Vehicle information recognition is a key component of Intelligent Transportation Systems. Color plays an important role in vehicle identification. As a vehicle has its inner structure, the main challenge of vehicle color recognition is to select the region of interest (ROI) for recognizing its dominant color.
Note : For inference tasks only, the weights can be downloaded and training is not required.
In case you want to train the model (preferably, with addition data), edit the Train.ipynb notebook in Training directory.
Download weights from here
Edit config.py file and modify MODEL_PATH variable to the full path of the downloaded weights.
Run the server using python3 api_server.py --port 1234.
Note : The server assumes that the images will be sent as a multipart file using 'image' as the
key.
Link to Original Project - Link
References P. Chen, X. Bai and W. Liu, "Vehicle Color Recognition on Urban Road by Feature Context," in IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 5, pp. 2340-2346, Oct. 2014, doi: 10.1109/TITS.2014.2308897.
"Vehicle Color Recognition using Convolutional Neural Network",
Reza Fuad Rachmadi and I Ketut Eddy Purnama
https://arxiv.org/abs/1510.07391