306 - Content based image retrieval​ via feature extraction in python

Code generated in the video can be downloaded from here:

In this video, we will create a content-based image retrieval system which is basically an image-based search. We achieve this task by storing features from images into a database that we will search to retrieve images. Features can be generated many ways. In this tutorial I will extract custom features using a few digital image filters. I will also show feature extraction using pre-trained VGG16 and ResNet50 networks on Imagenet database.

You will learn about the importance of features along the way.

The features from this query image are compared against features from the indexed database and a match score gets reported. The match is performed using the cosine distance method.

The top 3 matching image names are then printed on the screen.

[awaisahmad]

wow sir thank you. I was looking for this for a long time. Thank you.

This was My junior Masters research topic.

[OlgaChambers-xz]

thank you for highlighting important topics in DL. I am following your tutorials to grow up and find interesting tricks for my work. Hope you will continue with this amazing project =)

[srivathsansanthanam]

Sreeni can u make a video on BAYESIAN optimization for image classification/semantic segmentation using traditional machine learning? Would be of great great help.

[sullivanbacchus]

Hi, thank you for all your videos, could you please do a video on soft segmentation

[palurikrishnaveni]

Can you make a video on shallow neural networks and optimization like Bayesian, squirrel optimizers.

[techpriya]

Kindly make some videos on musculoskeletal system.

[hamidalavi]

Thank you for this fun excercise!
I couldn't find the codes on your github :(

[SoumedhT]

Sir, I'm going to learn image processing and want to do PhD