Build a System That Can Identify a Weapon Within a Given Image or Frame

I recently completed a project I am very proud of and figured I should share it in case anyone else is interested in implementing something similar to their specific needs. Before I get started in the tutorial, I want to give a HEFTY thanks to Adrian Rosebrock, PhD, creator of PyImageSearch. I am a self-taught programmer, so without his resources, much of this project would not be possible. He is the epitome of a _mensch- _I could not be more appreciative of the resources he puts on his website. If you want to learn advanced deep learning techniques but find textbooks and research papers dull, I highly recommend visiting his website linked above.

In most projects related to weapon classification, I was only able to find a dataset of 100–200 images maximum. This posed an issue because, from my experience, it is hard to get a working model with so little images. To gather images, I rigged my raspberry pi to scrape IMFDB.com- a website where gun enthusiasts post pictures where a model gun is featured in a frame or clip from a movie. If you visit the website, this will be more clear. To access the images that I used, you can visit my Google Drive. In this zip file, you will find all the images that were used in this project and the corresponding .xml files for the bounding boxes. If you are in need of bounding boxes for a large dataset, I highly recommend ScaleOps.AI, a company that specializes in data labeling for machine learning algorithms. Currently, I have 120,000 images from the IMFDB website, but for this project, I only used ~5000 due to time and money constraints.

#artificial-intelligence #machine-learning #object-detection #python #keras