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ML Camera

This Artificial Intelligence Camera uses Machine Learning models to classify images real time from your iPhone camera

This Artificial Intelligence Camera uses Machine Learning models to classify images real time from your iPhone camera

ML Camera

by Joao Frasco
ML Camera
ML Camera
ML Camera

What is it about?

This Artificial Intelligence Camera uses Machine Learning models to classify images real time from your iPhone camera. You don't need to take a photo, you just point your iPhone camera at any object or scene, and the classification happens instantaneously. I've provided five different machine learning models available for iOS, including: GoogLeNet Places (for classifications of scenes), Inceptionv3, VGG16, Resnet50, and SqueezeNet (all trained to classify objects across 1000 categories). In addition to classifying things, it also provides the probability of the classification label given.

ML Camera

App Details

Version
2023.10.11
Rating
NA
Size
192Mb
Genre
Utilities
Last updated
October 11, 2023
Release date
September 23, 2017
More info

App Store Description

This Artificial Intelligence Camera uses Machine Learning models to classify images real time from your iPhone camera. You don't need to take a photo, you just point your iPhone camera at any object or scene, and the classification happens instantaneously. I've provided five different machine learning models available for iOS, including: GoogLeNet Places (for classifications of scenes), Inceptionv3, VGG16, Resnet50, and SqueezeNet (all trained to classify objects across 1000 categories). In addition to classifying things, it also provides the probability of the classification label given.

This is a simple but very powerful tool that demonstrates how far artificial intelligence and machine learning has come, especially the power of deep neural networks and specifically, convolutional neural networks.These models are all freely available from the internet under the licenses provided by the links below.

GoogLeNetPlaces: Creative Common License. More information available at http://places.csail.mit.edu

Resnet50: MIT License. More information available at https://github.com/fchollet/keras/blob/master/LICENSE

Inceptionv3: MIT License. More information available at https://github.com/fchollet/keras/blob/master/LICENSE

VGG16: Creative Commons Attribution 4.0 International(CC BY 4.0). More information available at https://creativecommons.org/licenses/by/4.0/

SqueezeNet: BSD License. More information available at https://github.com/DeepScale/SqueezeNet/blob/master/LICENSE

MobileNet: Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0

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