Note: "speedyblackman" is YT/Blackpanthaa's IGN. Nothing racist.
Here's the plan (Oct 13 2021):
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Three different models on three different datasets.
- Acceleration, break, reverse frames
- Left, right turn frames
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Work on left/right dataset first, then acceleration/break dataset.
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Implement speedyblackman.
Vague TODO:
- Create dataloader for the dataset working with and save the copy to drive.
- Test the dataset on different models.
- Trained the turns data on ResNet18, VGG-19_bn, InceptionV3, MobileNetV2 and AlexNet.
- AlexNet gave the best results when implemented.
- Although the train, test accuracies were high, all the models seemed to overfit over a few epochs except AlexNet.
- Trained the acceleration data on ResNet18, MobileNetV2 and AlexNet.
- MobileNetV2 gave the best results when implemented.
- Almost all the models overfit. So the model that least overfit was chosen for the implementation.
- The data was not sufficient
- 10GB (~52k frames) of turns data was used (which gave pretty good results).
- 1.35GB (~6.8k frames) of acceleration data was used (which was definitely not sufficient and hence every model overfit).
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Get NFS Rivals - you know what to do
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Clone this repository and change directory into it
git clone https://github.com/insaiyancvk/speedyblackman cd speedyblackman
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Download the weights from drive and save them in speedyblackman folder
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Install the dependencies
pip install torch torchvision numpy keyboard opencv-python
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Start the game and run the code
python speedyblackman.py