mtcnn_facenet_cpp_tensorRT
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Deepstream
Is there a way i can deploy using Nvidia Deepstream ? Or create Deepstream app from this?
check this, dlib model and facenet have similar output https://forums.developer.nvidia.com/t/face-recognition-using-dlib-with-jetson-nano/167172
So it is possible
@hirwa145 this was asked before and i think it is a great idea. Let me know if you are interested to work on that
@nwesem I am working on a similar project, but first I'm trying to use dlib's model for face recognition with deepstream
Have you succeeded with it?
currently i am working on https://github.com/riotu-lab/deepstream-facenet this, because to run this repo with deepstream will require us to configure mtcnn as with the deepstream.
Hey, I managed to get facenet working with deepstream but it's a python implementation. shall I put up a pull request? @nwesem
@shubham-shahh yes please. Can you upload it. I am very interested to see how you managed to make it work with Deepstream
I have a python edition, currently I am working on a C++ version as well, shall I PR a python version?
Yes, you can PR the python version
@shubham-shahh you pull requested the python version?
not yet, @nwesem should create a new branch for the python version, meanwhile, I'll commit the project to my account.
Yeah. That is also okay, you can commit it to your account whilest we are waiting for him to open new branch
Yeah. That is also okay, you can commit it to your account whilest we are waiting for him to open new branch
I'll complete it by this weekend
Alright, thank you
hey @shubham-shahh, cool! Thanks for contributing to this project! I am looking forward to see your implementation. I added you as a collaborator on the project, please add your code to a branch called python-develop and I will check it out and merge it if everything works as expected. Currently I am pretty busy with work, but I will take the time to test your implementation asap. If you can't create a new branch just push it to your forked repo and send me a pull request
hey @shubham-shahh, cool! Thanks for contributing to this project! I am looking forward to see your implementation. I added you as a collaborator on the project, please add your code to a branch called
python-develop
and I will check it out and merge it if everything works as expected. Currently I am pretty busy with work, but I will take the time to test your implementation asap.
Hey, I hope you are doing fine, thanks for the branch I'll submit my work by this weekend.
Hey, @nwesem I updated the develop branch of my fork with the python implementation, @hirwa145 please test it and let me know if there are any issues, and once this is tested ill put up a pull request on your develop branch and it would be great if we keep them in separate branches. Here
Hello @shubham-shahh . Great job doing deepstream implementation. So far i tried the python implementation and it is working perfect and thank you. I am currently testing the cpp implementation version even tho it is taking long for testing the sample app and i am not sure why. But i have a question, is there a way to implement the recognition where faces in video files are compared to saved images in the folder and display the name of the person instead of '"person". Thank you.
Hello @shubham-shahh . Great job doing deepstream implementation. So far i tried the python implementation and it is working perfect and thank you. I am currently testing the cpp implementation version even tho it is taking long for testing the sample app and i am not sure why. But i have a question, is there a way to implement the recognition where faces in video files are compared to saved images in the folder and display the name of the person instead of '"person". Thank you.
Hello, did you follow the guide step by step? was there any issue at any step? and thanks for testing. and about your question, I will implement that functionality this weekend if possible but if you want to implement it by yourself i can tell you the approach which you can follow. thanks again
for python implementation, everything works as expected. But for C++ implementation, i have to first test the test sample, so it seems it stuck here
NvMMLiteOpen : Block : BlockType = 261 NVMEDIA: Reading vendor.tegra.display-size : status: 6 NvMMLiteBlockCreate : Block : BlockType = 261
. D you know why?
for python implementation, everything works as expected. But for C++ implementation, i have to first test the test sample, so it seems it stuck here
NvMMLiteOpen : Block : BlockType = 261 NVMEDIA: Reading vendor.tegra.display-size : status: 6 NvMMLiteBlockCreate : Block : BlockType = 261
. D you know why?
Is this the sample App? or the one i included in the repo? whats your video source .mp4 or .h264?
sample_720p.mp4, as mentioned from your instructions
sample_720p.mp4, as mentioned from your instructions
and is it the sample app present already or you are using the repo app?
yes, available since i installed deepstream. it must be tested on that sample? Or i can test on another .mp4 file?
yes, available since i installed deepstream. it must be tested on that sample? Or i can test on another .mp4 file?
The one that is already presemt works with .h264 files only and the one in the repo works with mp4 files and rtsp streams
So which means when i am doing testing c++ implementation. i do this ./deepstream-infer-tensor-meta-app -t infer /opt/nvidia/deepstream/deepstream-5.0/samples/streams/sample_720p.h264
instead of ./deepstream-infer-tensor-meta-app -t infer /opt/nvidia/deepstream/deepstream-5.0/samples/streams/sample_720p.mp4
So which means when i am doing testing c++ implementation. i do this
./deepstream-infer-tensor-meta-app -t infer /opt/nvidia/deepstream/deepstream-5.0/samples/streams/sample_720p.h264
instead of./deepstream-infer-tensor-meta-app -t infer /opt/nvidia/deepstream/deepstream-5.0/samples/streams/sample_720p.mp4
right
Perfect. Now i am able to run C++ implementation successfully and detecting faces as it should. Sometimes misses face that are out of focus.( probably due to resolution/quality of the video) , also if i noticed that when testing on .mp4 or longer video, there is no quiting option, so i have to wait to wait for video to finish so that i quit the app.
Also if it is possible, could you show me how i can implement the function that the name of face owner is displayed please? Thank you