JetPack 3.1 post installation on TX2 issue

I have test caffe SSD model on TX2 platform,but only got 3 fps.From other issues’ suggestion,JetPack 3.1 which contains TensorRT2.1 and cuDNN v6 can speed up 2x.
As I post install TesnsorRT and cuDNN on target,there is problems like this:
Get:1 file:/var/cuda-repo-8-0-local InRelease
Ign:1 file:/var/cuda-repo-8-0-local InRelease
Get:2 file:/var/libopencv4tegra-repo InRelease
Ign:2 file:/var/libopencv4tegra-repo InRelease
Get:3 file:/var/nv-gie-repo-ga-cuda8.0-gie1.0-20170116 InRelease
Ign:3 file:/var/nv-gie-repo-ga-cuda8.0-gie1.0-20170116 InRelease
Get:4 file:/var/nv-gie-repo-ga-cuda8.0-trt2.1-20170614 InRelease
Ign:4 file:/var/nv-gie-repo-ga-cuda8.0-trt2.1-20170614 InRelease
Get:5 file:/var/visionworks-repo InRelease
Ign:5 file:/var/visionworks-repo InRelease
Get:6 file:/var/visionworks-sfm-repo InRelease
Ign:6 file:/var/visionworks-sfm-repo InRelease
Get:7 file:/var/visionworks-tracking-repo InRelease
Ign:7 file:/var/visionworks-tracking-repo InRelease
Get:8 file:/var/cuda-repo-8-0-local Release [574 B]
Get:9 file:/var/libopencv4tegra-repo Release [347 B]
Get:10 file:/var/nv-gie-repo-ga-cuda8.0-gie1.0-20170116 Release [574 B]
Get:11 file:/var/nv-gie-repo-ga-cuda8.0-trt2.1-20170614 Release [574 B]
Get:8 file:/var/cuda-repo-8-0-local Release [574 B]
Get:12 file:/var/visionworks-repo Release [1,999 B]
Get:9 file:/var/libopencv4tegra-repo Release [347 B]
Get:13 file:/var/visionworks-sfm-repo Release [2,003 B]
Get:10 file:/var/nv-gie-repo-ga-cuda8.0-gie1.0-20170116 Release [574 B]
Get:14 file:/var/visionworks-tracking-repo Release [2,008 B]
Get:11 file:/var/nv-gie-repo-ga-cuda8.0-trt2.1-20170614 Release [574 B]
Get:12 file:/var/visionworks-repo Release [1,999 B]
Get:13 file:/var/visionworks-sfm-repo Release [2,003 B]
Get:14 file:/var/visionworks-tracking-repo Release [2,008 B]
0% [Working]

thanks, how can i fix this?

it seems network problems.when I do this command "sudo apt-get update "on TX2,meet the same problem.

Hi,

Please maximize device performance first:

sudo nvpmodel -m 0
sudo ~/jetson_clocks.sh

thanks ,AastaLLL.
I had maximize device to model 0.

Hi,

What framerate do you expect?

We also have some users use SSD on TX2. They got similar framerate and planned to accelerate it with TensorRT.
Here for your reference:
https://devtalk.nvidia.com/default/topic/1007313/how-to-build-the-objection-detection-framework-ssd-with-tensorrt-on-tx2-/

Thanks,AastaLLL.
From this reference, i know you had got 8~9 fps (SSD model)on TX2 using Jetpack 3.1.
https://devtalk.nvidia.com/default/topic/1021809/jetson-tx2/can-the-nvidia-tensorrt-accelerate-ssd-single-shot-detector-/1

So, today I flash my tx2 platform using jetpack 3.1, it speed up 2x as expected up to 5~8 fps.But the fps flows up and down,and i do the command “sudo ~/tegrastats”,shows the GR3D GPU %0,%99,%57,and etc.The frequency also fluctuates up and down.
Can I get a fixed processing FPS?

Please notice that fps=8-9 is from ssd_pascal_video.py.

For web-camera, it’s recommended to use TensorRT instead of Caffe to get better performance.

Thanks,AastaLLL.
I do run ssd_pascal_video.py on tx2, and use the caffemodel download from github.How can I speed up further more using caffe? And is it normal while the FPS changes wide scope?

Hi,AastaLLL.
I think use FP16 instead of FP32 can speed up. How can I change SSD caffe model to FP16,can you give some suggestions?

Hi,

Sorry for the late reply.

Please make sure you are on JetPack3.1 and maximized the CPU/GPU frequency.
Usually, we can get a stable 8-9 fps results.

For fp16 issue:
Since SSD is a particular Caffe branch, please check the source if it supports fp16 mode.
Thanks.