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🚨 New Release: ultralytics8.2.51
🚨 New Release: ultralytics8.2.51
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🍺Live Space : 
🍺Live Space : 
resource
https://huggingface.co/spaces/prithivMLmods/YOLO-VIDEO
space
prithivMLmods/YOLO-VIDEO
https://huggingface.co/spaces/prithivMLmods/YOLO-VIDEO
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 , Duplicate the Space to avoid queuing issues.
 , Duplicate the Space to avoid queuing issues.
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🍺T4  Colab : 
🍺T4  Colab : 
link
https://colab.research.google.com/drive/1BKgFUfk2Me1cSPFmbtZSVCn_4cYImPO-?au
https://colab.research.google.com/drive/1BKgFUfk2Me1cSPFmbtZSVCn_4cYImPO-?au
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👉🏻For HPC, use A100/T4 under controlled conditions.
👉🏻For HPC, use A100/T4 under controlled conditions.
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👉🏻Speed Estimation, Object Counting, Distance Calculation, Workout Monitoring, Heatmaps,etc.
👉🏻Speed Estimation, Object Counting, Distance Calculation, Workout Monitoring, Heatmaps,etc.
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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.
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.
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🔗 
🔗 
link
https://pypi.org/project/ultralytics/8.2.58/
https://pypi.org/project/ultralytics/8.2.58/
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🚀More Features You can try:
🚀More Features You can try:
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✅ Classes selection support added
✅ Classes selection support added
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✅ Live FPS display in the sidebar 
✅ Live FPS display in the sidebar 
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✅ Webcam and video support added
✅ Webcam and video support added
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✅ Confidence and NMS threshold option to modify.
✅ Confidence and NMS threshold option to modify.
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✅ Segmentation, detection, and pose models support added.
✅ Segmentation, detection, and pose models support added.
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🙀Ultralytics Live inference: 
🙀Ultralytics Live inference: 
link
https://docs.ultralytics.com/guides/streamlit-live-inference/
https://docs.ultralytics.com/guides/streamlit-live-inference/
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```
from ultralytics import solutions
solutions.inference()
### Make sure to run the file using command `streamlit run <file-name.py>`

```
from ultralytics import solutions
solutions.inference()
### Make sure to run the file using command `streamlit run <file-name.py>`
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⚡yolo streamlit-predict
⚡yolo streamlit-predict
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👉🏻Advantages of Live Inference
👉🏻Advantages of Live Inference
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      ☑️ 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.
      ☑️ 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.
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      ☑️Efficient Resource Utilization: YOLOv8 optimized algorithm ensure high-speed processing with minimal computational resources.
      ☑️Efficient Resource Utilization: YOLOv8 optimized algorithm ensure high-speed processing with minimal computational resources.
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🙀Ultralytics feature Models: 
🙀Ultralytics feature Models: 
link
https://docs.ultralytics.com/models/
https://docs.ultralytics.com/models/
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, Ultralytics new Solutions: 
, Ultralytics new Solutions: 
link
https://docs.ultralytics.com/solutions/
https://docs.ultralytics.com/solutions/
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👉🏻Official Documentation:
👉🏻Official Documentation:
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    Ultralytics YOLOv8 Documentation: Refer to the official YOLOv8 documentation for comprehensive guides and insights on various computer vision tasks and projects. 🔗 
    Ultralytics YOLOv8 Documentation: Refer to the official YOLOv8 documentation for comprehensive guides and insights on various computer vision tasks and projects. 🔗 
link
https://docs.ultralytics.com/
https://docs.ultralytics.com/
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🚨 New Release: ultralytics8.2.51
🍺Live Space : https://huggingface.co/spaces/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/ 

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