Color Image Retrieval

Color Image Retrieval#

Image retrieval is the process of finding images relevant to a given query. Traditionally, this is done using metadata such as tags or descriptions. A more advanced approach is to retrieve images based on their visual content, allowing searches to be driven by characteristics like color, texture, and shape.

In this project, you will develop a content-based image retrieval system with PyTorch. You will focus on the case where the query is a color palette, and the goal is to find images whose dominant colors match the palette. You will build a neural network that learns a similarity metric between natural images and color palettes represented as images, allowing you to retrieve images that match a given set of colors.

Difficulty

Suggested Tutorials

Easy

Convolutional Networks, Feature Extraction, Triplet Loss

Retrieval


Grading

The project will be graded based on the following criteria. Points for each activity are awarded based on quality and completeness (partial credit possible).

Activity

Points (max)

Build a baseline image retrieval system

8

Properly evaluate its performance (precision, recall)

2

Implement and compare a different loss function

2

Collect more images for underperforming color classes

3

Deployment (model made usable)

2

Presentation (clarity & demo)

3

Total

0-20