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65 lines
2.0 KiB
Python

from manim import *
from manim_ml.neural_network.layers.parent_layers import NeuralNetworkLayer
from manim_ml.image import GrayscaleImageMobject, LabeledColorImage
import numpy as np
class PairedQueryLayer(NeuralNetworkLayer):
"""Paired Query Layer"""
def __init__(self, positive, negative, stroke_width=5, **kwargs):
super().__init__(**kwargs)
self.positive = positive
self.negative = negative
self.stroke_width = stroke_width
# Make the assets
self.assets = self.make_assets()
self.add(self.assets)
@classmethod
def from_paths(cls, positive_path, negative_path, grayscale=True):
"""Creates a query using the paths"""
# Load images from path
if grayscale:
positive = GrayscaleImageMobject.from_path(positive_path)
negative = GrayscaleImageMobject.from_path(negative_path)
else:
positive = ImageMobject(positive_path)
negative = ImageMobject(negative_path)
# Make the layer
query_layer = cls(positive, negative)
return query_layer
def make_assets(self):
"""
Constructs the assets needed for a query layer
"""
# Handle positive
positive_group = LabeledColorImage(
self.positive,
color=GREEN,
label="Positive",
stroke_width=self.stroke_width
)
# Handle negative
negative_group = LabeledColorImage(
self.negative,
color=RED,
label="Negative",
stroke_width=self.stroke_width
)
# Distribute the groups uniformly vertically
assets = Group(positive_group, negative_group)
assets.arrange(DOWN, buff=1.5)
return assets
@override_animation(Create)
def _create_layer(self):
# TODO make Create animation that is custom
return FadeIn(self.assets)
def make_forward_pass_animation(self):
"""Forward pass for query"""
return AnimationGroup()