Official YOLOv7 Pose vs MediaPipe | Full comparison of real-time Pose Estimation | Which is Faster?
ฝัง
- เผยแพร่เมื่อ 7 ก.ค. 2024
- YOLOv7 Pose estimation vs. MediaPipe: Comparison for Human Pose Estimation.
In this video, we make an extensive comparison of YOLOv7-Pose vs. MediaPipe
Our Conclusion:
-YOLOv7 is a multi-person detection framework. MediaPipe can not beat YOLOv7 in this category.
-MediaPipe is observed to be producing good results on low-resolution inputs compared to YOLOv7.
-It is faster than YOLOv7 on CPU inference.
-MediaPipe is also comparatively good at detecting far-away objects (persons in our case). However, when it comes to occlusion, YOLOv7 wins.
-Moreover, YOLOv7 can harness the power of GPU.
In this video, you will get answers to the following questions
✅What is YOLOv7 Pose?
✅What is MediaPipe Pose?
✅How is YOLOv7 Pose different from MediaPipe?
✅How YOLOv7 Pose compares to MediaPipe?
❓FAQ
How does human Pose Estimation work?
What is MediaPipe Pose Estimation?
Can MediaPipe detect multiple people?
What is human pose estimation?
⭐️ Time Stamps:⭐️
0:00-00:30: Introduction
00:30-01:22: What is Human Pose Estimation
01:22-01:50: Applications of Human Pose Estimation
01:50-01:58: Popular Algorithms of Human Pose Estimation
01:58-03:18: What is YOLO Pose
03:18-03:35: YOLO Pose Architecture
03:35-03:46: YOLOv7 Architecture
03:46-04:04: MediaPipe
04:04-04:09: YOLOv7-Pose vs MediaPipe
04:09- 08:01: Result Comparison between YOLOv7-Pose and MediaPipe
08:01- 09:09: Summary
Resources:
📚 Blog post Link: learnopencv.com/yolov7-pose-v...
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• YOLO Master Class: Mas...
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It was a real pleasure to watch such a clear and concise comparison. Excellent video 👍
Glad you liked it @John. More videos incoming!
Nice Video! the test on many cases was so helpful!
Thank you Yohanes!
Awesome comparison, it reduced my work drastically.
We felt the same while working with both YOLOv7 and mediapipe that everyone should know about this comparison! Glad you found it useful.
Great Video!! Thank you for the super informative video, was looking for the right pose estimation to use for my dance project and this really helped!
Glad it was helpful!
Great video comparisson between Yolov and Mediapipe man, good thing I saw this video in my TH-cam feed.
+1 Sub 👍
Awesome, thank you!
great work, thanks!
great explanation! thanks from Argentina
Mediapipe does support multiperson detection now
I like your sharing. It is clear and easy to understand.
Thank you, glad you liked it 😊
thank you so much, this video is very helpful
Glad it is helpful!
Great Video sir. Thank you for sharing.
You are very welcome
Hi thanks for the nice job in the video ... I'm doing single image (3 image consecutive) face landmarks alignment, is Yolo better than MP ?
Thanks for the kind words Geoff!
YOLO does not have good enough number of points for Face landmarks alignment. Mediapipe has a dedicated face mesh model that gives 468 3D landmark points on the face. You can check out our blog post on Creating Snapchat filters using mediapipe. You can learn about how to use the different points for your application.
learnopencv.com/create-snapchat-instagram-filters-using-mediapipe/
Excellent
Thank you. Glad you liked it.
Many thanks for this great video! You mentioned that one can use any object detection model for yolo pose - could you elaborate on that? How could one plug in the smallest version of yolov7?
You would need to retrain the network with a different backbone.
The authors have trained it for the YOLOv7-W6 model. You can train the model using a different yolov7 model. What you would need is a config (.yaml) file corresponding to the smaller model. You can then train the model using the commands given here: github.com/WongKinYiu/yolov7/tree/pose
I doubt it would give accurate results for smaller models. I would use mediapipe if I don't need multi-person pose estimation.
I felt in love with Mediapipe 1 year ago when I worked with facial pose estimation… but YOLOv7 just outperforms it in terms of faces
Hi Maxim
Are you talking about face Detection or Facial Landmarks Detection using YOLOv7?
Hey!
I’m talking about Facial Landmarks Detection. I fine-tuned and used ensemble instead
Great, do you have a repo you could share?
@@LearnOpenCV I worked with medical sensitive data(
No Issues!
👍👍
Thank You!
nice video
Thank you so much!
Can we tweek mediapipe to work even when upper part of body is not visible
The pose solution model consists of two models. The detection model (that detects the body), and the landmark model (that maps the landmarks). If you can make the detection model detect the body without its upper part, theoretically, the solution will work.
호호
I'm not sure what that means, but I'm hoping you liked it! 😊
What about in images
As mentioned in the summary section, it's better to use YOLOv7 or other pose models as mediapipe is optimized for real-time performance which is more suitable for video inference.
Hope that helps!
@@LearnOpenCV so with Multiperson which is better than yoloV7.
@@dj.qb91 For Multiperson we're checking out MMPose next -> github.com/open-mmlab/mmpose. You may also check it out and compare with YOLOv7. Check this out for getting started: mmpose.readthedocs.io/en/v0.29.0/get_started.html#inference-with-pre-trained-models
@@LearnOpenCV thanks 🙏🏾
Are you sure Mediapipe doesn't support Multi-person? pls verify once
As of 2024 Jan update, Mediapipe does supports mutiperson pose but limited to 5 at a time.
For further info check out:
developers.google.com/mediapipe/solutions/vision/pose_landmarker/
📚 LINK TO BLOGPOST: learnopencv.com/yolov7-pose-vs-mediapipe-in-human-pose-estimation/
▶ LINK TO YOLO MASTERCLASS PLAYLIST: th-cam.com/play/PLfYPZalDvZDLALsG9o-cjwNelh-oW9Xc4.html