dcgan_fashiongen

⚠️ Notice: Limited Maintenance

This project is no longer actively maintained. While existing releases remain available, there are no planned updates, bug fixes, new features, or security patches. Users should be aware that vulnerabilities may not be addressed.

GAN(Generative Adversarial Networks) models using TorchServe

• In this example we will demonstrate how to serve a GAN model using TorchServe.
• We have used a pretrained DCGAN model from facebookresearch/pytorch_GAN_zoo (Introduction to DCGAN on FashionGen)

1. Create a Torch Model Archive

Execute the following command to create dcgan_fashiongen.mar :

./create_mar.sh

The create_mar.sh script does the following :

• Download the model's source code, extract the relevant directory and zip it. (--extra-files)
• Download a checkpoint file DCGAN_fashionGen-1d67302.pth. (--serialized-file)
• Provide a custom handler - dcgan_fashiongen_handler.py. (--handler)

Alternatively, you can directly download the dcgan_fashiongen.mar

2. Start TorchServe and Register Model

mkdir modelstore
mv dcgan_fashiongen.mar modelstore/
torchserve --start --ncs --model-store ./modelstore --models dcgan_fashiongen.mar --disable-token-auth --enable-model-api

3. Generate Images

Invoke the predictions API and pass following payload(JSON)

• number_of_images : Number of images to generate
• input_gender : OPTIONAL; If specified, needs to be one of - Men, Women
• input_category : OPTIONAL; If specified, needs to be one of - One of - SHIRTS, SWEATERS, JEANS, PANTS, TOPS, SUITS & BLAZERS, SHORTS, JACKETS & COATS, SKIRTS, JUMPSUITS, SWIMWEAR, DRESSES
• input_pose : OPTIONAL; If specified, needs to be one of - id_gridfs_1, id_gridfs_2, id_gridfs_3, id_gridfs_4

Example

1. Create a single image (random gender, category, pose)

   curl -X POST -d '{"number_of_images":1}' -H "Content-Type: application/json" http://localhost:8080/predictions/dcgan_fashiongen -o img1.jpg
   

   Result image should be similar to the one below -

2. Create '64' images of 'Men' wearing 'Shirts' in 'id_gridfs_1' pose

   curl -X POST -d '{"number_of_images":64, "input_gender":"Men", "input_category":"SHIRTS", "input_pose":"id_gridfs_1"}' -H "Content-Type: application/json" http://localhost:8080/predictions/dcgan_fashiongen -o img2.jpg
   

   Result image should be similar to the one below -

3. Create '32' images of 'Women' wearing 'Dresses' in 'id_gridfs_3' pose

   curl -X POST -d '{"number_of_images":32, "input_gender":"Women", "input_category":"DRESSES", "input_pose":"id_gridfs_3"}' -H "Content-Type: application/json" http://localhost:8080/predictions/dcgan_fashiongen -o img3.jpg
   

   Result image should be similar to the one below -