def it_calculate_resampled_nparray_from_small_region_svs_image(self):
slide = Slide(SVS.CMU_1_SMALL_REGION,
os.path.join(SVS.CMU_1_SMALL_REGION, "processed"))
resampled_array = slide.resampled_array(scale_factor=32)
expected_value = load_expectation(
"svs-images/small-region-svs-resampled-array", type_="npy")
np.testing.assert_almost_equal(resampled_array, expected_value)
def it_knows_its_resampled_array(self, tmpdir, resampled_dims_):
tmp_path_ = tmpdir.mkdir("myslide")
image = PILIMG.RGBA_COLOR_500X500_155_249_240
image.save(os.path.join(tmp_path_, "mywsi.png"), "PNG")
slide_path = os.path.join(tmp_path_, "mywsi.png")
slide = Slide(slide_path, "processed")
resampled_dims_.return_value = (100, 200, 300, 400)
resampled_array = slide.resampled_array(scale_factor=32)
assert type(resampled_array) == np.ndarray
assert resampled_array.shape == (400, 300, 3)
# Inside the save_thumbnail
pil_img = pdx_slide._wsi.get_thumbnail(pdx_slide._thumbnail_size)
print(type(pil_img))
print(pil_img.size)
# pil_img.show() # why this doesn't work??
# plt.imshow(pil_img); plt.axis('off');
pil_img.save(tmp_outpath / 'pil_img.png', format='png')
# Apply mask to image
pil_img_boxed = histolab.util.apply_mask_image(
pil_img, pdx_slide.biggest_tissue_box_mask)
pil_img_boxed.save(tmp_outpath / 'pil_img_boxed.png', format='png')
# Scale and save image
scale_factor = 16
np_img_scaled = pdx_slide.resampled_array(
scale_factor=scale_factor) # scale and return ndarray
print(type(np_img_scaled))
print(np_img_scaled.shape)
# out image file path: {name}-{scale_factor}x-{large_w}x{large_h}-{new_w}x{new_h}.{IMG_EXT}
pdx_slide.save_scaled_image(
scale_factor=scale_factor) # scale and save into file
# Show img from array
# plt.imshow(img_scaled); plt.axis('off');
fig, ax = plt.subplots(figsize=(5, 5))
ax.imshow(np_img_scaled)
ax.axis('off')
# PIL.Image.fromarray(np_img_scaled)
# -----------------------------------
# Metadata
