TL_Dataset_Classification

This repo implements an end-to-end classifier in Traffic Light Dataset based on pytorch.

Requirements

• pytorch：0.4.0
• torchsummary：pip install torchsummary
• cv2: pip install opencv-python
• matplotlib
• numpy

How To Run

First, you should clone this repo:

$ git clone https://github.com/FangYang970206/TL_Dataset_Classification

Second, download the dataset with onedrive, baiduyun or google. Move the TL_Dataset.zip in the TL_Dataset_Classification/, then unzip the TL_Dataset.zip.

Third, start training.

$ python main.py

or(custom)

$ python main.py --img_resize_shape tuple --batch_size int --lr float --num_workers int --epochs int --val_size float --save_model bool --save_path str 

The val_size(defualt=0.3) is radio in whole dataset.

Result

learning curve:

In the testset, achieve 97.425%. (keep improving)