Aerial Image Segmentation with PyTorch

Por: Coursera . en: , ,

In this 2-hour project-based course, you will be able to :

- Understand the Massachusetts Roads Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation domain augmentations to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair.

- Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library.

- Create train function and evaluator function which will helpful to write training loop. Moreover, you will use training loop to train the model.

- Finally, we will use best trained segementation model for inference.

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