Intel® Distribution of OpenVINO™ Toolkit
Community assistance about the Intel® Distribution of OpenVINO™ toolkit, OpenCV, and all aspects of computer vision-related on Intel® platforms.

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fizzgo
Beginner
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I have download openvino_toolkit_runtime_raspbian_p_2021.4.752 on raspberry pi4b. I want to perform yolov3-tiny on raspberry pi4B with NCS2.But when i try it on Ubuntu18 ,some mistakes happend.

The demo i use is   ./intel64/Release/object_detection_demo 

yolov3-tiny.jpg

I get yolov3-tiny.weights in pjreddie/darknet: Convolutional Neural Networks (github.com)

l really need help

thanks

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Peh_Intel
Moderator
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Hi fizzgo,


Have you tried with OpenVINO™ Toolkit Public Pre-Trained Model, yolo-v3-tiny-tf ?


Besides, please also share the Model Optimizer command in converting your yolo-v3 model.



Regards,

Peh


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fizzgo
Beginner
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Second,l tried yolov3-tiny (I got it from pjreddie).I also converted it successfully,but it ran wrongly.I have described it in my first question.

At last,l tried my own yolov3-tiny model(only one class),it detected nothing.The following   pictures shows my orders .

 

Thanks for your help.

 

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fizzgo
Beginner
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First,l have tried yolo-v3-tiny-tf ,but it performed badly.

I got two files yolo-v3-tiny-tf.json and yolo-v3-tiny-tf by the order : python3 downloader.py --name yolo-v3-tiny-tf

then i used mo_tf.py  to convert it to IR(xml bin) successfully.But when i tried it with NCS2,it act like below:

 

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Peh_Intel
Moderator
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Hi fizzgo,


For the OpenVINO™ Toolkit Public Pre-Trained Model, yolo-v3-tiny-tf, you are getting poor inferencing performance due to the model conversion.


You can use the converter.py script to convert the model or manually use mo_tf.py script to convert with full Model Optimizer arguments:

python3 mo_tf.py --input_shape=[1,416,416,3] --input=image_input --scale_values=image_input[255] --reverse_input_channels --transformations_config=$dl_dir/yolo-v3-tiny-tf/yolo-v3-tiny-tf.json --input_model=$dl_dir/yolo-v3-tiny-tf/yolo-v3-tiny-tf.pb

Next, convert the yolo-v3-tiny model ( get from Pjreddie) with the same Model Optimizer arguments especially the --reverse_input_channels argument.


Lastly, for the custom yolo-v3-tiny model (one class), convert the model with the same Model Optimizer arguments and make sure you have modified the classes in yolo_v3_tiny.json.



Regards,

Peh


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fizzgo
Beginner
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Dear Peh,

 

Thanks for your help,i have solved my problems.

 

Regards,

fizzgo

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Peh_Intel
Moderator
708 Views

Hi fizzgo,


This thread will no longer be monitored since this issue has been resolved. If you need any additional information from Intel, please submit a new question. 



Regards,

Peh


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