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Training a model using UNET and ResNet34 to do image segmentation on street images
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Image_Segmentation.ipynb
README.md

README.md

Street Image Segmentation

Training a model using UNET and ResNet34 to do image segmentation on street images. Image Segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as image objects).

You can find more about the dataset here.

Notebook

If you are having trouble opening the notebook with github click here to view it with NBViewer.

Results

Input:

image

Output:

image

Color codes of categories

image

We can see that the predictions in this case were pretty accurate. It predicted the buildings, the trees, the vegetation, Bicyclist, Car(Auto), Road, Sign Symbol, Pole, fence. I don't think I have any complains with it.

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