Car Detection with Raspberry pi 4 + Intel Neural Compute Stick

Car Detection with Raspberry pi 4 + Intel Neural Compute Stick

System Requirements

Hardware:

• Raspberry Pi 4B board or 3B+ 
• 32GB microSD card

• One of Intel® Movidius™ Visual Processing Units (VPU):

Intel® Movidius™ Neural Compute Stick or Intel® Neural Compute Stick 2

Operating Systems:

• Raspbian 10 ( Buster )
• OpenVINO for Raspberry pi ( 2019.1.094 )
• OpenCV 4.0.0
• Python 3.7.3

Machine Learning

Model : SSD MobileNet V2

Video Test

MP4 960x540 Resolution

Source Code in Python
https://docs.openvinotoolkit.org/latest/_inference_engine_ie_bridges_python_sample_object_detection_demo_ssd_async_README.html

Run Code

Test 1 Raspberry pi 4B  NCS2

Test 2 Raspberry pi 4B  NCS1

Test 3 Raspberry pi 3B+  NCS2

Test 4 Raspberry pi 3B+  NCS1 

Test Result

Raspberry Pi 4 vs Raspberry pi 3B+

Reference

Install the Intel® Distribution of OpenVINO™ Toolkit for Raspbian* OS

https://software.intel.com/en-us/articles/OpenVINO-Install-RaspberryPI

Pretrained Models

https://software.intel.com/en-us/openvino-toolkit/documentation/pretrained-models

Inference Engine Samples 

http://docs.openvinotoolkit.org/latest/_docs_IE_DG_Samples_Overview.html

OpenVINO, OpenCV, and Movidius NCS on the Raspberry Pi

https://www.pyimagesearch.com/2019/04/08/openvino-opencv-and-movidius-ncs-on-the-raspberry-pi/

Raspberry pi 4 TensorFlow Face Recognition

Raspberry pi 4 TensorFlow Face Recognition

Hardware
Raspberry pi 4B - 1GB , Raspberry pi 3B+
SD card 32 GB.

Software
Raspbien 10 ( buster )
TensorFlow 1.13.1
OpenCV 4.0.0
Python 3.7.3

Machine Learning 
Model : Facenet Inception Resnet V1

Source Code
FaceRec.  A simple working facial recognition program.
https://github.com/vudung45/FaceRec 

Recognition Dataset

Run Code on Raspberry pi 4 , 3B+ in Image

Recognise with no dataset

Run Code on Macbook Pro 2.3 GHz Intel Core i7 ( 2012 )

Reference

FaceRec.  A simple working facial recognition program.
https://github.com/vudung45/FaceRec

Pretrained models from: https://github.com/davidsandberg/facenet

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://kpzhang93.github.io/MTCNN_face_detection_alignment/

Face recognition with OpenCV, Python, and deep learning

https://www.pyimagesearch.com/2018/06/18/face-recognition-with-opencv-python-and-deep-learning/

Raspberry pi4 Tensorflow object detection

Raspberry pi 4 TensorFlow Object Detection

On June 2019 Raspberry pi announce new version of raspberry pi board.
Now we have a new raspberry pi 4 model B 1GB So try to run TensorFlow object detection and then compare with Raspberry pi3B+ also.

Install TensorFlow on Raspberry pi4

Add some dependency

sudo pip3 install grpcio

sudo pip3 install h5py

Then Download tensorFlow
https://www.piwheels.org/simple/tensorflow/tensorflow-1.13.1-cp37-none-linux_armv7l.whl#sha256=25f4ff027beec1e568baf8e90a07bad59d354560533d6b37318b9efeb70beeb1

sudo pip3 install tensorflow-1.13.1-cp37-none-linux_armv7l.whl

Summary Software for test.

Rasbien 10 ( Buster )
Python 3.7.3
OpenCV 4.0.0
Tensorflow 1.13.1

Run Tensorflow Object Detection

Model SSDlite Mobilenet V2
Video MP4 768x432 12 fps

run on the same img os in same sd-card.

Raspberry pi 4 is 2.xx fps .

Raspberry pi 3 is less than 1 fps.

So, only Raspberry pi Board is not faster enough for tensorFlow object detection application.

Then next we use raspberry pi with intel neural compute stick for better performance.

Raspberry pi 4 vs Raspberry pi3 specification

My Website

http://softpowergroup.net/

email : info@softpowergroup.net  ,amphancm@gmail.com  Tel .+6681-6452400