mirror of
https://github.com/helblazer811/ManimML.git
synced 2025-07-09 03:36:22 +08:00
89 lines
2.7 KiB
Python
89 lines
2.7 KiB
Python
from manim import *
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from manim_ml.neural_network.layers import FeedForwardLayer, ImageLayer, EmbeddingLayer
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from manim_ml.neural_network.neural_network import NeuralNetwork
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from PIL import Image
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import numpy as np
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config.pixel_height = 720
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config.pixel_width = 720
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config.frame_height = 6.0
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config.frame_width = 6.0
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class VAECodeSnippetScene(Scene):
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def make_code_snippet(self):
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code_str = """
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# Make Neural Network
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nn = NeuralNetwork([
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ImageLayer(numpy_image, height=1.2),
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FeedForwardLayer(5),
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FeedForwardLayer(3),
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EmbeddingLayer(),
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FeedForwardLayer(3),
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FeedForwardLayer(5),
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ImageLayer(numpy_image, height=1.2),
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], layer_spacing=0.1)
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# Play animation
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self.play(nn.make_forward_pass_animation())
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"""
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code = Code(
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code=code_str,
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tab_width=4,
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background_stroke_width=1,
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# background_stroke_color=WHITE,
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insert_line_no=False,
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background="window",
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# font="Monospace",
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style="one-dark",
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language="py",
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)
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return code
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def construct(self):
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image = Image.open("../../tests/images/image.jpeg")
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numpy_image = np.asarray(image)
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embedding_layer = EmbeddingLayer(dist_theme="ellipse", point_radius=0.04).scale(
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1.0
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)
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# Make nn
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nn = NeuralNetwork(
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[
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ImageLayer(numpy_image, height=1.2),
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FeedForwardLayer(5),
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FeedForwardLayer(3),
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embedding_layer,
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FeedForwardLayer(3),
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FeedForwardLayer(5),
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ImageLayer(numpy_image, height=1.2),
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],
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layer_spacing=0.1,
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)
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nn.scale(1.1)
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# Center the nn
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nn.move_to(ORIGIN)
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# nn.rotate(-PI/2)
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# nn.all_layers[0].image_mobject.rotate(PI/2)
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# nn.all_layers[0].image_mobject.shift([0, -0.4, 0])
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# nn.all_layers[-1].image_mobject.rotate(PI/2)
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# nn.all_layers[-1].image_mobject.shift([0, -0.4, 0])
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nn.shift([0, -1.4, 0])
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self.add(nn)
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# Make code snippet
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code_snippet = self.make_code_snippet()
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code_snippet.scale(0.52)
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code_snippet.shift([0, 1.25, 0])
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# code_snippet.shift([-1.25, 0, 0])
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self.add(code_snippet)
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# Play animation
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self.play(nn.make_forward_pass_animation(), run_time=10)
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if __name__ == "__main__":
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"""Render all scenes"""
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# Neural Network
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nn_scene = VAECodeSnippetScene()
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nn_scene.render()
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