[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

setup.cfg

@@ -7,7 +7,7 @@ url = https://github.com/Hekstra-Lab/yeast-mcrnn
 author = Ian Hunt-Isaak, John Russell
 author_email = [email protected], [email protected]
 license = MIT
-license_file = LICENSE
+license_files = LICENSE
 platforms = Linux, Mac OS X, Windows
 classifiers =
     Intended Audience :: Developers
@@ -16,10 +16,6 @@ classifiers =
     Programming Language :: Python
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3 :: Only
-    Programming Language :: Python :: 3.6
-    Programming Language :: Python :: 3.7
-    Programming Language :: Python :: 3.8
-    Programming Language :: Python :: 3.9
     Programming Language :: Python :: Implementation :: CPython
 
 [options]
@@ -29,10 +25,10 @@ install_requires =
     fast-overlap
     numpy
     pandas
-    read_roi
+    read-roi
     tifffile
     torch
-python_requires = >=3.6
+python_requires = >=3.8
 
 [options.extras_require]
 test =

yeast_mrcnn/model.py

@@ -33,7 +33,7 @@ def mrcnn():
     )
 
     # Make anchor generator with 3 sizes per feature map and 5 aspect ratios
-    sizes = tuple(2.0 ** x for x in range(5, 12))
+    sizes = tuple(2.0**x for x in range(5, 12))
     aspects = tuple(0.5 * x for x in range(1, 5))
     n_feature_maps = 5  # true for resnet50 with FPN
     ag_sizes = tuple(tuple(sizes[i : i + 3]) for i in range(n_feature_maps))

yeast_mrcnn/train.py

@@ -15,7 +15,6 @@
 
 
 def train_one_epoch(model, dataloader, optimizer, epoch, device):
-
     loss_df = pd.DataFrame()
 
     lr_scheduler = None
@@ -70,7 +69,6 @@ def train(
     model.train()
 
     for e in range(epochs):
-
         loss_df = train_one_epoch(model, train_dataloader, optimizer, e, device)
 
         loss_df = loss_df.join(evaluate_test(model, val_dataloader, device))