Roboflow Changelog: September 2022

Each month, we share a recap of product and company updates; if you missed the last edition of the Roboflow Changelog, you can find it here.

Roboflow Organize and Annotate

• Semantic Segmentation Labeling

• Assign: Find Similar Images to Assign, Find Similar Images from Generated Images

• Dataset Search: Filter Images by Class, Filter/Search for Null Images

• Smart Polygon annotations

• Added an Overlap Slider to Label Assist

Roboflow Train and Deploy

• Instance Segmentation added to the Python Package | Inference Documentation
• Launch: Test Computer Vision Models Locally

Roboflow Universe

• Updated the Roboflow Universe Hero Image

• Universe Search Filtering and Styling Updates

New Tutorials

• Georeferencing detections from models deployed to drones
• How to Train YOLOv5 Instance Segmentation

Projects from New Employees

• How I use Computer Vision and Twilio to Guarantee Availability at Busy Public Tennis Courts

Other

• Released the Roboflow Command Line Interface

• Ultralytics YOLO Vision: What Training 10,000 Vision Models Tells Us about Getting to Production with Joseph Nelson | Using CV to Improve Accessibility through Automated Sign Language Captioning with Mohamed Traore | A CV Approach to Quantifying Plastic in the Ocean with Jay Lowe | Bridging AI From Digital to Physical: Real-World AI, Right at the Edge with Elaine Wu
• Object Detection Using YOLOv5 Tutorial - Data Moves Me
• Improvements to dataset upload speed
• Added Improvements to the Product Onboarding Flow
• Updated the in-app Roboflow Tutorial

• Celebrated 1 year anniversaries for 1 team member
• Welcomed 1 new employee (Machine Learning Field Engineer)
• Roboflow Product Team Onsite in Pittsburgh, PA
• Team meetups in San Francisco, CA, and Des Moines, IA

• Conducted UXR sessions
• 23 new discussions on the Roboflow Forum
• 10k+ new Universe projects
• 11 new blog posts
• 3 new YouTube videos

User Research Publications and Projects

• Train Activity Recognition Models Using Spectrograms and Computer Vision, Particle Identification System in Cloud Chamber Using YoloV5, Enhanced pothole detection system using YOLOX algorithm, People Detection in an Elevator Car Using Computer Vision, Automated Crack Severity Level Detection and Classification for Surface, How to train custom object detection model using TensorFlow Object Detection API — Part 2, YOLOv5 Wildfire Smoke Detection with Roboflow and Weights & Biases, ROBOFLOW DETECTRON2 İLE GÖRÜNTÜ İŞLEME, Real-Time Detection of Objects on Roads for Autonomous Vehicles Using Deep Learning, Heavy RF usage for rice leaf disease classification with YOLOv5, AN INTELLIGENT FOOD INVENTORY MONITORING SYSTEM USING MACHINE LEARNING AND COMPUTER VISION, 我的NVIDIA开发者之旅—使用NVIDIA TAO和NEMO开发AI应用的埋坑经验-CSDN社区, YOLOv7- Real-time Object Detection at its Best - Analytics Vidhya, How to retrain YOLOv7 model with your own dataset?, Car Detection and Features Identification Based on YOLOV5, Method description for the lymphocytes and plasma cells detection task, Aquarium Fish Classification with Roboflow, Intelligent Food Inventory Monitoring System using Machine Learning and Computer Vision, Train YOLOv7 Segmentation on Custom Data, Object Detection with TensorFlow 2 Object Detection API, A YOLO-Deep Learning Algorithm for Improved Detection of Cell Phone Usage in Restricted Places, USE OF MULTIPLE LOW COST AUTONOMOUS DRONES FOR HIGH VOLTAGE LINE INSPECTION, Object Detection service with YOLO and FastAPI, Thai Recipe Retrieval Application Using Convolutional Neural Network, Cycle Route Signs Detection Using Deep Learning, Plastic Bottle Detector For Lake, DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection, Snow particle analyzer for simultaneous measurements of snow density and morphology, Single Stage Facial Recognition based on YOLOv5, Computational Collective Intelligence, Early flash flood warn system, BeeO Terminal, The compliance of head-mounted industrial PPE by using deep learning object detectors, Machine Learning Techniques to Detect Objects with a Meraki MV Camera, CartoDx: Mapping Vector-Borne Disease Vulnerabilities in Urban Environments – IAAC Blog, An Upgraded-YOLO with Object Augmentation: Mini-UAV Detection Under Low-Visibility Conditions by Improving Deep Neural Networks, KeesTalksTech (Twitter thread) / (part 2) / and (part 3)

Cite this Post

Use the following entry to cite this post in your research:

Mohamed Traore. (Oct 1, 2022). Roboflow Changelog: September 2022. Roboflow Blog: https://blog.roboflow.com/changelog-september-2022/

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