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Merge pull request #418 from bilalsal/patch-1

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Fix skimage import issue, for NVIDIA's PyTorch SSD
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skierat 2020-03-13 12:03:16 +01:00 committed by GitHub
parent e0b6d222b4 8e3ef240b8
commit db408837c2
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1 changed files with 6 additions and 4 deletions
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10
hubconf.py
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@ -228,13 +228,15 @@ def nvidia_waveglow(pretrained=True, **kwargs):
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(skimage.io.imread(image_path))
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
@ -246,13 +248,13 @@ def nvidia_ssd_processing_utils():
if (aspect > 1):
# landscape orientation - wide image
res = int(aspect * input_height)
imgScaled = skimage.transform.resize(img, (input_width, res))
imgScaled = transform.resize(img, (input_width, res))
if (aspect < 1):
# portrait orientation - tall image
res = int(input_width / aspect)
imgScaled = skimage.transform.resize(img, (res, input_height))
imgScaled = transform.resize(img, (res, input_height))
if (aspect == 1):
imgScaled = skimage.transform.resize(img, (input_width, input_height))
imgScaled = transform.resize(img, (input_width, input_height))
return imgScaled
@staticmethod