Solved: 2 tests for gradio app launch failed on windows + investigation of pytest warnings

qim3d/tests/gui/test_annotation_tool.py

@@ -9,14 +9,15 @@ def test_starting_class():
     assert app.title == "Annotation tool"
 
 
-def test_app_launch():
-    ip = "0.0.0.0"
-    port = 65432
-
 def start_server(ip, port):
     app = qim3d.gui.annotation_tool.Interface()
     app.launch(server_name=ip, server_port=port)
 
+
+def test_app_launch():
+    ip = "localhost"
+    port = 65432
+
     proc = multiprocessing.Process(target=start_server, args=(ip, port))
     proc.start()
 

qim3d/tests/gui/test_iso3d.py

@@ -9,14 +9,15 @@ def test_starting_class():
     assert app.title == "Isosurfaces for 3D visualization"
 
 
-def test_app_launch():
-    ip = "0.0.0.0"
-    port = 65432
-
 def start_server(ip, port):
     app = qim3d.gui.iso3d.Interface()
     app.launch(server_name=ip, server_port=port)
 
+
+def test_app_launch():
+    ip = "localhost"
+    port = 65432
+
     proc = multiprocessing.Process(target=start_server, args=(ip, port))
     proc.start()
 

qim3d/utils/internal_tools.py

@@ -6,7 +6,6 @@ import outputformat as ouf
 import matplotlib.pyplot as plt
 import matplotlib
 import numpy as np
-import socket
 import os
 import shutil
 import requests

qim3d/viz/img.py

 """ Provides a collection of visualization functions."""
 import matplotlib.pyplot as plt
 from matplotlib.colors import LinearSegmentedColormap
-from matplotlib import cm
+from matplotlib import colormaps
 import torch
 import numpy as np
 from qim3d.io.logger import log
@@ -56,7 +56,7 @@ def grid_overview(data, num_images=7, cmap_im="gray", cmap_segm="viridis", alpha
         num_images = len(data)
 
     # Adapt segmentation cmap so that background is transparent
-    colors_segm = cm.get_cmap(cmap_segm)(np.linspace(0, 1, 256))
+    colors_segm = colormaps.get_cmap(cmap_segm)(np.linspace(0, 1, 256))
     colors_segm[:128, 3] = 0
     custom_cmap = LinearSegmentedColormap.from_list("CustomCmap", colors_segm)
 
@@ -142,7 +142,7 @@ def grid_pred(in_targ_preds, num_images=7, cmap_im="gray", cmap_segm="viridis",
     inputs,targets,preds = [items[:num_images] for items in in_targ_preds]
     
     # Adapt segmentation cmap so that background is transparent
-    colors_segm = cm.get_cmap(cmap_segm)(np.linspace(0, 1, 256))
+    colors_segm = colormaps.get_cmap(cmap_segm)(np.linspace(0, 1, 256))
     colors_segm[:128, 3] = 0
     custom_cmap = LinearSegmentedColormap.from_list("CustomCmap", colors_segm)