Video comparison Python project
Python-based video comparison project for a marketing company to track audience interest.
The algorithm we implemented can be described as follows:
- Preprocessing (all information about the videos is extracted, aspect ratio, resolution and fps are taken into account for detailing further analysis);
- Video frame generators are created based on derived parameters;
- To each pair of frames the background subtraction is applied sequentially (clahe for further stabilization effect + bg sub);
- The result of bg sub is followed with some morphological operations to eliminate small noise and improve strong regions of difference;
- Then we search for rectangular regions of difference on resulting mask and apply SSIM check (and, if SSIM indicates difference indeed - additional SIFT check) to each region;
- Once a number of different pairs reach the preset threshold of all frames or a big portion of consequent frames is different (running window approach), videos are labeled as different. If the threshold is not reached until the end, videos are considered equal.
Virtual try-on tool for makeup products
The system consists of a face detection and segmentation model and an algorithm that allows recoloring objects without losing their original texture.
Online sign language interpreter
AI algorithm that converts video of a person using sign language into a text transcript
Influencers search API
The API we’ve developed can help a company to find a best matching influencer. Want to promote your new music album in Instagram stories? Just send this to the API and get a list of accounts which will increase your revenue.