Pygame inference

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Pygame inference
Adding an AI character generator to pygame
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For this tutorial we'll use a pre-trained HyperGAN model.
Download the tflite generator
Download the generator https://hypergan.s3-us-west-1.amazonaws.com/0.10/tutorial1.tflite (13.9 MB)
wget https://hypergan.s3-us-west-1.amazonaws.com/0.10/tutorial1.tflite
Load the tflite model
import numpy as np
import tensorflow as tf
​
# Load TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path="tutorial1.tflite")
interpreter.allocate_tensors()
Sample the tflite model to a surface
def sample():
  input_details = interpreter.get_input_details()
  output_details = interpreter.get_output_details()
​
  # Set the 'latent' input tensor.
  input_shape = input_details[0]['shape']
  latent = (np.random.random_sample(input_shape) - 0.5) * 2.0
  input_data = np.array(latent, dtype=np.float32)
  interpreter.set_tensor(input_details[0]['index'], input_data)
​
  interpreter.invoke()
​
  # Get the output image and transform it for display
  result = interpreter.get_tensor(output_details[0]['index'])
  result = np.reshape(result, [256,256,3])
  result = (result + 1.0) * 127.5
  result = pygame.surfarray.make_surface(result)
  result = pygame.transform.rotate(result, -90)
  return result
Init pygame
import pygame
pygame.init()
display = pygame.display.set_mode((300, 300))
Display the surface
surface = sample()
running = True
​
while running:
    for event in pygame.event.get():
        if event.type == pygame.QUIT:
            running = False
    display.blit(surface, (0, 0))
    pygame.display.update()
pygame.quit()
Randomize the latent variable
In the event loop:
if event.type == pygame.KEYDOWN:
    if event.key == pygame.K_SPACE:
      surface = sample()
This runs the generator for a new random sample with each press of the space key.
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Pressing space will change the image
An issue: this uses the CPU not the GPU.
This technique uses the tflite interpreter which was created for mobile devices.
On desktop, it is not GPU accelerated. Unanswered question about this here: https://stackoverflow.com/questions/56184013/tensorflow-lite-gpu-support-for-python​
Putting it all together
See pygame-tutorial.py​
Create your own model
If you want to train a model from scratch, you will need:
a GPU
a HyperGAN training environment
a dataset directory of images to train against
Train your model
hypergan train [dataset]
This will take several hours. A view will display the training progress.
You will need to save and quit the model when you are satisfied with the results.
Build your model
hypergan build
This will generate a tflite file in your build directory.
Fine tune your results
There are many differing configurations you can use to train your GAN and each decision will effect the final output.
You can see all the prepacked configurations with:
hypergan new . -l
More information and help can be found in the discord.
References
​https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/guide/inference.md#load-and-run-a-model-in-python​
​https://www.github.com/HyperGAN/HyperGAN​
Tutorials - Previous
Training a GAN
Next - Tutorials
Creating an image dataset
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Adding an AI character generator to pygame
Create your own model