Master Computer Vision with **Detectron2**! 🚀
This tutorial simplifies Meta AI's modular framework, showing you how to build a Faster R-CNN pipeline for high-accuracy object detection.
📖 Medium: [https://medium.com/object-detection-tutorials/easy-detectron2-object-detection-tutorial-for-beginners-a7271485a54b]()
💻 Code: [https://eranfeit.net/easy-detectron2-object-detection-tutorial-for-beginners/]()
No GPU? No problem! 💻
Run real-time object detection directly on your CPU using SSD MobileNet v3 & OpenCV.
📺 Video: [https://youtu.be/e-tfaEK9sFs](https://youtu.be/e-tfaEK9sFs)
📖 Guide: [https://eranfeit.net/ssd-mobilenet-v3-object-detection-explained-for-beginners/](https://eranfeit.net/ssd-mobilenet-v3-object-detection-explained-for-beginners/)
---
This [Build an Object Detector using SSD MobileNet v3](https://www.youtube.com/watch?v=e-tfaEK9sFs) video walks you through the complete Python code implementation for high-speed detection on edge hardware.
Scaling your AI projects? Efficient data annotation is key. 🔑
Use the YOLOv8-seg architecture to automate high-quality mask creation and transform video frames into labeled datasets with minimal manual effort.
Full tutorial: [https://eranfeit.net/boost-your-dataset-with-yolov8-auto-label-segmentation/](https://eranfeit.net/boost-your-dataset-with-yolov8-auto-label-segmentation/)
Read on Medium: [https://bit.ly/42L7mR2](https://www.google.com/search?q=https://bit.ly/42L7mR2)
\#ImageSegmentation \#YoloV8 \#AI
This guide implements YOLOv8 for dog segmentation, utilizing pre-trained models to balance inference speed with high-precision boundaries in video.
Source & Code: https://eranfeit.net/fast-yolov8-dog-segmentation-tutorial-for-video-images/
Unlock professional football analytics with YOLOv8 Multi-Class Segmentation! ⚽️
Ditch overlapping boxes for pixel-level masks. Learn to fine-tune yolov8l-seg.pt for precise player & ball tracking.
Guide: [https://eranfeit.net/yolov8-segmentation-tutorial-for-multi-class-football/](https://eranfeit.net/yolov8-segmentation-tutorial-for-multi-class-football/)
Video: [https://youtu.be/iXaq4OXNwSs](https://youtu.be/iXaq4OXNwSs)
Want to use AI for good? 🌊
Check out this YOLOv8 Segmentation tutorial for real-world flood detection. Eran Feit breaks it all down:
💻 **Code**: [https://eranfeit.net/yolov8-segmentation-tutorial-for-real-flood-detection/](https://eranfeit.net/yolov8-segmentation-tutorial-for-real-flood-detection/)
📺 **Video**: [https://youtu.be/diZj_nPVLkE](https://youtu.be/diZj_nPVLkE)
#YoloV8 #ImageSegmentation #FloodDetection #AI
---
**Would you like me to generate a shorter version specifically for a LinkedIn "hook" or a different social platform?**
For anyone studying Quick Yolov5 segmentation tutorial in minutes: this guide focuses on implementing the yolov5x-seg model for instance segmentation. It details environment isolation and using dedicated scripts for pixel-level mask generation. #YoloV5
Blog: [https://eranfeit.net/quick-yolov5-segmentation-tutorial-in-minutes/](https://eranfeit.net/quick-yolov5-segmentation-tutorial-in-minutes/)
Video: [https://youtu.be/z3zPKpqw050?si=28h5BhkgfYpkfR_N](https://youtu.be/z3zPKpqw050?si=28h5BhkgfYpkfR_N)
Would you like a version that specifically mentions the Python and CUDA versions used in the environment setup?
Build custom segmentation models with YOLOv8 and SAM! 🚀
Full guide: https://eranfeit.net/segment-anything-tutorial-generate-yolov8-masks-fast/
Watch: https://youtu.be/8cir9HkenEY
One click, infinite masks! 🖱️
Learn how to use SAM (ViT-H) and OpenCV to generate segmentation masks from a single point.
Code: https://eranfeit.net/one-click-segment-anything-in-python-sam-vit-h/
Gemini said
Master SAM for custom datasets! 🚀 Segment objects with zero training or manual labels. Full workflow here:
🔗 https://eranfeit.net/segment-anything-python-no-training-image-masks/
🎥 https://youtu.be/8ZkKg9imOH8
