convolutional-pose-machines-release
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Network Speed
Hi Shih-En,
Thanks so much for sharing your work. I've implemented your code & it's working great, but I don't get anywhere near realtime performance using a very good GPU. How did you achieve your videos with the realtime performance?
Also, are you using any bayesian filtering for tracking the estimates?
Best regards, Tom
There might be these difference:
- Network itself: we just add a new model that runs faster and scores higher on MPI. Please pull repo and run
testing/get_model.shagain. - We only use single scale testing for the real-time system. You can reduce the number of scales to be search in
config.m. For above please see this demo ipython notebook for more details and explanations. - We used 4 GPUs (all Titan X) to scale up the throughput.
- We used CUDA to accelerate other image processing, and result rendering etc, in the real-time system.
Finally, no we didn't use any temporal information in the video. All results shown are per-frame detection.
Hi Shih-En
Thank you for sharing your great work. 1) I am wondering which model is the fastest for pose estimation? You mentioned in this thread that you do have a faster and more accurate model. an you specify the name? 2) It seems the llink of python notebook is corrupt. Where can I find details regarding the network speed?
Thank you
Hello everyone, In gpu mode, one nvidia gtx 1080 which has 8 g graphics memory can use to train the network and real-time forecasting?
If anyone knows, please tell me, much thanks!