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YOLOE: Real-Time Zero-Shot Object Detection and Segmentation Explained | Visual Prompting
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YOLOE released by researchers at Tsinghua University: Real-time seeing anything with zero-shot performance.
YOLOE can do both object detection and image segmentation and supports different prompt types, including text prompts, visual inputs, or even no prompt at all.
💡YOLOE results have been compared with YOLO-Worldv2, which supports arbitrary text prompts too.
Key highlights:
✅ Zero-shot performance: It can find and recognize new objects, even if it hasn’t seen them before.
✅ Training time: Based on a research paper, It reaches the same accuracy as YOLO-Worldv2 but in one-third of the time on the LVIS dataset.
✅ Inference time: Its prediction speed is slightly better in comparison to YOLO-Worldv2.
✅ Pretrained embeddings: It uses a stored Apple MobileCLIP text encoder to keep training fast.
*Github Repo:*
*🧑🏻💻 My AI and Computer Vision Courses⭐*
*📘 YOLOv12: Custom Object Detection, Tracking & WebApps (13$)*
*📙 Modern Computer Vision with OpenCV 2025 (13$)*
*📚 YOLO11 & YOLOv12: Object Detection & Web Apps in Python 2025 (13$)*
*📘 AI 4 Everyone: Build Generative AI & Computer Vision Apps (13$)*
*📙 YOLOv9, YOLOv10 & YOLO11: Learn Object Detection & Web Apps (13$)*
*📕 Learn LangChain: Build #22 LLM Apps using OpenAI & Llama 2 (14$)*
*📕 Learn OpenCV: Build # 30 Apps with OpenCV, YOLOv8 & YOLO-NAS (13$)*
_______________________________________________________________
*Support Us on Patreon*
_______________________________________________________________
*Don't forget to connect with me*
_______________________________________________________________
*⚒️Freelance Work*
_______________________________________________________________
*For Consultation Call 📞*
Happy Coding!
Tags:
#yoloe #yolo #objectdetection #yoloworld
YOLOE can do both object detection and image segmentation and supports different prompt types, including text prompts, visual inputs, or even no prompt at all.
💡YOLOE results have been compared with YOLO-Worldv2, which supports arbitrary text prompts too.
Key highlights:
✅ Zero-shot performance: It can find and recognize new objects, even if it hasn’t seen them before.
✅ Training time: Based on a research paper, It reaches the same accuracy as YOLO-Worldv2 but in one-third of the time on the LVIS dataset.
✅ Inference time: Its prediction speed is slightly better in comparison to YOLO-Worldv2.
✅ Pretrained embeddings: It uses a stored Apple MobileCLIP text encoder to keep training fast.
*Github Repo:*
*🧑🏻💻 My AI and Computer Vision Courses⭐*
*📘 YOLOv12: Custom Object Detection, Tracking & WebApps (13$)*
*📙 Modern Computer Vision with OpenCV 2025 (13$)*
*📚 YOLO11 & YOLOv12: Object Detection & Web Apps in Python 2025 (13$)*
*📘 AI 4 Everyone: Build Generative AI & Computer Vision Apps (13$)*
*📙 YOLOv9, YOLOv10 & YOLO11: Learn Object Detection & Web Apps (13$)*
*📕 Learn LangChain: Build #22 LLM Apps using OpenAI & Llama 2 (14$)*
*📕 Learn OpenCV: Build # 30 Apps with OpenCV, YOLOv8 & YOLO-NAS (13$)*
_______________________________________________________________
*Support Us on Patreon*
_______________________________________________________________
*Don't forget to connect with me*
_______________________________________________________________
*⚒️Freelance Work*
_______________________________________________________________
*For Consultation Call 📞*
Happy Coding!
Tags:
#yoloe #yolo #objectdetection #yoloworld
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