This very lightweight model recognizes clothes pictures stance.
This model classifies clothes picture based on their stance. It can recognize picture of the front, back, label, close up and
more. It is not perfectly accurate on the recognized stance but is perfect to sort pictures consistently e.g. front first,
back second, third closeup and label last.
It has been trained on a dataset made up of 50% commercial studio pictures (from Fashionpedia) and 50% second hand (
=amateur) pictures.
The base model is
nvidia_efficientnet_b0 that has been retrained using pytorch. You can see the training
parameters
here.
As the base model is super small (5.2M parameters), it runs fast on CPU and with a very small memory footprint. It also
runs blazing fast on GPU. CUDA is not required to run the model.
The dataset has been curated by hand. For any enquiry about the training
dataset,
contact me.
