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YOLO for ALPR and vehicle detection with mxnet framework

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YOLOv3 For ALPR And VOR

ALPR: Automatic License Plate / VOR: Vehicle Orientation Recognition Recognition

Contents

Demo

ALPR室內測試影片連結


ALPR室外測試影片連結


模型車姿態辨識影片連結


驗證姿態辨識影片連結


ALPR+IBVS+VOR


Installation

  • Install ROS(Not necessary for train/valid)
  • Install ROS camera package(Not necessary for train/valid)
(sudo) apt-get install ros-$version-usb-cam
(sudo) apt-get install ros-$version-cv-bridge
  • Download Source Code
git clone https://github.com/n8886919/YOLO
  • Install Dependencies

如果不是使用CUDA10,請將requirements.txt 中mxnet-cu100改成對應版本 (ex: CUDA9.2->mxnet-cu92)

# use Conda(optional)
conda create --name yolo_test python=2.7 pip
conda activate yolo_test
# then
cd <$git clone path>
pip install -r requirements.txt 

Projects

預測車牌在空間中的位置與姿態,並將車牌以此姿態投影至相機平面,找出邊界框,最後將邊界框變形回長方形,以利後續辨識文字。由於需要知道車牌姿態來訓練,因此訓練資料完全以合成方式產生。 可匯出網路成ONNX格式,以TensorRT進行推斷,在Jetson Xavier約可達50FPS

用於辨識車牌偵測後變形回長方形車牌的文字。

Blender合成車輛訓練圖片,用於預測車輛方位角、俯角與邊界框。

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