mirror of
https://github.com/helblazer811/ManimML.git
synced 2025-07-15 07:57:41 +08:00
87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
from manim import *
|
|
from PIL import Image
|
|
|
|
from manim_ml.neural_network.layers.convolutional3d import Convolutional3DLayer
|
|
from manim_ml.neural_network.layers.feed_forward import FeedForwardLayer
|
|
from manim_ml.neural_network.layers.image import ImageLayer
|
|
from manim_ml.neural_network.neural_network import NeuralNetwork
|
|
|
|
class SingleConvolutionalLayerScene(ThreeDScene):
|
|
|
|
def construct(self):
|
|
# Make nn
|
|
layers = [
|
|
Convolutional3DLayer(3, 4)
|
|
]
|
|
nn = NeuralNetwork(layers)
|
|
nn.scale(1.3)
|
|
# Center the nn
|
|
nn.move_to(ORIGIN)
|
|
self.add(nn)
|
|
# Play animation
|
|
self.set_camera_orientation(phi=280*DEGREES, theta=-10*DEGREES, gamma=90*DEGREES)
|
|
# self.play(nn.make_forward_pass_animation(run_time=5))
|
|
|
|
class Simple3DConvScene(ThreeDScene):
|
|
|
|
def construct(self):
|
|
"""
|
|
TODO
|
|
- [X] Make grid lines for the CNN filters
|
|
- [ ] Make Scanning filter effect
|
|
- [ ] Have filter box go accross each input feature map
|
|
- [ ] Make filter lines effect
|
|
- [ ] Make flowing animation down filter lines
|
|
"""
|
|
# Make nn
|
|
layers = [
|
|
Convolutional3DLayer(1, 5, 5, 5, 5, feature_map_height=3, filter_width=3, filter_height=3),
|
|
Convolutional3DLayer(1, 3, 3, 1, 1, feature_map_width=3, filter_width=3, filter_height=3),
|
|
]
|
|
nn = NeuralNetwork(layers)
|
|
# Center the nn
|
|
nn.move_to(ORIGIN)
|
|
self.add(nn)
|
|
# Play animation
|
|
# self.set_camera_orientation(phi=280*DEGREES, theta=-10*DEGREES, gamma=90*DEGREES)
|
|
self.play(nn.make_forward_pass_animation(run_time=30))
|
|
|
|
# Make the specific scene
|
|
config.pixel_height = 1200
|
|
config.pixel_width = 1900
|
|
config.frame_height = 6.0
|
|
config.frame_width = 6.0
|
|
|
|
class CombinedScene(ThreeDScene):
|
|
def construct(self):
|
|
image = Image.open('../assets/mnist/digit.jpeg')
|
|
numpy_image = np.asarray(image)
|
|
# Make nn
|
|
nn = NeuralNetwork(
|
|
[
|
|
ImageLayer(numpy_image, height=1.4),
|
|
Convolutional3DLayer(1, 5, 5, 3, 3, filter_spacing=0.2),
|
|
Convolutional3DLayer(2, 3, 3, 1, 1, filter_spacing=0.2),
|
|
FeedForwardLayer(3, rectangle_stroke_width=4, node_stroke_width=4),
|
|
FeedForwardLayer(1, rectangle_stroke_width=4, node_stroke_width=4)
|
|
],
|
|
layer_spacing=0.5,
|
|
camera=self.camera
|
|
)
|
|
|
|
nn.scale(1.3)
|
|
# Center the nn
|
|
nn.move_to(ORIGIN)
|
|
self.add(nn)
|
|
# Play animation
|
|
# self.set_camera_orientation(phi=280* DEGREES, theta=-20*DEGREES, gamma=90 * DEGREES)
|
|
# self.begin_ambient_camera_rotation()
|
|
forward_pass = nn.make_forward_pass_animation(
|
|
run_time=10,
|
|
corner_pulses=False
|
|
)
|
|
print(forward_pass)
|
|
self.play(
|
|
forward_pass
|
|
)
|