Course Content

Unit 3: Profiling Semantic Segmentation Datasets


Welcome to the unit on profiling semantic segmentation datasets. Our focus is to empower you with the insights needed to improve the quality of your semantic segmentation datasets. You’ll learn how to identify potential issues, derive solutions to enhance model performance, and understand the implications of these features for your datasets.


About this Unit

In this unit, we’ll delve into six vital features, each covered in a dedicated lesson.
While some features, such as Distribution of Object Area, may be analogous to those found in object detection datasets, others like Object Convexity have unique relevance in the realm of semantic segmentation.

By the end of this unit, you’ll have a deeper understanding of the unique complexities involved in semantic segmentation datasets, and the necessary skills to navigate them efficiently. This knowledge will be instrumental in enhancing your ability to train effective models for this specific task. Let’s commence this exploration and elevate your proficiency in semantic segmentation tasks. 

Add Your Heading Text Here
					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")

model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")