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Weather Classification and Image Restoration Algorithm Attentive to Weather Condition in Autonomous Vehicles


Summary

With the advent of deep learning, a lot of attempts have been made in computer vision to substitute deep learning models for conventional algorithms. Among them, image classification, object detection, and image restoration have received a lot of attention from researchers. However, most of the contributions were refined in one of the fields only. We propose a new paradigm of model structure. End-to-end model which we will introduce classifies noise of an image and restores accordingly. Through this, the model enhances universality and efficiency. Our proposed model is an 'One-For-All' model which classifies weather condition in an image and returns clean image accordingly. By separating weather conditions, restoration model became more compact as well as effective in reducing raindrops, snowflakes, or haze in an image which degrade the quality of the image.


Code explanation

Train

You can train our model with your own dataset

Test

You can test with the given samples.
If you start the test files, you can see the denoised result of the test samples.

$ python Deraining_test.py
$ python Dehazing_test.py
$ python Desnowing_test.py

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