Forget Coding; start Vibing! Tell AI what you want, and watch it build your dream website while you enjoy a cup of coffee.

Date: Thursday, April 17th at 9 PM IST

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🚦 Traffic Lights Detection using Ultralytics YOLO11! 🧠🤖

Ultralytics YOLOv11 can be used for real-time detection of 🚫 red, ⚠️ yellow, and ✅ green traffic lights — boosting road safety, traffic management, and autonomous navigation 🛣️🚗

🌆 Unlock new possibilities in:
🌐 Smart city planning 🏙️
🚦 Adaptive traffic control
🔍 Computer vision-powered transportation systems

🚀 Get started now ➡️ https://ow.ly/XQyG50VgcR3

📡 By: https://t.iss.one/DataScienceN

Don't forget to attend this session!

🔥 SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation, has been accepted at hashtag#CVPR2025! 🎉

make #SegmentAnything wiser by enabling it to understand text prompts—all with just 4.9M additional trainable parameters.

🚀💡 What makes SAMWISE special?
🔹 Textual & Temporal Adapter for #SAM2 – We introduce a novel adapter that enables early fusion of text and visual features, allowing SAM2 to understand textual queries while modeling temporal evolution across frames.
🔹 Tracking Bias Correction – SAM2 tends to keep tracking an object even when a better match for the text query appears. Our learnable correction mechanism dynamically adjusts its focus, ensuring it tracks the most relevant object at every moment.

✨ State-of-the-art performance across multiple benchmarks:

✅ New SOTA on Referring Video Object Segmentation (RVOS)
✅ New SOTA on image-level Referring Segmentation (RIS)✅ Runs online
✅ Requires no fine-tuning of SAM2 weights
🚀 SAMWISE is the first text-driven segmentation approach built on SAM2 that achieves SOTA while staying lightweight and online.
🏠 Project page: https://lnkd.in/dtBHBVbG
💻 Code and models: https://lnkd.in/d-fadFGd
🔗 Paper: arxiv.org/abs/2411.17646

📡 By: https://t.iss.one/DataScienceN

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Follow me on linkedin (important for you)

https://www.linkedin.com/in/hussein-sheikho-4a8187246

𝑯𝒐𝒎𝒐𝒈𝒓𝒂𝒑𝒉𝒚 𝒂𝒏𝒅 𝑲𝒆𝒚𝒑𝒐𝒊𝒏𝒕 𝒇𝒐𝒓 𝑭𝒐𝒐𝒕𝒃𝒂𝒍𝒍 𝑨𝒏𝒂𝒍𝒚𝒕𝒊𝒄𝒔 ⚽️📐

🚀 Highlighting the latest strides in football field analysis using computer vision, this post shares a single frame from our video that demonstrates how homography and keypoint detection combine to produce precise minimap overlays. 🧠🎯

🧩 At the heart of this project lies the refinement of field keypoint extraction. Our experiments show a clear link between both the number and accuracy of detected keypoints and the overall quality of the minimap. 🗺️
📊 Enhanced keypoint precision leads to a more reliable homography transformation, resulting in a richer, more accurate tactical view. ⚙️⚡

🏆 For this work, we leveraged the championship-winning keypoint detection model from the SoccerNet Calibration Challenge:

📈 Implementing and evaluating this state‑of‑the‑art solution has deepened our appreciation for keypoint‑driven approaches in sports analytics. 📹📌

🔗 https://lnkd.in/em94QDFE

📡 By: https://t.iss.one/DataScienceN


#ObjectDetection hashtag#DeepLearning hashtag#Detectron2 hashtag#ComputerVision hashtag#AI
hashtag#Football hashtag#SportsTech hashtag#MachineLearning hashtag#ComputerVision hashtag#AIinSports
hashtag#FutureOfFootball hashtag#SportsAnalytics
hashtag#TechInnovation hashtag#SportsAI hashtag#AIinFootball hashtag#AI hashtag#AIandSports hashtag#AIandSports
hashtag#FootballAnalytics hashtag#python hashtag#ai hashtag#yolo hashtag

📡 By: https://t.iss.one/DataScienceN

📡 By: https://t.iss.one/DataScienceN

🎯 Trackers Library is Officially Released! 🚀

If you're working in computer vision and object tracking, this one's for you!

💡 Trackers is a powerful open-source library with support for a wide range of detection models and tracking algorithms:

✅ Plug-and-play compatibility with detection models from:
Roboflow Inference, Hugging Face Transformers, Ultralytics, MMDetection, and more!

✅ Tracking algorithms supported:
SORT, DeepSORT, and advanced trackers like StrongSORT, BoT‑SORT, ByteTrack, OC‑SORT – with even more coming soon!

🧩 Released under the permissive Apache 2.0 license – free for everyone to use and contribute.

👏 Huge thanks to Piotr Skalski for co-developing this library, and to Raif Olson and Onuralp SEZER for their outstanding contributions!

📌 Links:
🔗 GitHub
🔗 Docs


📚 Quick-start notebooks for SORT and DeepSORT are linked 👇🏻
https://www.linkedin.com/posts/skalskip92_trackers-library-is-out-plugandplay-activity-7321128111503253504-3U6-?utm_source=share&utm_medium=member_desktop&rcm=ACoAAEXwhVcBcv2n3wq8JzEai3TfWmKLRLTefYo


#ComputerVision #ObjectTracking #OpenSource #DeepLearning #AI


📡 By: https://t.iss.one/DataScienceN