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tracking wildlife in minecraft using deep learning :hocho: :chicken:

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deep-learning computer-vision object-tracking object-detection minecraft heatmaps data-augmentation pytorch opencv pyautogui

deep-chicken-terminator's Introduction

deep-chicken-terminator

deep learning to track (and possibly kill) chickens in minecraft ๐Ÿ”ช ๐Ÿ”

Binder

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Step 1 - collecting training data for the deep neural network

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  • This was mostly just me taking cropped screenshots of animals while playing the game, took about 40 screenshots of each animal.
  • The 20 screenshots of each animal were then augmented and got 500 samples of each.
  • The dataset is very small, but it works anyways for now

Step 2 - training a deep learning model on the samples

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  • The architecture was kept intentionally small so that it keeps a good response time on the live feed
  • The dataset had only 2000 images sized at 50*50, so training barely took any time

Step 3 - Collecting more training data with the trained model

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  • this is done by saving the frames which give a probaility of over 99% on the pre trained model
  • these saved images are again used for further training, which means hunter() is getting better and better.

Step 4 - detecting a and tracking chicken (or any animal for that matter) with the mouse using the trained model

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  • This was done using a custom detect_animal_numpy() function which iterates through the image with a certain kernel size and a stride size, and feeds each sample to the trained NN (nicknamed hunter)
  • A heatmap is then generated from the output of the NN which gives us a probability distribution over the image of a certain animal ( chicken, pig, or panda)
  • why use heatmaps instead of rectangles ? because they look cooler.

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Step 5 (and probably the final step) - Train hunter() to detect fellow villagers and wipe out whole villages

  • Chickens are just an excuse, it can be easily modified to shoot arrows on anything that moves.
  • This is yet to be done.

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