I mentioned in a previous post that I had some issues with the results of my yolov7 ai model which was supposed to identify perks based on the image in Dead by Daylight. They were all coming back with “Windows” as the perk for every single one. I’ve now found a way to increase that…
Since the way I was training wasn’t working, I’ve opted to use the model I had going as a means to get coordinates, height and width to automatically crop each perk from each screenshot. I’ll be able to take the upscaled 640×640 images and upload them to roboflow. It’ll be a manual process for me…
I recently have been trying to train an AI model that will be table to ingest a screenshot of the post-game dead by daylight scoreboard and identify all of the perks that are being used. Here is an example of the training data I generated (I played a bunch of games and took screenshots, which…
Added a function to the DBD app that will allow you to toggle between the aggregated list of killers and the last 35 killers (with timestamp) that you faced I’ve also been working on an AI model to identify which perks were used by survivors on the end screen. This has been a particular challenge…
To test this tool, I’ve been using screenshots of the end screen that I can pull up and have it detect it on the screen. Using screenshots though adds bad data to the database in with my good data. I’ve added a button for “Remove Last’ to the bottom which will remove the very last…
Lately I’ve noticed that my friends and I try to recount what all of the killers we faced in Dead by Daylight that night, which got me thinking. What if I wrote a lightweight application that would scan the screen every second for the end of match scoreboard. When detected, read what the killer was…