WorkflowsBlocks
YOLOv8 Instance Segmentation
Model
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Use YOLOv8 Instance Segmentation to Build Computer Vision Pipelines and Applications

Connect YOLOv8 Instance Segmentation to other blocks to build a custom workflow.
Build a Workflow
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Filter
AWS Secrets Retriever
Relative Static Crop
Crop
Absolute Static Crop
LMM
Model

YOLOv8 Instance Segmentation

YOLOv8 Instance Segmentation is a type of Roboflow Instance Segmentation Model.
Webhook Publish
Super Annotator
Non Empty Predictions Tagger
Prediction Alarm
Filter
CSV Sink
Kafka Publish
Detection Offset
Detection Filter
Crop
Active Learning Data Collector
Detections Consensus

Build a Custom Vision AI Application

Connect pre-trained models, open source models, LLM APIs, advanced logic, and external applications. Deploy as an API endpoint, on-prem, or at the edge.
FilterTransformation

Filter

Conditionally filter and output data fields based on boolean conditions from a preceding workflow step.
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AWS Secrets RetrieverTransformation

AWS Secrets Retriever

Retrieve and manage secrets from AWS Secrets Manager for use in workflow automation.
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Relative Static CropTransformation

Relative Static Crop

Use relative coordinates for cropping.
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CropTransformation

Crop

Create dynamic crops from a detections model.
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Webhook PublishSink

Webhook Publish

Securely transmit data to specified webhooks using HMAC-SHA512 for payload authentication, ensuring data integrity and confidentiality.
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Super AnnotatorSink

Super Annotator

Enhance images with visual annotations based on detection predictions, combining bounding boxes and labels for clarity.
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Non Empty Predictions TaggerTransformation

Non Empty Predictions Tagger

Tag batches of images with boolean flags indicating the presence or absence of predictions for various detection types.
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Prediction AlarmTransformation

Prediction Alarm

Monitor and trigger an alarm if the count of specified prediction classes within a defined timeframe exceeds a set threshold.
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Workflow Templates

Explore pre-made templates for specific use cases.
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Explore Popular Combinations Using YOLOv8 Instance Segmentation

YOLOv8 Instance Segmentation to Active Learning Data Collector

Build a computer vision workflow that connects YOLOv8 Instance Segmentation to Active Learning Data Collector.

YOLOv8 Instance Segmentation to CSV Sink

Build a computer vision workflow that connects YOLOv8 Instance Segmentation to CSV Sink.

YOLOv8 Instance Segmentation to Super Annotator

Build a computer vision workflow that connects YOLOv8 Instance Segmentation to Super Annotator.

YOLOv8 Instance Segmentation to Azure Sink

Build a computer vision workflow that connects YOLOv8 Instance Segmentation to Azure Sink.

YOLOv8 Instance Segmentation to Webhook Publish

Build a computer vision workflow that connects YOLOv8 Instance Segmentation to Webhook Publish.

YOLOv8 Instance Segmentation to MQTT Publisher

Build a computer vision workflow that connects YOLOv8 Instance Segmentation to MQTT Publisher.

How to Build a Workflow

Learn how to use a low-code open source platform to simplify building and deploying vision AI applications.
1
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Choose a Block

Choose from 40+ pre-built blocks that let you use custom models, open source models, LLM APIs, pre-built logic, and external applications. Blocks can be models from OpenAI or Meta AI, applications like Google Sheets or Pager Duty, and logic like filtering or cropping.
2
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Connect Blocks

Each block can receive inputs, execute code, and send outputs to the next block in your Workflow. You can use the drag-and-drop UI to configure connections and see the JSON definitions of what’s happening behind the scenes.
3
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Deploy Workflows

You’ll receive an output of the final result from your Workflow and the format you want it delivered in, like JSON. Once your Workflow produces sufficient results, you can use the Workflow as a hosted API endpoint or self-host in your own cloud, on-prem, or at the edge.

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Deploy Workflows at Scale

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Deploy your Workflows directly on fully managed infrastructure through an infinitely-scalable API endpoint for high volume workloads
Run Workflows on-device, internet connection optional, without the headache of environment management, dependencies, and managing CUDA versions.
Isolate dependencies in your software by using the Python SDK or HTTP API to operate and maintain your Workflows separate from other logic within your codebase
Supported devices include ARM CPU, x86 CPU, NVIDIA GPU, and NVIDIA Jetson

Customize Your Pipeline

Connect models from OpenAI or Meta AI, applications like Slack or Pager Duty, and logic like filtering or cropping.
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