mapextrackt 0.4.3

Pytorch Feature Map Extractor

MapExtrakt

Convolutional Neural Networks Are Beautiful

We all take our eyes for granted, we glance at an object for an instant and our brains can identify with ease. However distorted the information may be, we do a pretty good job at it.

Low light, obscured vision, poor eyesight... There are a myriad of situations where conditions are poor but still we manage to understand what an object it. Context helps, but we humans were created with sight in mind.

Computers have a harder time, but modern advances with convolutional neural networks are making this task a reality and have now surpassed human level accuracy.

Computers are beautiful, neural networks are beautiful. And the maps they create to determine what makes a cat a cat are beautiful.

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MapExtrakt makes viewing feature maps a breeze.

Catch a glimpse of how a computer can see.

MapExtrakt Usage

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First import your model

import torchvision
model = torchvision.models.vgg19(pretrained=True)

Import MapExtract's Feature Extractor and load in the model

from MapExtrackt import FeatureExtractor
fe = FeatureExtractor(model)

Set image to be analysed - input can be PIL Image, Numpy array or filepath. We are using the path

fe.set_image("pug.jpg")

View Layers

fe.display_from_map(layer_no=1)

View Single Cells At a Time

fe.display_from_map(layer_no=2, cell_no=4)

Slice the class to get a range of cells (Layer 2 Cells 0-9)

fe[2,0:10]

Or Export Layers To Video

fe.write_video(out_size=(1200,800), file_name="output.avi", time_for_layer=60, transition_perc_layer=0.2)

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More Examples

For LOTS more - view the jupyter notebook.

Examples

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Installation

It's as easy as PyPI

pip install mapextrackt

or build from source in terminal

git clone https://github.com/lewis-morris/mapextrackt &&\
cd mapextrackt &&\
pip install -e .

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Todo List

• Add the ability to slice the class i.e FeatureExtractor[1,3]
• Show parameters on the image
• Fix video generation
• Enable individual cells to be added to video
• Add video parameters such as duration in seconds.
• Clean up code
• Make speed improvements

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Author

Created by me, initially to view the outputs for my own pleasure.

If anyone has any suggestions or requests please send them over I'd be more than happy to consider.

[e-mail]