Difficulties of the project
The custom videos were of low quality, with poor lighting.
To improve the picture, we used four computer vision models. They predicted the position of an object in the frame, making the image clearer.
The neural network could color different frames in different ways; noises appeared in the video.
We have improved the work of the algorithm that was responsible for the clarity of the picture.
Time-consuming video processing: a 15 - second video could take 15 minutes. There was a risk that the user would not wait or the servers would not be able to handle the load.
We began to indicate the position of the user in the queue to download the video, if it was necessary to wait. Added spare capacity for stable operation.