In [3]:
%matplotlib inline
%load_ext autoreload
%autoreload 2
from webclient.image_ops import search as data
from webclient.image_ops import convert_images as ci
import matplotlib.pyplot as plt
In [6]:
parentCrop, labelMask = data.trainingsPatchForLabel(ImageLabel.objects.last())
In [7]:
type(parentCrop)
Out[7]:
In [9]:
plt.subplot(1,3,1)
plt.imshow(parentCrop)
plt.subplot(1,3,2)
plt.imshow(labelMask)
plt.subplot(1,3,3)
plt.imshow(parentCrop)
plt.hold
plt.imshow(labelMask*10+parentCrop[:,:,0])
Out[9]:
In [64]:
import numpy as np
In [ ]:
np.array()