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CNN Attention layer to be used with tf or tf.keras

Project description


GitHub license PyPI - Python Version PyPI PyPI - Wheel

A set of image attention layers implemented as custom keras layers that can be imported dirctly into keras

Currently Implemented layers:


You can see the projects official pypi page :

pip install visual-attention-tf

Use --no-dependencies if you have tensorflow-gpu installed already


from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Conv2D
from visual_attention import PixelAttention2D , ChannelAttention2D,EfficientChannelAttention2D

inp = Input(shape=(1920,1080,3))
cnn_layer = Conv2D(32,3,,activation='relu', padding='same')(inp)

# Using the .shape[-1] to simplify network modifications. Can directly input number of channels as well
Pixel_attention_cnn = PixelAttention2D(cnn_layer.shape[-1])(cnn_layer)
Channel_attention_cnn = ChannelAttention2D(cnn_layer.shape[-1])(cnn_layer)
EfficientChannelAttention_cnn = EfficientChannelAttention2D(cnn_layer.shape[-1])(cnn_layer)

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