optimize imports

src/hest/io/seg_readers.py

@@ -1,15 +1,13 @@
 from collections import defaultdict
-from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor, as_completed
+from concurrent.futures import ProcessPoolExecutor, as_completed
 import json
-import time
 import warnings
 from abc import abstractmethod
 
 import geopandas as gpd
 from loguru import logger
 import numpy as np
 import pandas as pd
-from matplotlib import pyplot as plt
 from shapely.geometry.polygon import Point, Polygon
 from tqdm import tqdm
 
@@ -240,6 +238,7 @@ def write_geojson(gdf: gpd.GeoDataFrame, path: str, category_key: str, extra_pro
 
 
 def generate_colors(names):
+    from matplotlib import pyplot as plt
     colors = plt.get_cmap('hsv', len(names))
     color_dict = {}
     for i in range(len(names)):

src/hest/readers.py

@@ -13,7 +13,6 @@
 from hestcore.segmentation import get_path_relative
 from loguru import logger
 
-from hest.autoalign import autoalign_visium
 from hest.custom_readers import ADT_to_adata, GSE144239_to_adata, colon_atlas_to_adata, heart_atlas_to_adata
 from hest.HESTData import (HESTData, STHESTData, VisiumHDHESTData,
                            VisiumHESTData, XeniumHESTData)
@@ -457,6 +456,7 @@ def read(self,
             if (not tissue_position_exists and alignment_file_path is None):
                 print('no tissue_positions_list.csv/tissue_positions.csv or alignment file found')
             print('attempt fiducial auto alignment...')
+            from hest.autoalign import autoalign_visium
 
             os.makedirs(os.path.join(os.path.dirname(img_path), 'spatial'), exist_ok=True)
             autoalign_save_dir = None

src/hest/segmentation/TissueMask.py

@@ -1,7 +1,6 @@
 import pickle
 from typing import List
 
-import cv2
 import numpy as np
 from PIL import Image
 
@@ -27,6 +26,8 @@ def load_tissue_mask(pkl_path: str, jpg_path: str, width: int, height: int) -> T
         with Image.open(jpg_path) as img:
             tissue_mask = np.array(img).copy()
 
+
+        import cv2
         tissue_mask = cv2.resize(tissue_mask, (width, height))
 
         mask = TissueMask(tissue_mask, contours_tissue, contours_holes)

src/hest/segmentation/cell_segmenters.py

@@ -2,17 +2,13 @@
 
 import os
 import sys
-import time
 import traceback
 import warnings
 from abc import abstractmethod
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from multiprocessing import Pool, cpu_count
-from time import sleep
+from concurrent.futures import ThreadPoolExecutor
 from typing import Tuple, Union
 
 import geopandas as gpd
-import matplotlib.pyplot as plt
 import numpy as np
 import openslide
 import pandas as pd
@@ -410,6 +406,7 @@ def expand_nuclei(gdf: gpd.GeoDataFrame, pixel_size: float, exp_um=5, plot=False
     gdf_cell.geometry = gdf_cell.union(gdf.loc[~invalid_mask])
 
     if plot:
+        import matplotlib.pyplot as plt
         logger.info('Plotting...')
         _, ax = plt.subplots(figsize=(50, 50))