Yolo World is a zero shot object detection model with its YoloV8 backbone to extract image features along with a shared vocabulary embeddings prompted by the user. This avoids the need to manually annotate images unlike traditional Yolo models.So when a user prompts with the desired class it's converted to vocab embeds,the box head shared with text contrastive head helps to find the object embeddings fusing text and image features Earlier Vocab embed models are transformer based backbone requiring heavy compute and slow wherein Yolo backbone models are known for lighweight and fast inference. For more on this checkout: docs.ultralytics.com/models/yolo-world/
Can anyone please how to save the model after training on custom dataset, so that I don't have to train again and again for inference in different type of videos
Thank you
Thank you
you make very cool videos!
Thank you so much!
Hi sir, where can I find the YOLO NAS colab notebook to work on
Hi, you can find the notebook here: github.com/spmallick/learnopencv/tree/master/YOLO-NAS_Introduction
Hi Sir, Can you please make a video on YOLO world model? How it is different from other YOLO model with Use case for yoloworld model.
Yolo World is a zero shot object detection model with its YoloV8 backbone to extract image features along with a shared vocabulary embeddings prompted by the user.
This avoids the need to manually annotate images unlike traditional Yolo models.So when a user prompts with the desired class it's converted to vocab embeds,the box head shared with text contrastive head helps to find the object embeddings fusing text and image features
Earlier Vocab embed models are transformer based backbone requiring heavy compute and slow wherein Yolo backbone models are known for lighweight and fast inference.
For more on this checkout:
docs.ultralytics.com/models/yolo-world/
Thank you so much
Can anyone please how to save the model after training on custom dataset, so that I don't have to train again and again for inference in different type of videos
All the model checkpoints are saved in their respective "experiment-name" directories.
awesome
Thank you!
but how is a v5 model better than v7 ??
YOLOv5 and YOLOv7 have different authors and developers.
@@LearnOpenCV I thought v7 is also from ultralytics…
Check this repo for more info: github.com/WongKinYiu/yolov7