yolov3 accuracy
Hello, The new version 4 is awesome for the fast dnn speed.
However when I use the dnn(and load yolo weight and cfg). It's not as accurate as original Yolo version. I doubt it's due to the optimization dnn has made. The yolo I am using is yoloV3. I test on a image, and save the detection frame. In some frame the result is just missing.
Here is the Images: Images Could anyone help?
Hmm i am wondering why you are not using yolo native? Is opencv4 faster with evaluation or have better accuracy? If not - i would just say stick to yolo native.
Hi, Im building an appliction using opencv and part of it is detections of objects. Running darknet.exe appart will add a complexity that i might can avoid. further more, opencv detection are faster using cpu, but are not accurate, there is any fix? i used the dnn tutorial, with thresh 0.5 nms = 0.4 scale = 1/255. Thanks
Well running a model on top of opencv adds complexity too? The stuff you are dealing with right now - and the source of you question.
Yes opencv is fast on cpu cause they have optimized code for this. But i run my models on GPU anyway cause i need to be fast.
Its very promising to use opencv as a cross platform cnn/dnn but i found it very time consuming as there was always some little things which went wrong.
From my personal experience i use opencv for low level task like image generation / augmentation and leave the rest up to the cnn/dnn of my choice (yolo or tensorflow). Its just not worth putting so much time into building a monolith which will not work anyway and break on changes on the yolo side.
I hope i dont get downvoted for this - but this is my experience /opinion.
thanks for the replay, maybe i will try to include direclty yolo dll.
That what i do and i have a wrapper around it. So i can consume yolo from every other application regardless of java php or javascript or whatever. All they need to do is call a rest api. This concept is called Microservice
@nitsan57, no one can help you until you describe what "It's not as accurate as original Yolo version." means and which YOLO version is used. Have you tried to use OpenCV's https://github.com/opencv/opencv/blob... sample? Which image is used for tests?
Hello! Im using yolov3 608 608 weights from their site. I used images that i took the picture. In darknet.exe it detected more object then with opencv4. I used the dnn tutorial of opencv4 with the parameters that i mentioned in original question. I must emphasize that opencv detected objects indeed but less.. Thank you.
@nitsan57, "more" and "less" is a wrong way to describe the problem. We cannot try ALL the images from internet to catch it. Please attach three images: an origin image in
.pngformat, resulting image from darknet and resulting image from OpenCV.@dkurt hi, i uploaded one example.