TrafficLightChallenge-DeepLearning-Nexar
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Traffic Light Recognition Network
This model was created for the nexar challenge 1. It reached 93.6% accuracy on the challenge test data.
This work is based on the squeezeNet model and it's kera's implementation.
Using
in order to use the model to classify image to 3 classes:
- no traffic light
- red light
- green light
just edit the variable TEST_FOLDER
in pred.py file.
then:
python pred.py
it will create csv file: results.csv