i am only half way through the video and this is by far the best one i've seen yet. zero issues following, very clearly explained and the structure is perfect. done! Thanks!!: MBP M2 Pro on 640x640 video running at 29ms per frame on battery power, 20ms on full power. Rough calculation with ms per 100k pixels shows it's about 4x faster than M1. Also 170ms on CPU is quite good
Yoooo your blog was so short and accurate! Didn't know that "mps" is the equivalent to cuda to using the mac gpu! My processtimes reduced from 3000ms to 100ms! Lessgo
Can the teacher guide a lesson to identify objects with yolo and control the webcam to follow that object? using jetson nano. Thank you very much sir, have a nice evening
On my M2 MacBook Air I got this result (in line with the older GPU?) 0: 384x640 1 dog, 28.6ms Speed: 1.4ms preprocess, 28.6ms inference, 11.0ms postprocess per image at shape (1, 3, 384, 640)
Hi, thanks your video. When I use my macbook pro (M1pro) test my MPS is appear true, but run my code I can't saw the speed is incerase. It seems like doesn't work by gpu. How can I to solve ? tks
Hello Pysource, can you please provide an idea or tutorial to predict a person weight using computer vision in real time ? Can you please help me on that
Hi On my laptop Rtx 3060, with input video 1280x720 and inference image size 800x480, i get 6ms with Tensor Rt, segemtation medium model. Wich is near 10 times faster than M1... And on the M1, post-process is 13.4ms...
Are you using miniconda M1 version? if so which check the python using mps like below: import platform print(platform.platform()) you should get output something like this -- "macOS-13.2.1-arm64-arm-64bit"
Hi, i am searching for a tool to identify archaeological finds from photos. We need size, color, and hopefully with a big database, type, and date when it was used. Do you know any?
i am only half way through the video and this is by far the best one i've seen yet. zero issues following, very clearly explained and the structure is perfect.
done! Thanks!!: MBP M2 Pro on 640x640 video running at 29ms per frame on battery power, 20ms on full power. Rough calculation with ms per 100k pixels shows it's about 4x faster than M1. Also 170ms on CPU is quite good
Yoooo your blog was so short and accurate! Didn't know that "mps" is the equivalent to cuda to using the mac gpu! My processtimes reduced from 3000ms to 100ms! Lessgo
That's really Perfect clear! Thank you.
precise and on point, perfect video!
Hello Sergio Canu, thanks for the interesting video! When will the course on training YOLO v8 on custom object detector ?
hello pysource i love your videos and please make a video on action recognition using pytorch and python , thank you ❤️
You are a hero! Very motivating
Can the teacher guide a lesson to identify objects with yolo and control the webcam to follow that object? using jetson nano. Thank you very much sir, have a nice evening
Thanks! , very useful
Can you do an example counting like haw many cows across the line similar a counting people Chosen one classes.
On my M2 MacBook Air I got this result (in line with the older GPU?)
0: 384x640 1 dog, 28.6ms
Speed: 1.4ms preprocess, 28.6ms inference, 11.0ms postprocess per image at shape (1, 3, 384, 640)
Hi, thanks your video. When I use my macbook pro (M1pro) test my MPS is appear true, but run my code I can't saw the speed is incerase. It seems like doesn't work by gpu. How can I to solve ? tks
excelent video
Hello Pysource, can you please provide an idea or tutorial to predict a person weight using computer vision in real time ? Can you please help me on that
Hey Pysource can you make how you can detect if a truck has lifted wheel axle or not?
Hi
On my laptop Rtx 3060, with input video 1280x720 and inference image size 800x480, i get 6ms with Tensor Rt, segemtation medium model. Wich is near 10 times faster than M1... And on the M1, post-process is 13.4ms...
Make a video on segmentation and other Yolo modules
I am getting errors in attributes not in list
nice video ! How to directly show the actual name of the detected object instead of numbers ?
Thank you
instead of cv2.putText(frame, str(cls)), do cv2.putText(frame, result.names[cls])
Hi, I’m trying to train yolov8 on my M1 Pro MacBook using mps but it doesn’t work. Did you have any luck in training for obj detection?
facing same problem
Are you using miniconda M1 version?
if so which check the python using mps like below:
import platform
print(platform.platform())
you should get output something like this -- "macOS-13.2.1-arm64-arm-64bit"
facing same problem
update to atleast 12.3
Hi, i am searching for a tool to identify archaeological finds from photos. We need size, color, and hopefully with a big database, type, and date when it was used. Do you know any?
su ubuntu desktop 22.04 con una A4000 i frame vengono elaborati in un tempo medio intorno ai 13ms con punte di 18ms... direi niente male yolo8
yolov8 custom object detection tutorial ?
Ciao, dove posso scaricare il video dei cani in modo da fare lo stesso test di velocità della mia GPU?
How to use yolov8 to track objects so that the trajectory is drawn?
in first step it showing that comand not found: pip
is it same for mac m2
Hi , bro how can i speak with you
Or like a counting a car going up and down only selecting only one animal classes with yolo v8 for Mac m1
Rgds.
come back man, we need you!
Really need help