Course Content

Unit 2: Profiling Object Detection Datasets


Welcome to the unit on profiling object detection datasets. In this section, we will dive into key object detection dataset features such as distribution of bounding box width and height. You will learn to compute, analyze, and interpret these features, giving you the tools to identify and rectify potential issues that could compromise your model’s performance on object detection tasks. 

About this Unit

This unit is composed of seven lessons, each honing in on a distinct key feature of object detection datasets. Each lesson offers an in-depth look at the selected feature, exploring its significance, highlighting the potential pitfalls, and suggesting practical solutions to overcome these hurdles.

This unit is designed to equip you with a robust understanding and tools to improve your object detection dataset preparation and training. Get ready for a deep dive into the world of object detection datasets! 

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

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

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