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.