- DISCLAIMER : I am not responsible for any consequences that stem from the illicit use of the contents of this repository.
-
Data extracted from replays produced by a slightly modified version of danser-go
-
Aiming works but clicking does not.
-
All skins used are located in assets/skins
-
Showcase videos Clicking (DOES NOT WORK CURRENTLY) and Aiming.
- The following assume that your monitor/screen size is 1920x1080 (plan to make it dynamic later)
- Clone this repository along with this modified version of danser
- Build danser using the instructions in the repository
- Copy danser-settings.json to
"cloned danser repo"/settings/danser-settings.json - Launch danser using the built binary
- Once danser is done importing in the config dropdown switch it to the settings we copied earlier
- Switch mode to "Watch a Replay" and select the replay you want to train on
- Switch the dropdown on the bottom from "Watch" to "Record"
- Before recording you can configure the settings to use a different skin.
- Once ready click "danse!" and wait for danser to generate the recording.
- Once done it will open a folder with a json file and an mkv file, these are needed to generate the dataset.
- Going back to the osu-ai folder first setup Anaconda
- Run the following in the terminal to create an enviroment
conda create --name osu-ai python=3.9.12
conda activate osu-ai- Install Poetry
- Run the following in the enviroment we created
poetry install
# For cuda support run "poe force-cuda"
# For win32Mouse support run "poe use-win32"- now we can run main
python main.py- You should see this menu
What would you like to do ?
[0] Train or finetune a model
[1] Convert a video and json into a dataset
[2] Test a model
[3] Quit- Select "1" for Convert, name it whatever you want. For the video and json type in the path to the respective files we generated earlier i.e.
a/b/c.mkva/b/c.json. - For the number of threads I usually use 5 and we will leave the offset at 0.
- For
Max images to keep in memory when writingI usually leave it at 0 unless the video is really long - Now wait for the dataset to be generated
- Now we can train. Select "0" to train then "0" for aim. Name it whatever and select the dataset we just made. I usually set max epochs to a very large number since
ctrl+cwill stop training early. - And that's it.
