Vehicle brand & model classification based on RetinaNet & Stanford Car Dataset
- Detect vehicle in the image and mark with box. (Work on 196 brands)
- Show the brand of the vehicle with probability.
- Time spent during the detection.
git clone https://github.com/joey66666/vehicle-classify.git
cd vehicle-classify/vehicle_UI
conda install tensorflow==1.14.0 opencv numpy matplotlib keras
pip install pyqt5 keras-retinanet
cd keras_retinanet
mkdir snapshots
wget https://github.com/joey66666/vehicle-classify/releases/download/0.01/converted_restnet50_model.h5
python vehicle_ui.py
- It may take serval seconds to run the program related to the hardware, please wait after starting.
- Trained Models are here
- keras-retinanet
- Pyqt5
- Opencv
- Tensorflow
- Matplotlib
基于 RetinaNet 和 Stanford Car Dataset 的车辆型号检测识别方案
- 检测画面中车辆并使用方框标记(可识别196种型号)
- 给出车辆型号与可信度
- 显示识别耗时
git clone https://github.com/joey66666/vehicle-classify.git
cd vehicle-classify/vehicle_UI
conda install tensorflow==1.14.0 opencv numpy matplotlib keras
pip install pyqt5 keras-retinanet
cd keras_retinanet
mkdir snapshots
wget https://github.com/joey66666/vehicle-classify/releases/download/0.01/converted_restnet50_model.h5
python vehicle_ui_cn.py
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根据不同硬件情况,识别可能耗费数十秒钟,请耐心等待
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训练后的模型在这里
- keras-retinanet
- Pyqt5
- Opencv
- Tensorflow
- Matplotlib