Connect YOLOv7 Instance Segmentation with Active Learning Data Collector

Build a multi-stage computer vision pipeline by connecting YOLOv7 Instance Segmentation with Active Learning Data Collector and deploy a production application in minutes.

Deploy this Workflow

16,000+ organizations build with Roboflow

YOLOv7 Instance Segmentation

YOLOv7 Instance Segmentation is a type of Roboflow Instance Segmentation Model.

Use YOLOv7 Instance Segmentation in the Roboflow Instance Segmentation Model Roboflow Workflows block.

Active Learning Data Collector

Collect data and predictions that flow through workflows for use in active learning.

Sample images and model predictions from a workflow and upload them back to a Roboflow project. This block is useful for: 1. Gathering data for use in training a new model, from scratch, or; 2. Gathering data to improve an existing model. This block uses an Active Learning Configuration to determine how to configure active learning. The Configuration specification allows you to determine a sampling strategy, such s random sampling or threshold sampling. To learn more about active learning configurations, refer to the Inference Active Learning Configuration documentation.

Deploy Workflows with a Hosted API or on the Edge

Use workflows with YOLOv7 Instance Segmentation and Active Learning Data Collector in production

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.

Explore Popular Combinations

This is some text inside of a div block.

YOLOv7 Instance Segmentation to Active Learning Data Collector

Build a computer vision workflow that connects YOLOv7 Instance Segmentation to Active Learning Data Collector.

YOLOv5 to Active Learning Data Collector

Build a computer vision workflow that connects YOLOv5 to Active Learning Data Collector.

YOLOv8 to Active Learning Data Collector

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

YOLOv8 Keypoint Detection to Active Learning Data Collector

Build a computer vision workflow that connects YOLOv8 Keypoint Detection to Active Learning Data Collector.

YOLOv8 Instance Segmentation to Active Learning Data Collector

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

YOLO-NAS to Active Learning Data Collector

Build a computer vision workflow that connects YOLO-NAS to Active Learning Data Collector.

How to Build a Workflow

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

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.

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.

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.

Deploy Workflows at Scale

Roboflow powers millions of daily inferences for the world’s largest enterprises on-device and in the cloud

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.

View All Blocks