problem about SSD model in ecosystem running with Google Colab

[I-M-Russell]

when running this part in SSD|PyTorch
inputs = [utils.prepare_input(uri) for uri in uris] tensor = utils.prepare_tensor(inputs, precision == 'fp16')
on Google Colab, it gives these error:
`---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
in ()
----> 1 inputs = [utils.prepare_input(uri) for uri in uris]
2 tensor = utils.prepare_tensor(inputs, precision == 'fp16')

2 frames
/root/.cache/torch/hub/NVIDIA_DeepLearningExamples_torchhub/hubconf.py in load_image(image_path)
235 def load_image(image_path):
236 """Code from Loading_Pretrained_Models.ipynb - a Caffe2 tutorial"""
--> 237 img = skimage.img_as_float(skimage.io.imread(image_path))
238 if len(img.shape) == 2:
239 img = np.array([img, img, img]).swapaxes(0, 2)

AttributeError: module 'skimage' has no attribute 'io'`
How do I solve it?

[bilalsal]

The following fix to nvidia_ssd_processing_utils in NVIDIA_DeepLearningExamples_torchhub/hubconf.py worked for me in Python 3 (see PR NVIDIA/DeepLearningExamples#418)

def nvidia_ssd_processing_utils():
import numpy as np
import skimage
from skimage import io, transform
from PyTorch.Detection.SSD.src.utils import dboxes300_coco, Encoder

class Processing:
    @staticmethod
    def load_image(image_path):
        """Code from Loading_Pretrained_Models.ipynb - a Caffe2 tutorial"""
        img = skimage.img_as_float(io.imread(image_path))
        if len(img.shape) == 2:
            img = np.array([img, img, img]).swapaxes(0, 2)
        return img

    @staticmethod
    def rescale(img, input_height, input_width):
        """Code from Loading_Pretrained_Models.ipynb - a Caffe2 tutorial"""
        aspect = img.shape[1] / float(img.shape[0])
        if (aspect > 1):
            # landscape orientation - wide image
            res = int(aspect * input_height)
            imgScaled = transform.resize(img, (input_width, res))
        if (aspect < 1):
            # portrait orientation - tall image
            res = int(input_width / aspect)
            imgScaled = transform.resize(img, (res, input_height))
        if (aspect == 1):
            imgScaled = transform.resize(img, (input_width, input_height))
        return imgScaled

[skierat]

@I-M-Russell does the fix work you? Can we close the issue

[ailzhang]

Closing as I confirmed this works in Colab now. Thanks!