1.3 KiB
Tentative Title For A ResNet-Based Image Classifier
This is a simple ResNet based image classifier for images, using a similar training framework I use to train VALL-E.
Premise
This was cobbled together in a night, partly to test how well my training framework fares when not married to my VALL-E implementation, and partly to solve a minor problem I faced.
This is by no ways state of the art, as it just leverages an existing ResNet arch provided by torchvision
.
Training
-
Throw the images you want to train under
./data/images/
. -
Modify the
./data/config.yaml
accordingly. -
Install using
pip3 install -e ./image_classifier/
. -
Train using
python3 -m image_classifier.train --yaml='./data/config.yaml'
. -
Wait.
Inferencing
Simply invoke the inferencer with the following command: python3 -m image_classifier --path="./data/path-to-your-image.png" --yaml="./data/config.yaml"
Continuous Usage
If you're looking to continuously classify images, use python3 -m image_classifier --listen --port=7860 --yaml="./data/config.yaml"
instead to enable a light webserver using simple_http_server
. Send a GET
request to http://127.0.0.1:7860/?b64={base64 encoded image string}
and a JSON response will be returned with the classified label.