Ultralytics

Ultralytics

Software Development

Los Angeles, CA 51,209 followers

Simpler. Smarter. Further.

About us

Ultralytics is on a mission to empower people and companies to unleash the positive potential of AI. We make model development accessible, efficient to train, and easy to deploy. It’s been a remarkable journey, but we’re just getting started. Bring your models to life with our vision AI tools: 🔘 Ultralytics HUB - Create and train sophisticated models in seconds with no code for web and mobile 🔘 Ultralytics YOLO - Explore our state-of-the-art AI architecture to train and deploy your highly accurate AI models like a pro

Website
http://ultralytics.com
Industry
Software Development
Company size
11-50 employees
Headquarters
Los Angeles, CA
Type
Privately Held
Specialties
AI, Deep Learning, Data Science, YOLOv5, YOLOv8, Artificial Intelligence, Machine Learning, ML, YOLO, and SaaS

Locations

Employees at Ultralytics

Updates

  • View organization page for Ultralytics, graphic

    51,209 followers

    Detect your signatures using Ultralytics YOLOv8 🚀 With YOLOv8, you can effortlessly detect and locate signatures in images and videos. This technology boosts security, simplifies document verification, and supports automated processes across different industries. It also helps in fraud detection, data integrity, and ensures compliance with ease. 😍 As Jordan Belfort said, "Your signature is your identity; it represents you in a unique way." ⭐ Learn more ➡️ https://ow.ly/k33o50RAK7S #computervision #yolov9 #signatures #ai

  • Ultralytics reposted this

    View profile for Muhammad Rizwan Munawar, graphic

    Computer Vision Engineer @Ultralytics | Solving Real-World Challenges🔎| Python | Published Research | Open Source Contributor | GitHub 🌟 | Daily Computer Vision LinkedIn Content 🚀 | Technical Writer VisionAI @Medium📝

    Object tracking comparison Ultralytics 💙 🚀 BotSort vs ByteTrack 😎 💠 Botsort assigns the track IDs to the object early, but it sometimes misses the tracking in a few frames for a specific object. On the other side, Bytetrack tries to assign IDs after more calculations over several frames, but then the tracking ID is much more stable over frames. 💠 Due to the immediate assigning of tracking ID in botsort, sometimes it considers a 2-3 frames detection as part of the track and assigns them tracking ID which can cause issues because later objects do not exist in coming frames. Bytetrack on the other side does not consider that object as a track. 🔥Bytetrack is slow as compared to Botsort in processing, which means low FPS, but better accuracy :) 🔥 😍 My favorite is bytetrack, looking forward to hearing your thoughts 👇 Learn more ➡ https://lnkd.in/g8S53amT

  • View organization page for Ultralytics, graphic

    51,209 followers

    From Farm to Table: How AI Drives Innovation in Agriculture. 🍓 Discover how AI is helping in every step of the lifecycle of fruits, from planting and harvesting to processing and retail. Learn how AI is enhancing efficiency, sustainability, and quality in agriculture in Abirami Vina's new blog! Read more ➡️ https://ow.ly/ZwLX50SzpMv #AI #Agriculture

    From Farm to Table: How AI Drives Innovation in Agriculture by Abirami Vina

    From Farm to Table: How AI Drives Innovation in Agriculture by Abirami Vina

    ultralytics.com

  • View organization page for Ultralytics, graphic

    51,209 followers

    How is AI transforming the tourism industry? 🌍✈️ From personalized travel recommendations and virtual assistants to smart booking systems and augmented reality tours, AI is changing modern travel. Discover the benefits, challenges, and future potential of AI in enhancing convenience, efficiency, and personalization for travelers and businesses alike. Learn more ➡️ https://ow.ly/qpcn50SyFEL #AI #Tourism

    The Impact of AI on the Tourism Industry by Mostafa Ibrahim

    The Impact of AI on the Tourism Industry by Mostafa Ibrahim

    ultralytics.com

  • Ultralytics reposted this

    View profile for Muhammad Rizwan Munawar, graphic

    Computer Vision Engineer @Ultralytics | Solving Real-World Challenges🔎| Python | Published Research | Open Source Contributor | GitHub 🌟 | Daily Computer Vision LinkedIn Content 🚀 | Technical Writer VisionAI @Medium📝

    Interesting results, Car parts segmentation Ultralytics 💙🚀 🔗 Code: https://lnkd.in/dZVhSye4 Segmenting AUDI AG car body parts aids in damage analysis, which is crucial for various automotive industry tasks. By fine-tuning the model on a car parts segmentation dataset for 50 epochs using Ultralytics YOLOv8, I achieved impressive results. Advantages: ✅ Enhanced damage analysis for better repair assessments ✅ Streamlined processes for automotive industry tasks ✅ Accurate identification and segmentation of car components 🔥 With more data, you can even get better results 🔥

  • View organization page for Ultralytics, graphic

    51,209 followers

    New tutorial | CIFAR-10 image classification with Ultralytics! 😍 In this video, we will dive into the widely-used CIFAR-10 dataset, learn about its key features, how to use it for image classification, and see examples of training and prediction results using Google Colab. What's covered: ✅ CIFAR-10 image classification using Google Colab ✅ Training results and validation metrics ✅ Prediction on the test set and output understanding Watch now ➡️ https://lnkd.in/dMmesNqE

  • View organization page for Ultralytics, graphic

    51,209 followers

    Harnessing AI to combat deforestation! 🌳 Check out our latest blog as we explore how AI can be used in forest conservation. Innovative solutions such as real-time deforestation monitoring, satellite and drone imagery analysis, object and smoke detection are changing the way we fight deforestation. Discover the change AI brings to this field and its potential for protecting our planet. Learn more ➡️ https://ow.ly/7KxT50SxLeG #AI #ForestConservation #Sustainability

    Harnessing AI to Combat Deforestation by Mostafa Ibrahim

    Harnessing AI to Combat Deforestation by Mostafa Ibrahim

    ultralytics.com

  • View organization page for Ultralytics, graphic

    51,209 followers

    We’re celebrating 50k followers on LinkedIn with an Ultralytics giveaway! 🎁 Thank you to our amazing open-source community for helping us reach this incredible milestone on LinkedIn! To show our appreciation, we're announcing a giveaway, with a special contribution from our friends at Seeed Studio! What’s up for grabs? ✅ $500 worth of Ultralytics HUB credits ✅ reComputer J1010 -Edge AI Device with Jetson Nano module ✅ 1-hour free consulting session with Glenn Jocher, author of Ultralytics YOLOv5 and YOLOv8! To win: 1. Follow Ultralytics on LinkedIn, Twitter and YouTube 2. Like and share this post on your LinkedIn feed, tagging Ultralytics and Seeed Studio 3. Comment below with what you like most about Ultralytics! 🗓 The giveaway ends on July 29th and the winner will be announced on August 1st. Good luck, everyone, and thank you for your continued support! 🚀 #Ultralytics #Giveaway

  • View organization page for Ultralytics, graphic

    51,209 followers

    Distance calculation using Ultralytics YOLOv8! 🚀 YOLOv8 provides precise distance calculation from the camera to vehicles, delivering real-time analytics and enhancing various applications. You can use this technology for improved spatial awareness and operational efficiency in transportation and logistics. Key Benefits: ✅ Enhance vehicle safety and collision avoidance ✅ Improve traffic management and flow ✅ Optimize parking and fleet management Learn more ➡️ https://ow.ly/9UUu50SnQLZ #ComputerVision #DistanceCalculation #YOLOv8 #VehicleSafety #AI

  • View organization page for Ultralytics, graphic

    51,209 followers

    Speed estimation using Ultralytics YOLOv8 💙

    View profile for Muhammad Rizwan Munawar, graphic

    Computer Vision Engineer @Ultralytics | Solving Real-World Challenges🔎| Python | Published Research | Open Source Contributor | GitHub 🌟 | Daily Computer Vision LinkedIn Content 🚀 | Technical Writer VisionAI @Medium📝

    Speed estimation + image masking Ultralytics 💙🔥🔥 🔗 Code: https://lnkd.in/d9bZ9ZWn ❤️ Speed estimation with computer vision is possible, but exact calculations require a depth channel typically available in 3D camera visuals. This factor significantly impacts vehicle speed measurement. 💡 I've shared a 2D image speed estimation, which may not be accurate for every vehicle but provides a general estimate. The main concern is that it's highly dependent on GPU speed, making precise vehicle speed determination challenging overall. 🔥 I do have a plan for speed estimation using 3D data in the future, where the 3d data will be used for effective speed estimation 😍

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