Update superdsm.io module

.github/workflows/validate_pr.yml

@@ -20,12 +20,14 @@ jobs:
   validate_conditional_checks:
     name: Validate conditional checks
     runs-on: ubuntu-latest
+    timeout-minutes: 1440
 
     steps:
 
       - uses: blend/[email protected]
         with:
           interval: 20s
+          timeout: 1440m
           checks-yaml: |
             - job: 'Test: U2OS'
               paths:

superdsm/batch.py

@@ -2,7 +2,7 @@
 from .objects import _compute_objects
 from ._aux import mkdir, is_subpath, copy_dict
 from .output import get_output, Text
-from .io import imread, imwrite
+from .io import imread, imsave
 from .render import rasterize_labels, render_ymap, render_atoms, render_adjacencies, render_result_over_image
 from .automation import create_config
 from .config import Config
@@ -74,7 +74,7 @@ def write_adjacencies_image(name, data):
             ymap = render_ymap(data)
             ymap = render_atoms(data, override_img=ymap, border_color=(0,0,0), border_radius=1)
             img  = render_adjacencies(data, override_img=ymap, edge_color=(0,1,0), endpoint_color=(0,1,0))
-            imwrite(adj_filepath, img)
+            imsave(adj_filepath, img)
 
     atomic_stage = pipeline.stages[pipeline.find('c2f-region-analysis')]
     atomic_stage.add_callback('end', write_adjacencies_image)
@@ -86,12 +86,12 @@ def write_adjacencies_image(name, data):
         if seg_border is None: seg_border = 8
         img_overlay = render_result_over_image(result_data, border_width=seg_border)
         mkdir(pathlib.Path(overlay_filepath).parents[0])
-        imwrite(overlay_filepath, img_overlay)
+        imsave(overlay_filepath, img_overlay)
 
     if seg_filepath is not None:
         seg_result = rasterize_labels(result_data, **rasterize_kwargs)
         mkdir(pathlib.Path(seg_filepath).parents[0])
-        imwrite(seg_filepath, seg_result)
+        imsave(seg_filepath, seg_result)
 
     return result_data, timings
 

superdsm/export.py

@@ -1,7 +1,7 @@
 from .render import colorize_labels, normalize_image, render_ymap, render_result_over_image, render_atoms, render_adjacencies
 from .batch import Task, _resolve_timings_key
 from .output import get_output
-from .io import imread, imwrite
+from .io import imread, imsave
 
 import numpy as np
 import gzip, dill, pathlib
@@ -93,7 +93,7 @@
             img = imread(im_filepath)
             if args.enhance: img = normalize_image(img)
             outputfile.parents[0].mkdir(parents=True, exist_ok=True)
-            imwrite(str(outputfile), img)
+            imsave(str(outputfile), img)
     elif args.mode in ('seg', 'fgc', 'adj', 'atm'):
         if args.mode in ('fgc', 'adj', 'atm'):
             task.last_stage = 'c2f-region-analysis'
@@ -105,7 +105,7 @@
             ymap_legend = np.vstack([ymap_legend] * 10)
             ymap_legendfile = outdir / f'ymap_legend.png'
             out.write(f'\nWriting legend: {ymap_legendfile}')
-            imwrite(str(ymap_legendfile), ymap_legend)
+            imsave(str(ymap_legendfile), ymap_legend)
         data = task.run(one_shot=True, force=True, evaluation='none', out=out)
         out.write('\nRunning export:')
         for image_id in task.file_ids:
@@ -124,7 +124,7 @@
                 img  = render_adjacencies(dataframe, override_img=ymap, edge_color=(0,1,0), endpoint_color=(0,1,0))
             elif args.mode == 'atm':
                 img = render_atoms(dataframe, border_color=(0,1,0), border_radius=border_width // 2, normalize_img=args.enhance)
-            imwrite(str(outputfile), img)
+            imsave(str(outputfile), img)
             out.write(f'  Exported {outputfile}')
         out.write('\n')
     out.write(f'Exported {len(task.file_ids)} files')

superdsm/io.py

@@ -2,8 +2,9 @@
 import os, warnings
 
 
-def imwrite(filepath, img, shape=None, antialias=False):
-    """Writes an image to a file.
+def imsave(filepath, img, shape=None, antialias=False):
+    """
+    Writes an image to a file.
 
     :param filepath: The path of the file to be written.
     :param img: A ``numpy.ndarray`` object corresponding to the image data.
@@ -32,23 +33,40 @@ def imwrite(filepath, img, shape=None, antialias=False):
         skimage.io.imsave(filepath, img)
 
 
-def imread(filepath, **kwargs):
-    """Loads an image from file.
+def imread(filepath, force_filetype=None, **kwargs):
+    """
+    Loads an image from file.
 
     Supported file extensions are PNG, TIF, and TIFF.
+
+    :param force_filetype: Pretend that the file has a specific extension.
     """
+
+    if force_filetype is not None:
+        force_filetype = force_filetype.lower()
+        assert force_filetype in ('png', 'tif', 'tiff')
+        filetype = force_filetype
+
+    else:
+        filepath_parts = str(filepath).split('.')
+        assert len(filepath_parts) >= 2, f'Failed to determine file extension: {filepath}'
+        filetype = filepath_parts[-1].lower()
+
     filepath = os.path.expanduser(filepath)
     if not os.path.exists(filepath) or not os.path.isfile(filepath):
-        raise ValueError('not a file: %s' % filepath)
-    fp_lowercase = filepath.lower()
-    if 'as_gray' not in kwargs: kwargs['as_gray'] = True
-    if fp_lowercase.endswith('.png'):
+        raise ValueError(f'Not a file: {filepath}')
+
+    if 'as_gray' not in kwargs:
+        kwargs['as_gray'] = True
+
+    if filetype == 'png':
         img = skimage.io.imread(filepath, **kwargs)
-    elif fp_lowercase.endswith('.tif') or fp_lowercase.endswith('.tiff'):
+
+    elif filetype in ('tif', 'tiff'):
         with warnings.catch_warnings():
             warnings.filterwarnings('ignore', category=RuntimeWarning)
             img = skimage.io.imread(filepath, plugin='tifffile', **kwargs)
+
     else:
-        raise ValueError('unknown file extension: %s' % filepath)
+        raise ValueError(f'Unknown file extension: {filepath}')
     return img
-

tests/testsuite.py

@@ -66,7 +66,7 @@ def validate_image(test, name, img):
     except:
         actual_path = root_dir / 'actual' / name
         actual_path.parent.mkdir(parents=True, exist_ok=True)
-        superdsm.io.imwrite(str(actual_path), img)
+        superdsm.io.imsave(str(actual_path), img)
         raise