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)

#YoloV8 #AI #EranFeitTutorial

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

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**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

#Ultralytics #SegmentAnything #AI

One click, infinite masks! 🖱️

Learn how to use SAM (ViT-H) and OpenCV to generate segmentation masks from a single point.

Medium: https://medium.com/image-segmentation-tutorials/one-click-segment-anything-in-python-sam-vit-h-bf6cf9160b61

Code: https://eranfeit.net/one-click-segment-anything-in-python-sam-vit-h/

#AI #Python #CV

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

From zero to masks with Segment Anything: generate, annotate, sort by size, and inspect predictions in a clean Python pipeline using OpenCV + Supervision.
Read: https://eranfeit.net/segment-anything-tutorial-fast-auto-masks-in-python/

Watch: https://youtu.be/vmDs2d0CTFk?si=nvS4eJv5YfXbV5K7

For anyone practicing photo segmentation with Detectron2, this shows an end-to-end custom dataset workflow using Mask R-CNN.
From COCO annotations to training and testing on fresh photos.
Code: https://eranfeit.net/detectron2-custom-dataset-training-made-easy/

Video: https://youtu.be/JbEy4Eefy0Y

Panoptic Segmentation with Detectron2: beginner-friendly walkthrough of how panoptic combines instance and semantic segmentation for full pixel-level scene understanding using Detectron2’s COCO panoptic model in Python.

Tutorial + code:
https://eranfeit.net/detectron2-panoptic-segmentation-made-easy-for-beginners/

Hands-on instance segmentation with Detectron2 🧠
This tutorial covers running Mask R-CNN inference with a pretrained COCO model, visualizing instance masks, and saving results—all in a clear, beginner-friendly workflow.

Guide 👉 [https://eranfeit.net/make-instance-segmentation-easy-with-detectron2/](https://eranfeit.net/make-instance-segmentation-easy-with-detectron2/)

#ComputerVision #Detectron2 #Python #AI