def display_image(np_rgb, text=None, scale_up=False):
"""
Display an image with optional text above image.
Args:
np_rgb: RGB image tile as a NumPy array
text: Optional text to display above image
scale_up: If True, scale up image to display by slide.SCALE_FACTOR
"""
if scale_up:
np_rgb = np.repeat(np_rgb, slide.SCALE_FACTOR, axis=1)
np_rgb = np.repeat(np_rgb, slide.SCALE_FACTOR, axis=0)
img_r, img_c, img_ch = np_rgb.shape
if text is not None:
np_t = np_text(text)
t_r, t_c, _ = np_t.shape
t_i_c = max(t_c, img_c)
t_i_r = t_r + img_r
t_i = np.zeros([t_i_r, t_i_c, img_ch], dtype=np.uint8)
t_i.fill(255)
t_i[0:t_r, 0:t_c] = np_t
t_i[t_r:t_r + img_r, 0:img_c] = np_rgb
np_rgb = t_i
pil_img = util.np_to_pil(np_rgb)
pil_img.show()
def create_summary_pil_img(np_img, title_area_height, row_tile_size,
col_tile_size, num_row_tiles, num_col_tiles):
"""
Create a PIL summary image including top title area and right side and bottom padding.
Args:
np_img: Image as a NumPy array.
title_area_height: Height of the title area at the top of the summary image.
row_tile_size: The tile size in rows.
col_tile_size: The tile size in columns.
num_row_tiles: The number of row tiles.
num_col_tiles: The number of column tiles.
Returns:
Summary image as a PIL image. This image contains the image data specified by the np_img input and also has
potentially a top title area and right side and bottom padding.
"""
r = row_tile_size * num_row_tiles + title_area_height
c = col_tile_size * num_col_tiles
summary_img = np.zeros([r, c, np_img.shape[2]], dtype=np.uint8)
# add gray edges so that tile text does not get cut off
summary_img.fill(120)
# color title area white
summary_img[0:title_area_height, 0:summary_img.shape[1]].fill(255)
summary_img[title_area_height:np_img.shape[0] + title_area_height,
0:np_img.shape[1]] = np_img
summary = util.np_to_pil(summary_img)
return summary
def apply_filters_to_image(slide_name, save=True, display=False):
"""
Apply a set of filters to an image and optionally save and/or display filtered images.
Args:
slide_name: The slide name.
save: If True, save filtered images.
display: If True, display filtered images to screen.
Returns:
Tuple consisting of 1) the resulting filtered image as a NumPy array, and 2) dictionary of image information
(used for HTML page generation).
"""
t = Time()
print(f"Processing slide {slide_name}")
info = dict()
if save and not os.path.exists(slide.FILTER_DIR):
os.makedirs(slide.FILTER_DIR)
np_orig = slide.get_slide(slide_name)
filtered_np_img = apply_image_filters(np_orig,
slide_name,
info,
save=False,
display=False)
if save:
result_path = slide.get_filter_image_result(slide_name)
pil_img = util.np_to_pil(filtered_np_img)
pil_img.save(result_path)
return filtered_np_img, info
def add_tile_stats_to_top_tile_summary(pil_img, tiles, z):
np_sum = util.pil_to_np_rgb(pil_img)
sum_r, sum_c, sum_ch = np_sum.shape
np_stats = np_tile_stat_img(tiles)
st_r, st_c, _ = np_stats.shape
combo_c = sum_c + st_c
combo_r = max(sum_r, st_r + z)
combo = np.zeros([combo_r, combo_c, sum_ch], dtype=np.uint8)
combo.fill(255)
combo[0:sum_r, 0:sum_c] = np_sum
combo[z:st_r + z, sum_c:sum_c + st_c] = np_stats
result = util.np_to_pil(combo)
return result
def pil_hue_histogram(h):
"""
Create Matplotlib histogram of hue values for an HSV image and return the histogram as a PIL image.
Args:
h: Hue values as a 1-dimensional int NumPy array (scaled 0 to 360)
Returns:
Matplotlib histogram of hue values converted to a PIL image.
"""
np_hist = np_hsv_hue_histogram(h)
pil_hist = util.np_to_pil(np_hist)
return pil_hist
def save_filtered_image(np_img, slide_name, filter_num, filter_text):
"""
Save a filtered image to the file system.
Args:
np_img: Image as a NumPy array.
slide_name: The slide number.
filter_num: The filter number.
filter_text: Descriptive text to add to the image filename.
"""
t = Time()
filepath = slide.get_filter_image_path(slide_name, filter_num, filter_text)
pil_img = util.np_to_pil(np_img)
pil_img.save(filepath)
print("%-20s | Time: %-14s Name: %s" %
("Save Image", str(t.elapsed()), filepath))
def get_pil_scaled_tile(self):
return util.np_to_pil(self.np_scaled_tile)