Raspberry pi openVINO License plate recognition Demo
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Security Barrier Camera С++ Demo
This code sample showcases vehicle detection, vehicle attributes, and license plate recognition.
The demo uses OpenCV to display the resulting frame with detections rendered as bounding boxes and text.
This demo showcases Vehicle and License Plate Detection network followed by the Vehicle Attributes Recognition and License Plate Recognition networks applied on top of the detection results. You can use a set of the following pre-trained models with the demo:
vehicle-license-plate-detection-barrier-0106, which is a primary detection network to find the vehicles and license plates
vehicle-attributes-recognition-barrier-0039, which is executed on top of the results from the first network and reports general vehicle attributes, for example, vehicle type (car/van/bus/track) and color
license-plate-recognition-barrier-0001, which is executed on top of the results from the first network and reports a string per recognized license plate
For more information about the pre-trained models, refer to the https://github.com/opencv/open_model_... "Open Model Zoo" repository on GitHub*.
System Requirements
Hardware:
Raspberry Pi* board with ARMv7-A CPU architecture
32GB microSD card
One of Intel® Movidius™ Visual Processing Units (VPU):
Intel® Movidius™ Neural Compute Stick or Intel® Neural Compute Stick 2
In this VDO we use Intel® Movidius™ Neural Compute Stick ( NCS1 )
Operating Systems:
Raspbian* Stretch, 32-bit
Reference
Install the Intel® Distribution of OpenVINO™ Toolkit for Raspbian* OS
https://software.intel.com/en-us/arti...
Pretrained Models
https://software.intel.com/en-us/open...
Inference Engine Samples
http://docs.openvinotoolkit.org/lates...
OpenVINO, OpenCV, and Movidius NCS on the Raspberry Pi
https://www.pyimagesearch.com/2019/04...