mirror of
https://github.com/helblazer811/ManimML.git
synced 2025-07-15 07:57:41 +08:00
46 lines
1.5 KiB
Python
46 lines
1.5 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.layers.parent_layers import ThreeDLayer
|
|
from manim_ml.neural_network.neural_network import NeuralNetwork
|
|
|
|
# Make the specific scene
|
|
config.pixel_height = 1200
|
|
config.pixel_width = 800
|
|
config.frame_height = 6.0
|
|
config.frame_width = 6.0
|
|
|
|
|
|
class CombinedScene(ThreeDScene):
|
|
def construct(self):
|
|
image = Image.open("../../assets/doggo.jpeg")
|
|
numpy_image = np.asarray(image)
|
|
# Rotate the Three D layer position
|
|
ThreeDLayer.rotation_angle = 15 * DEGREES
|
|
ThreeDLayer.rotation_axis = [1, -1.0, 0]
|
|
# Make nn
|
|
nn = NeuralNetwork(
|
|
[
|
|
ImageLayer(numpy_image, height=1.5),
|
|
Convolutional3DLayer(1, 7, 7, 3, 3, filter_spacing=0.32),
|
|
Convolutional3DLayer(3, 5, 5, 1, 1, filter_spacing=0.18),
|
|
],
|
|
layer_spacing=0.25,
|
|
layout_direction="top_to_bottom",
|
|
)
|
|
# Center the nn
|
|
nn.move_to(ORIGIN)
|
|
nn.scale(1.5)
|
|
self.add(nn)
|
|
# Play animation
|
|
forward_pass = nn.make_forward_pass_animation(
|
|
corner_pulses=False,
|
|
all_filters_at_once=False,
|
|
highlight_active_feature_map=True,
|
|
)
|
|
self.wait(1)
|
|
self.play(forward_pass)
|