GluonCV Model Zoo

GluonCV Model Zoo provides pre-defined and pre-trained models to help bootstrap computer vision applications.

Available Models

Please visit pages for tasks:

GluonCV is still under development, stay tuned for more models!

Model Zoo API

from gluoncv import model_zoo
# load a ResNet model trained on CIFAR10
cifar_resnet20 = model_zoo.get_model('cifar_resnet20_v1', pretrained=True)
# load a pre-trained ssd model
ssd0 = model_zoo.get_model('ssd_300_vgg16_atrous_voc', pretrained=True)
# load ssd model with pre-trained feature extractors
ssd1 = model_zoo.get_model('ssd_512_vgg16_atrous_voc', pretrained_base=True)
# load ssd model without initialization
ssd2 = model_zoo.get_model('ssd_512_resnet50_v1_voc', pretrained_base=False)

We recommend using gluoncv.model_zoo.get_model() for loading pre-defined models, because it provides name checking and lists available choices.

However, you can still load models by directly instantiate it like

from gluoncv import model_zoo
cifar_resnet20 = model_zoo.cifar_resnet20_v1(pretrained=True)


Detailed model_zoo APIs are available in API reference: gluoncv.model_zoo().