Update readme

README.md

@@ -14,8 +14,8 @@ We find labels with a custom trained YOLOv7 model (https://github.com/WongKinYiu
 Local scripts:
 - `fix-herbarium-sheet-names`: I had a problem where herbarium sheet file names were given as URLs and it confused the Pillow (PIL) module so I renamed the files to remove problem characters. You may not need this script.
 - `yolo-training`: If you are training your own YOLO7 model then you may want to use this script to prepare the images of herbarium sheets for training. The herbarim images may be in all sorts of sizes, and model training requires that they're all uniformly sized.
-  - This script also requires a CSV file containing the paths to the herbarium sheets and the class and location of the labels on that sheet.
-- `yolo-inference`: Prepare herbarium sheet image for inference; i.e. finding labels. The images must be in the same size the training data.
+  - YOLO scripts also requires a CSV file containing the paths to the herbarium sheets and the class and location of the labels on that sheet.
+- `yolo-inference`: Prepare herbarium sheet images for inference; i.e. finding labels. The images must be in the same size the training data.
 - `yolo-results-to-labels`: This takes for output of the YOLO model and creates label images. The label name contains information about the YOLO results. The label name format:
   - `<sheet name>_<label class>_<left pixel>_<top pixel>_<right pixel>_<bottom pixel>.jpg`
   - For example: `my-herbarium-sheet_typewritten_2261_3580_3397_4611.jpg`

finder/pylib/sheet_util.py

@@ -22,21 +22,25 @@ def to_yolo_image(path, yolo_images, yolo_size) -> tuple[int, int] | None:
     try:
         resized = image.resize((yolo_size, yolo_size))
         resized.save(yolo)
-        return image.size
 
     except IMAGE_EXCEPTIONS as err:
-        logging.error(f"Could not prepare {path.name}: {err}")
+        msg = f"Could not prepare {path.name}: {err}"
+        logging.exception(msg)
         return None
 
+    return image.size
+
 
 def sheet_image(path):
     with warnings.catch_warnings():
         warnings.filterwarnings("ignore", category=UserWarning)  # No EXIF warnings
 
         try:
             image = Image.open(path).convert("RGB")
-            return image
 
         except IMAGE_EXCEPTIONS as err:
-            logging.error(f"Could not prepare {path.name}: {err}")
+            msg = f"Could not prepare {path.name}: {err}"
+            logging.exception(msg)
             return None
+
+        return image

pyproject.toml

@@ -52,7 +52,7 @@ target-version = "py311"
 
 show-fixes = true
 
-select = [
+lint.select = [
     "F",
     "E",
     "W",
@@ -105,7 +105,7 @@ select = [
     "RUF",
 ]
 
-ignore = [
+lint.ignore = [
     "COM812",  # Trailing comma missing
     "D100",  # Missing docstring in public module
     "D101",  # Missing docstring in public class