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Kulkarni__Vinay
New Contributor I
78 Views

object_detection_demo_yolov3_async.exe not displaying any outputs

Hi ,

    I am trying to work on yolov3 from samples of openvino. I created IR format data from model optimizer and plugged in to samples code.

But the code runs saying read all params and video and then exits out without any output or information.

Is there anything that i am missing ?

Also i tried debugging through visual studio, but it gives pop up saying inference_engine.dll is not installed properly. Hence i ran setupvars batch file , still then it did not work. Whereas in command line it works without any output.

Any ideas, please ?

 

C:\Users\Ignitarium\Documents\Intel\OpenVINO\inference_engine_samples_2015\intel64\Debug>object_detection_demo_yolov3_async.exe -i C:\Users\Ignitarium\Downloads\FroggerHighway_1.mp4  -m C:\Users\Ignitarium\Documents\tensorflow-yolo-v3\yolo_v3.xml -d GPU
InferenceEngine:
        API version ............ 1.4
        Build .................. 17328
[ INFO ] Parsing input parameters
[ INFO ] Reading input
[ INFO:0] VIDEOIO: Enabled backends(6, sorted by priority): FFMPEG(1000); MSMF(990); DSHOW(980); VFW(970); CV_IMAGES(960); CV_MJPEG(950)
[ INFO ] Loading plugin
 

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7 Replies
Gdeep
Beginner
78 Views

Dear vinay

Can I know how you created I.R files, which command you used to convert .pb model to I.R

Kulkarni__Vinay
New Contributor I
78 Views

Hi Gagan,

     This is how i ran for conversion :

python  C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\model_optimizer\mo_tf.py --input_model yolo_v3.pb --tensorflow_use_custom_operations_config  yolo_v3_changed.json --batch 1

also have one from following  :

python  C:\Intel\computer_vision_sdk_2018.4.420\deployment_tools\model_optimizer\mo_tf.py --input_model yolo_v3.pb --tensorflow_use_custom_operations_config  yolo_v3_changed.json --input_shape [1,416,416,3]

 

Gdeep
Beginner
78 Views

Dear Vinay

Which version of the openvino you are using?  I am using R4, In this release, I have a file name "yolo_v3.json' but  there is no file 'yolo_v3_changed.json', and after conversion when I ran inference I am getting very less FPS around 2-FPS output, can you have any idea about how to increase the FPS for this yolo model

Kulkarni__Vinay
New Contributor I
78 Views

Hi Gagan,

      I am struggling to get it running. I am using following :

OpenVino Version : R4 (2018.4.420)

and yolo_v3_changed.json is the same file as that of yolo_v3.json, as i just took one backup.

Can you please help me how did you ran this ?

Can you paste your outputs here, please.

Mine it does not give any output, hence i am not sure how i can check for FPS.

 

Regards

Vinay

nikos1
Valued Contributor I
78 Views

Hello Vinay,

is this issue just for your YOLO? Can you run the other samples without any issues?  Also what is your OS and CPU model?

If only YOLO has issues perhaps you could read more about model optimization and inference in the other threads

https://software.intel.com/en-us/forums/computer-vision/topic/801626

https://software.intel.com/en-us/forums/computer-vision/topic/800049

> OpenVino Version : R4 (2018.4.420)

You may also want to try again with R5 - if it was a setup issue could be solved by a re-install of the SDK.

Cheers,

Nikos

nikos1
Valued Contributor I
78 Views

Hello Gagan,

> I am getting very less FPS around 2-FPS output, can you have any idea about how to increase the FPS for this yolo model

I think this is typical speeds we are seeing for the 608 size on both CPU/GPU path. Faster CPUs or GT4 GPUs will be a bit faster.

Maybe try tiny yolo or size 320.

Cheers,

Nikos

Kulkarni__Vinay
New Contributor I
78 Views

Hi Nikos,

     As per your advice, i uninstalled and installed R5.

My Demo application runs , whereas yolov3 does not run even with -h option.

There is some relation to setupvars.bash , when ran on same cmd line it shows help of yolo otherwise it does not.

Also i am not able to debug from visual studio too.