コード例 #1
0
def test_imagepalette():
    im = hopper("P")
    im.putpalette(ImagePalette.negative())
    assert_image_equal_tofile(im.convert("RGB"), "Tests/images/palette_negative.png")

    im.putpalette(ImagePalette.random())

    im.putpalette(ImagePalette.sepia())
    assert_image_equal_tofile(im.convert("RGB"), "Tests/images/palette_sepia.png")

    im.putpalette(ImagePalette.wedge())
    assert_image_equal_tofile(im.convert("RGB"), "Tests/images/palette_wedge.png")
コード例 #2
0
 def test_imagepalette(self):
     im = hopper("P")
     im.putpalette(ImagePalette.negative())
     im.putpalette(ImagePalette.random())
     im.putpalette(ImagePalette.sepia())
     im.putpalette(ImagePalette.wedge())
コード例 #3
0
def test_imagepalette():
    im = lena("P")
    assert_no_exception(lambda: im.putpalette(ImagePalette.negative()))
    assert_no_exception(lambda: im.putpalette(ImagePalette.random()))
    assert_no_exception(lambda: im.putpalette(ImagePalette.sepia()))
    assert_no_exception(lambda: im.putpalette(ImagePalette.wedge()))
コード例 #4
0
import os
#os.environ['CUDA_HOME'] = '/opt/anaconda3/lib/python3.6/site-packages/torch/cuda'

from torch.nn import functional as F
from torchvision.transforms import ToTensor, Normalize, Compose
import torch
print(torch.cuda.is_available())

import cv2
import random
from pathlib import Path

# In[3]:

random.seed(42)
NUCLEI_PALETTE = ImagePalette.random()
random.seed()

# In[4]:

rcParams['figure.figsize'] = 15, 15

# In[5]:

from models.ternausnet2 import TernausNetV2
# print('...')

# In[6]:


def get_model(model_path):
コード例 #5
0
 def test_imagepalette(self):
     im = lena("P")
     im.putpalette(ImagePalette.negative())
     im.putpalette(ImagePalette.random())
     im.putpalette(ImagePalette.sepia())
     im.putpalette(ImagePalette.wedge())