YOLOv8 Comparison with Latest YOLO models
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- เผยแพร่เมื่อ 9 ม.ค. 2023
- Introducing YOLOv8, the latest addition to the object detection family!
See how YOLO models perform in diverse scenarios, including daylight, low light, blurry and with fast-moving objects.
#yolo #yolov5 #yolov6 #yolov7 #yolov8 #objectdetection
#deeplearning #ai - วิทยาศาสตร์และเทคโนโลยี
The aeroplane in the middle of the street though
Hahahahahha
wish the confidence text was readable for v7
In fact, it would be better if the results were shared graphically. Visually, yolov7 seems to be better than the others.
Better doesn't mean good latency, every new model is better, faster and energy efficient from the previous one.
Depends on the model you trained as well. If you train a more narrow model, you tend to get better results overall.
Hi! Very nice work! Congrats!
thanks
The bridge is an airplane with 61% confidence 😂
So weird that it seems yolov7 is the best choice.
I think if you can put up a detection fps then it will be better to point out the advantage of yolov8
@@andrespereira4852 YoloV8 is a huge leap. From a developer's standpoint it's significantly easier to train and deploy... well, besides some of the deployment/export functionality to other frameworks is still in the works. But having a CLI to interact with YOLO is sublime. It's the first one to have it.
@@ForTheOmnissiah i don't know, but as a beginner to object detection things, it feel weird to interact with CLI
Not really. The architectures are different. Yolov7 was built by the original devs (AlexeyAB and WongKinYiu) that did v4 and its derivatives. pjreddie (who originally developed the darknet framework) publicly said that Yolov4 is the defacto successor.
Ultralytics (yolov5 & yolov8) uses a different framework written in Python. Darknet is written in C++.
Yolov8 is much faster than v7 in the last shot of the moving cars. v7 completely fails that task.
Doing a same research for blind spot detection for vehicle using yolo
huggingface.co/spaces/Pamudu/YOLO-Battlefield
Try this on huggingface spaces.
You can compare your desired YOLO model with other YOLO models to get an idea about real-time performance and detection accuracy.
hi
i am doing pothole detection porject what might be better to use yolo v5 or v7
Why are the boxes around the objects detected with the YOLOv7 model of a different format than other models? Or is it a display that is not difficult to change?
Its an option, you can define the thickness of whatever model
could you please share your code?
am i wrong, or v5 is detecting more objects than v8?
Was wondering the same thing
It seems that YOLOv5 detects more objects with greater accuracy than YOLOv8.
However, YOLOv8 runs faster than YOLOv5. I will do a complete analysis of this.
@@pamudu123ranasinghe7 thanks!
@@pamudu123ranasinghe7 after the your analysis please share your opinion, I will have been waiting for that :)
It seems that YOLOv7 is better than those two. Just look how steady and accurate are its bounding boxes from 0:25 to the end of the video. And why are its boxes painted with so tiny borders?🤨 It looks like Ultralytics is like the old chinese version of products, "look, look, is better and fast, dont worry about if it doesn't have a paper, just buy it, please, take it"
Yolo v8 can be used for classification tasks?
Yes you can use YOLOv8 for classification. Refer this: roboflow.com/model/yolov8-classification
you should tell what size model you used
YOLO medium models of each version is used for comparison
Is it possible to integrate it in flutter app?
Try "Ultralytics HUB" app at appstore.They run YOLO models real time on phone.
I am not sure yolo models can run locally on the phone. But you can host your model on a cloud platform and call it in through your flutter application.
Can u tell me whose model is best choice for CPU?
Out of these models, YOLOv8 performs better on a CPU.
It has a higher FPS rate, high detection accuracy and easy to use.
However, there is a new addition to the family called YOLO-NAS performs even better.
It has a much higher FPS rate and maintains good accuracy.
I have added a comparison video on YOLOv8 and Yolo-Nas.Check it aslo
th-cam.com/video/91p2SkSuZkc/w-d-xo.html&ab_channel=Pamudu123Ranasinghe
@@pamudu123ranasinghe7 thanks bro
huggingface.co/spaces/Pamudu/YOLO-Battlefield
Try this on huggingface spaces.
You can compare your desired YOLO model with other YOLO models to get an idea about real-time performance and detection accuracy.
Can you share the video clips?
drive.google.com/drive/folders/1XuLxUudlMVMnsUDR-kK9r_YXooT9yMGL?usp=sharing
Hey i have a project on license plate recognition, can u send me the repo link for that
You can use the following link to train a YOLOv8 model on a custom dataset:
github.com/roboflow/notebooks/blob/main/notebooks/train-yolov8-object-detection-on-custom-dataset.ipynb
universe.roboflow.com/wei-lun-wong-rlpuz/car-plate-detection-pnq5k
You can use this dataset or another dataset from Roboflow Universe to train this. The dataset in this link only includes predefined classes, which may not cover all possible variations of license plates. For example, license plates can contain different numbers and letters, such as Roman numerals or characters from languages other than English.
An alternative approach would be to train an object detector to identify the region of a license plate. After that, you can use an OCR method (easyOCR would be a good choice) to extract the characters from the license plate. This method will give more precise results.
Always an indian student that wants to copy code for college
Deep learning-based real-world object detection and improved anomaly detection for surveillance videos
Sir plz guide de this is my final year project how i start 😢
What kind of anomalies are you planning to detect? If you use already trained YOLO models, they can only detect the 80 classes in the COCO dataset.
tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/
If you need more clarification, please send more details about your project to my email.
@@pamudu123ranasinghe7 sir we are beginners we have no idea plz guide us , tell me some steps that we start! Thanks for replying sir ❤️
Which model puts less load on cpu
In my experience, YOLOv8 is better.
If you find it running slowly, you can speed it up by quantizing the model or converting it to a CPU-optimized version.
Another option is to try the YOLOv8 nano model and reduce the input image size for faster inference.
Check out the Ultralytics documentation for easy guidance.
which one is fastest?
YOLOv8
Refer to this for more optimization techniques for achieving a higher speed.
github.com/pamudu123/object-detection-optimization
Hello, can I use this video?
Yes sure, No problem at all
Can you undertake object detection project for our company? We need to identify objects as small as bolts and nuts (of abt 3 cm) using a CCTV camera mounted at about 300 to 400 m away. If yes, how do we contact you?
yes sure, you can contact me via pamudu1111@gmail.com
Can someone tell me that which version is best for window 7?
Fastest
YOLOv8 is fast and easy to use in Windows 7
Refer to this for more optimization techniques for achieving a higher speed.
github.com/pamudu123/object-detection-optimization
@@pamudu123ranasinghe7 thank u so much sir
Please write fps on video
huggingface.co/spaces/Pamudu/YOLO-Battlefield
Try this on huggingface spaces.
You can compare your desired YOLO model with other YOLO models to get an idea about real-time performance and detection accuracy.
hlo can we connect?
yes sure, pamudu1111@gmail.com
is yolov8 is a downgrade ?
Kind of 😄. Altought its library ultralytics are one of the best for developers out there
It runs significantly faster than previous models. By quite a bit. That's a huge plus for many applications. In fact, most video-input applications require speed over accuracy.
huggingface.co/spaces/Pamudu/YOLO-Battlefield
Try this on huggingface spaces.
You can compare your desired YOLO model with other YOLO models to get an idea about real-time performance and detection accuracy.
Yolo V5 is better
v7 is best
Its the worst imo. Every time I train a yolov7 model, its a disappointment.
@@RandomGuy-df1oy I have used YOLOR model It gives me better results than YOLOv7
@@pamudu123ranasinghe7 What about YOLOv8? Currently, I still use v5 despite the new v6 and v7. I'm gonna try YOLOR too, thanks
@@pamudu123ranasinghe7 What about YOLOv8? I still use v5 despite the appearance of v6 and v7. I'm gonna try YOLOR too, thanks.
@@RandomGuy-df1oy But how about those custom datasets of yours? Are they good enough to get good accuracy?🤔🤨