Deep Learning with PyTorch : Image Segmentation
Offered By: Coursera Project Network via Coursera
Course Description
Overview
In this 2-hour project-based course, you will be able to :
- Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation 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.
Syllabus
- Project Overview
- Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation 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.
Taught by
Parth Dhameliya
Related Courses
Computer Vision: The FundamentalsUniversity of California, Berkeley via Coursera Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital
Duke University via Coursera Fundamentals of Digital Image and Video Processing
Northwestern University via Coursera 医学图像处理技术 Medical Image Analysis
Shanghai Jiao Tong University via Coursera Image Processing and Analysis for Life Scientists
École Polytechnique Fédérale de Lausanne via edX