Unnecessary dependency on VOC dataset for model in Model Zoo

[thomelane]

When trying out fcn_resnet50_voc after a fresh install of Gluon CV you get the error detailed below, where it appears that the VOC dataset is required. Given it's common to only want to use the model and not download the whole dataset, a different check should be used here.

After downloading the VOC dataset with python pascal_voc.py as found here, I was able to use the model from the Model Zoo, but this shouldn't be required.

model = gluoncv.model_zoo.get_model('fcn_resnet50_voc', pretrained=True)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/model_zoo/model_zoo.py in get_model(name, **kwargs)
     54     try:
---> 55         net = gluon.model_zoo.vision.get_model(name, **kwargs)
     56     except ValueError as e:

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/mxnet/gluon/model_zoo/vision/__init__.py in get_model(name, **kwargs)
    150             'Model %s is not supported. Available options are\n\t%s' % (
--> 151                 name, '\n\t'.join(sorted(models.keys()))))
    152     return models[name](**kwargs)

ValueError: Model fcn_resnet50_voc is not supported. Available options are
    alexnet
    densenet121
    densenet161
    densenet169
    densenet201
    inceptionv3
    mobilenet0.25
    mobilenet0.5
    mobilenet0.75
    mobilenet1.0
    mobilenetv2_0.25
    mobilenetv2_0.5
    mobilenetv2_0.75
    mobilenetv2_1.0
    resnet101_v1
    resnet101_v2
    resnet152_v1
    resnet152_v2
    resnet18_v1
    resnet18_v2
    resnet34_v1
    resnet34_v2
    resnet50_v1
    resnet50_v2
    squeezenet1.0
    squeezenet1.1
    vgg11
    vgg11_bn
    vgg13
    vgg13_bn
    vgg16
    vgg16_bn
    vgg19
    vgg19_bn

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
<ipython-input-4-9baa5158fc03> in <module>()
----> 1 model = gluoncv.model_zoo.get_model('fcn_resnet50_voc', pretrained=True)

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/model_zoo/model_zoo.py in get_model(name, **kwargs)
     58         if name not in models:
     59             raise ValueError('%s\n\t%s' % (str(e), '\n\t'.join(sorted(models.keys()))))
---> 60         net = models[name](**kwargs)
     61     return net

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/model_zoo/fcn.py in get_fcn_voc_resnet50(**kwargs)
    140     >>> print(model)
    141     """
--> 142     return get_fcn('pascal_voc', 'resnet50', **kwargs)
    143 
    144 def get_fcn_voc_resnet101(**kwargs):

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/model_zoo/fcn.py in get_fcn(dataset, backbone, pretrained, root, ctx, **kwargs)
    113     # infer number of classes
    114     from ..data.segbase import get_segmentation_dataset
--> 115     data = get_segmentation_dataset(dataset)
    116     model = FCN(data.num_class, backbone=backbone, **kwargs)
    117     if pretrained:

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/data/segbase.py in get_segmentation_dataset(name, **kwargs)
     19         'pascal_aug': VOCAugSegmentation,
     20     }
---> 21     return datasets[name](**kwargs)
     22 
     23 

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/data/pascal_voc/segmentation.py in __init__(self, root, split, transform)
     35     def __init__(self, root=os.path.expanduser('~/.mxnet/datasets/voc'),
     36                  split='train', transform=None):
---> 37         super(VOCSegmentation, self).__init__(root)
     38         self.root = root
     39         _voc_root = os.path.join(self.root, self.BASE_DIR)

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/data/segbase.py in __init__(self, root, base_size, crop_size)
     37     # pylint: disable=abstract-method
     38     def __init__(self, root, base_size=520, crop_size=480):
---> 39         super(SegmentationDataset, self).__init__(root)
     40         self.base_size = base_size
     41         self.crop_size = crop_size

~/anaconda3/envs/mxnet_p36/lib/python3.6/site-packages/gluoncv/data/base.py in __init__(self, root)
     26                          datasets described in `gluon-cv/scripts/datasets`? You need \
     27                          to initialize each dataset only once.".format(root)
---> 28             raise OSError(helper_msg)
     29 
     30     @property

OSError: /home/ubuntu/.mxnet/datasets/voc is not a valid dir. Did you forget to initalize                          datasets described in `gluon-cv/scripts/datasets`? You need                          to initialize each dataset only once.

[zhanghang1989]

This has been fixed in master branch https://github.com/dmlc/gluon-cv/blob/master/gluoncv/model_zoo/fcn.py#L121

[zhanghang1989]

Closing it, since it has been fixed in master branch.