zzjoey/vehica

Vehica: Vehicle classification based on RetinaNet. 基于 RetinaNet 和 Stanford Car Dataset 的车辆型号检测识别

🚖Vehica: Vehicle classification based on RetinaNet

中文版

Vehicle brand & model classification based on RetinaNet & Stanford Car Dataset

✔️Feature

1. Detect vehicle in the image and mark with box. (Work on 196 brands)
2. Show the brand of the vehicle with probability.
3. Time spent during the detection.

👋🏻How to start

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

📸Screenshots

📃Tips

• It may take serval seconds to run the program related to the hardware, please wait after starting.
• Trained Models are here

⚙️Dependencies

• keras-retinanet
• Pyqt5
• Opencv
• Tensorflow
• Matplotlib

---

🚖车辆型号检测识别

基于 RetinaNet 和 Stanford Car Dataset 的车辆型号检测识别方案

✔️功能

1. 检测画面中车辆并使用方框标记（可识别196种型号）
2. 给出车辆型号与可信度
3. 显示识别耗时

👋🏻如何启动

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

📸截图

📃注意

1. 根据不同硬件情况，识别可能耗费数十秒钟，请耐心等待

2. 训练后的模型在这里

⚙️依赖

• keras-retinanet
• Pyqt5
• Opencv
• Tensorflow
• Matplotlib

vehica's Issues

点击开始识别会出现错误

Process finished with exit code -1073740791 (0xC0000409) 请问这个该怎么解决，改成cpu运行16G内存也会报错