Tensorflow Image Classifier
This is the code for 'Image Classifier in TensorFlow in 5 Min on YouTube. Use this CodeLab by Google as a guide. Also this tutorial is quite helpful.
##Requirements
##Usage
You just need to make a "classifier" directory with a directory "data" inside it with all your images For example
[any_path]/my_own_classifier/
[any_path]/my_own_classifier/data
[any_path]/my_own_classifier/data/car
[any_path]/my_own_classifier/data/moto
[any_path]/my_own_classifier/data/bus
and then put your image on it. This "classifier" directory will have your samples but also trained classifier after execution of "train.sh".
##Train process
Just type
./train.sh [any_path]/my_own_classifier
And it will do anything for you !
##Guess process
Just type for a single guess
./guess.sh [any_path]/my_own_classifier /yourfile.jpg
To guess an entire directory
./guessDir.sh [any_path]/classifier [any_path]/srcDir [any_path]/destDir
Example of result
# ./guess.sh /synced/tensor-lib/moto-classifier/ /synced/imagesToTest/moto21.jpg
moto (score = 0.88331)
car (score = 0.11669)
Use an absolute file path for classifier and images because the script dos not support relative path (volume mounting)
#The Challenge
Make your own classifier for scientists, then post a clone of this repo with your retrained model in it. (you can name it retrained_graph.pb and it will be around 80 MB. If it's too big for GitHub, upload it to DropBox and post the link to it in your README)
#Credits
Credit goes to Xblaster for the majority of this code. I've merely created a wrapper.