from __future__ import print_function
import cv2
import numpy as np
import sys
from matplotlib import pyplot as plt
from svsutils import Slide
s = Slide(
slide_path=
'/home/nathan/data/ccrcc/TCGA_KIRC/TCGA-A3-3346-01Z-00-DX1.95280216-fd71-4a03-b452-6e3d667f2542.svs',
process_mag=5,
process_size=512,
oversample_factor=1.25)
s.initialize_output(n_classes=3)
s.print_info()
for idx, img in enumerate(s.generator()):
s.place(img[:, :, ::-1], idx)
reconstruction = s.output_img
print(reconstruction.shape)
plt.imshow(reconstruction)
plt.show()
def feature_fn(img):
r, g, b = np.split(img, 3, axis=2)
output = np.asarray([np.mean(r), np.mean(g), np.mean(b)])
return np.expand_dims(output, axis=0)
with tf.Session(config=config) as sess:
ds = tf.data.Dataset.from_generator(generator=svs.generate_index,
output_types=tf.int64)
ds = ds.map(read_region_at_index, num_parallel_calls=4)
ds = ds.prefetch(512)
iterator = ds.make_one_shot_iterator()
img, idx = iterator.get_next()
print('Starting')
tstart = time.time()
while True:
try:
img_, idx_ = sess.run([img, idx])
features = feature_fn(img_)
svs.place(features, idx_, name='features', mode='tile')
except tf.errors.OutOfRangeError:
print('End')
break
print('Finished in {}s'.format(time.time() - tstart))
img_out = svs.output_imgs['features']
cv2.imwrite('test_tile_reconstruction.jpg', img_out * (255. / img_out.max()))