations
Enable Integrations or automations with these events of urlbox and Roboflow
Enable Integrations or automations with these events of urlbox and Roboflow
Actions
Full Page Screenshots Using URL
Capture an entire scrollable webpage from a URL and return the screenshot image.
Render HTML Screenshot
Generate a PNG, JPG, or PDF from provided HTML (with optional CSS), supporting viewport size, full-page capture, and high-resolution scaling.
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 urlbox and Roboflow accounts to viaSocket. Once connected, you can set up a workflow where an event in urlbox triggers actions in Roboflow (or vice versa).
Absolutely. You can customize how urlbox 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 urlbox 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 urlbox 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 urlbox
Urlbox is a screenshot API that allows you to generate images from a URL or HTML
Learn MoreAbout 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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