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YOLOv8 memang belum ada jurnalnya sampai sekarang

alhamdulillah, sama-sama

Both models were authored by the same team. They claimed yolov8 is better for both cases. However some users said they experienced yolov5 was better for their dataset. At the end, you have to check it by yourself to your dataset. I suggest, start with yolov8.

Needs a lot of modification

@@Dr.Priyanto.Hidayatullah will you update the course content in the future or i shouldn’t buy now?

@@chihebnouri5541 At the moment, this course is specialized for YOLOv8

Beberapa orang bilang seperti itu. Tapi beda video bisa beda hasilnya.

Kalau khusus Apple, di kelas kami belum ada. Tapi pengguna Apple bisa menggunakan Google colab. Kami sediakan file untuk dieksekusi di google colabnya (yolov7 dan YOLOv8). Bisa di searching di udemy YOLOv8, lalu cari yang instruktur nya saya.

Iya YOLOv8 lebih akurat. Namun di kasus tertentu, yolov9 lebih akurat. Kalau ingin lebih akurat lagi, harus dilakukan modifikasi. Bisa arsitektur, hyperparameter, atau tambah data.

Hi marcoz. Unfortunately no. YOLOv8 is the sequel of YOLOv5. Authored by the same team. Has many similarities. Has better performance than YOLOV5. Supposed you want to switch to YOLOv8 and want to improve the performance, this course is definitely for you.

@@Dr.Priyanto.Hidayatullah Hi Dr. for some reason I am getting much better accuracy with yolov5 than yolov8. would be really nice if you make a course about yolov5 too

That would be making another video :D But thank you for asking

I have answered your question in another video

@@Dr.Priyanto.Hidayatullah YOLOv10 in your case. You would want the faster response.

@@Canna_Science_and_Technology yes

For accuracy, choose between YOLOv8 / v9. For speed, YOLOv10

@@Dr.Priyanto.Hidayatullah thanks!

@@Dr.Priyanto.Hidayatullah Hello sir, i tried both yolov8 and yolov9 for conveyor belt tear with a dataset of 1300 images(75%training, 13%valid, 12%test), but i am getting low accuracy, around 57%precision, 34% recall, 32%mAP50 after training for 65 epochs. How can i increase it?

@@ramyeonmokja there are many way how to improve accuracy. 1. Is the accuracy still increasing as the training goes? If yes continue the training, you need more epoch 2. Do hyperparameter tuning 3. Modify the architecture so it suit you study case. 4. Add drop out if necessary 5. Increase first layer resolution And many more

Menurut saya bisa. Pas mengerjakannya harus sabar dan telaten

@@Dr.Priyanto.Hidayatullah Apakah ada harga promo untuk mengikuti kelasnya di Udemy Prof?

@@dosenswasta www.udemy.com/course/yolo-performance-improvement-masterclass/?couponCode=C00946B7B921C18E4ED9 Ini saya buatkan. Kuponnya tinggal berlaku 2-3 HARI lagi saja.

Mohon diperhatikan, kupon ini untuk kursus peningkatan performa YOLOv8 yang memang membahas cukup dalam tentang arsitektur YOLOv8 dan modifikasinya

Silakan bergabung pak. Namun mohon maaf, belum ada fasilitas temu muka online dari udemy. Tapi bapak bisa bertanya via QA section

Berdasarkan papernya, seperti itu pak. Hasil eksperimen kami juga seperti itu

Object detection in this video uses a confidence threshold of 0.25. The resolution is 1080p.

You're welcome!

IoU parameter is Intersection over Union (IoU) threshold. IoU is the ratio of the overlapping area between the predicted bounding box and the ground truth bounding box. The detection result is said to be correct, if it has an IoU value greater than or equal to this threshold.

thank you i havent read the docs hehe im sorry before that, i face a problem with modified model the result cant be get.. can you explain why my experiment get 0 on map value ?

@@yudisdwi1050 most probably, the problem is in the model.

Hi! Try to find the solution here support.udemy.com/hc/en-us/articles/360000165907-Payment-Methods-on-Udemy I hope it helps

You might want to try using different devices (laptop/mobile phone).

Thank you. Yes we do recommend bit.ly/Improve-YOLOv8 Regarding the subtitle, we Will consider it.

Based on architecture file github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/models/v8/yolov8-cls.yaml In the classification, there is no SPPF block in the backbone. After that in the head, there is only a classify block

Not with the channel, but with the resolution.

It is in the description. Or you can use this one bit.ly/YOLOv7_v8_v9_Course

Pertama, mobil dianggap Cell phone itu sudah suatu yg fatal. Yang kedua, kalaupun kelasnya benar (ada kasus lain), akurasinya lumayan bedanya.

Thank you for your kind words. Thank God

You have an accurate conclusion 👍

That would probably a long tutorial 😬

The colab is available if you enroll to the course 🙏 bit.ly/Improve-YOLOv8

@@Dr.Priyanto.Hidayatullah yes sir surely! Kinly share a discount link if you have any. I am so willing to learn from your courses.:)

@@healingherselfdaily5650 here you go: www.udemy.com/course/yolo-performance-improvement-masterclass/?couponCode=C00946B7B921C18E4ED9

it's time limited btw. Grab it fast!

You can write as arguments when you do the training. The hyperparameter is nlisted here docs.ultralytics.com/usage/cfg/#train-settings

@@Dr.Priyanto.Hidayatullah Thank you so much, and wht about if want to change in the architecture of the model inside , like the numbre of layers and ect..

@@ikramessafi9560 then the best option is you enroll to my course. We can discuss deeper there: bit.ly/Improve-YOLOv8

SiLU activation function

SiLU activation function

@@Dr.Priyanto.Hidayatullah Thank you sir. What about attention module?

@@businessjournal339 i have to check the code.

@@businessjournal339 I have check the source code and the paper, i'm not sure there is an attention module in YOLOv9. In fact, there is someone who wants to add attention module to YOLOv9 github.com/WongKinYiu/yolov9/issues/454

Thank you. Thank God..

in one POV, yes

You can downlooad it from here: stunningvisionai.com/article/yolov9-architecture

did you resolve this error?

Not yet. We are working on something else at the moment

For a list of activation functions that can be used, you can see the following link pytorch.org/docs/stable/nn.html#non-linear-activations-weighted-sum-nonlinearity You can change it in common.py file. github.com/WongKinYiu/yolov9/blob/main/models/common.py

Thank you, alhamdulilah

Upload your video by following the tutorial. Change the video path accordingly

Sir, i tried but it shows me error for the road folder. How can i solve this?

@@hridoydev8730 have you follow the tutorial 100% and working? If yes, then just change the video file name with yours

That would be another level of explanation. We need another video for it

No, IMO you don't have to. Tensorrt is related to the GPU. Your GPU is ok. You might want to check my tutorial in this channel on how to use tensorrt. Hope it helps

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