name: VGG models on ImageNet SINGA version: 1.1.1 SINGA commit: license: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py¶
Image Classification using VGG¶
In this example, we convert VGG on PyTorch to SINGA for image classification.
Instructions¶
Download one parameter checkpoint file (see below) and the synset word file of ImageNet into this folder, e.g.,
$ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/vgg/vgg11.tar.gz $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/resnet/synset_words.txt $ tar xvf vgg11.tar.gz
Usage
$ python serve.py -h
Example
# use cpu $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 --use_cpu & # use gpu $ python serve.py --use_cpu --parameter_file vgg11.pickle --depth 11 &
The parameter files for the following model and depth configuration pairs are provided:
Submit images for classification
$ curl -i -F image=@image1.jpg http://localhost:9999/api $ curl -i -F image=@image2.jpg http://localhost:9999/api $ curl -i -F image=@image3.jpg http://localhost:9999/api
image1.jpg, image2.jpg and image3.jpg should be downloaded before executing the above commands.
Details¶
The parameter files were converted from the pytorch via the convert.py program.
Usage:
$ python convert.py -h