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🚨 New Release: ultralytics8.2.51
🍺Live Space : prithivMLmods/YOLO-VIDEO , Duplicate the Space to avoid queuing issues.
🍺T4 Colab : https://colab.research.google.com/drive/1BKgFUfk2Me1cSPFmbtZSVCn_4cYImPO-?au
👉🏻For HPC, use A100/T4 under controlled conditions.
👉🏻Speed Estimation, Object Counting, Distance Calculation, Workout Monitoring, Heatmaps,etc.
Ultralytics dropped the YOLOv8 - #Ultralytics 8.2.51 🔥, YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
🔗 https://pypi.org/project/ultralytics/8.2.58/
🚀More Features You can try:
✅ Classes selection support added
✅ Live FPS display in the sidebar
✅ Webcam and video support added
✅ Confidence and NMS threshold option to modify.
✅ Segmentation, detection, and pose models support added.
🙀Ultralytics Live inference: https://docs.ultralytics.com/guides/streamlit-live-inference/
⚡yolo streamlit-predict
👉🏻Advantages of Live Inference
☑️ Seamless Real-Time Object Detection: Streamlit combined with YOLOv8 enables real-time object detection directly from your webcam feed. This allows for immediate analysis and insights, making it ideal for applications requiring instant feedback.
☑️Efficient Resource Utilization: YOLOv8 optimized algorithm ensure high-speed processing with minimal computational resources.
🙀Ultralytics feature Models: https://docs.ultralytics.com/models/, Ultralytics new Solutions: https://docs.ultralytics.com/solutions/
👉🏻Official Documentation:
Ultralytics YOLOv8 Documentation: Refer to the official YOLOv8 documentation for comprehensive guides and insights on various computer vision tasks and projects. 🔗 https://docs.ultralytics.com/
🍺Live Space : prithivMLmods/YOLO-VIDEO , Duplicate the Space to avoid queuing issues.
🍺T4 Colab : https://colab.research.google.com/drive/1BKgFUfk2Me1cSPFmbtZSVCn_4cYImPO-?au
👉🏻For HPC, use A100/T4 under controlled conditions.
👉🏻Speed Estimation, Object Counting, Distance Calculation, Workout Monitoring, Heatmaps,etc.
Ultralytics dropped the YOLOv8 - #Ultralytics 8.2.51 🔥, YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
🔗 https://pypi.org/project/ultralytics/8.2.58/
🚀More Features You can try:
✅ Classes selection support added
✅ Live FPS display in the sidebar
✅ Webcam and video support added
✅ Confidence and NMS threshold option to modify.
✅ Segmentation, detection, and pose models support added.
🙀Ultralytics Live inference: https://docs.ultralytics.com/guides/streamlit-live-inference/
from ultralytics import solutions
solutions.inference()
### Make sure to run the file using command `streamlit run <file-name.py>`⚡yolo streamlit-predict
👉🏻Advantages of Live Inference
☑️ Seamless Real-Time Object Detection: Streamlit combined with YOLOv8 enables real-time object detection directly from your webcam feed. This allows for immediate analysis and insights, making it ideal for applications requiring instant feedback.
☑️Efficient Resource Utilization: YOLOv8 optimized algorithm ensure high-speed processing with minimal computational resources.
🙀Ultralytics feature Models: https://docs.ultralytics.com/models/, Ultralytics new Solutions: https://docs.ultralytics.com/solutions/
👉🏻Official Documentation:
Ultralytics YOLOv8 Documentation: Refer to the official YOLOv8 documentation for comprehensive guides and insights on various computer vision tasks and projects. 🔗 https://docs.ultralytics.com/