Factor some code for library use.

mapped_downscale.py

@@ -227,14 +227,56 @@ def downsample_all(*, input_image: Image.Image, output_image: Optional[ImageRef]
 def str2bool(value) -> bool:
     if isinstance(value, bool):
        return value
-    if value.lower() in ("yes", "true", "t", "y", "1"):
+    if value.lower() in ("true", "1"):
         return True
-    elif value.lower() in ("no", "false", "f", "n", "0"):
+    elif value.lower() in ("false", "0"):
         return False
     else:
         raise argparse.ArgumentTypeError("Boolean value expected.")
 
 
+def mapped_downscale(*, control_path: str, input_path: str, output_up_path: Optional[str], output_down_path: Optional[str], sample_radius: Optional[int], downsampler: Image.Resampling, trim_cropped_edges: bool) -> None:
+    """
+    Downsample and rescale an image.
+    
+    :param control_path: Path to the control image.
+    :param input_path: Path to the input image.
+    :param output_up_path: Path to save the output image, upscaled to the original size.
+    :param output_down_path: Path to save the output image, kept at the downsampled size.
+    :param sample_radius: Radius for sampling (Manhattan distance).
+    :param downsampler: Downsampler to use.
+    :param trim_cropped_edges: Drop mapped checker grid elements that are cropped in the control image.
+    """
+    control_image = Image.open(control_path).convert("1")
+    input_image = Image.open(input_path)
+    if control_image.size != input_image.size:
+        raise ValueError("Control image and input image must have the same dimensions.")
+    
+    output_image: Optional[ImageRef] = None
+    down_image: Optional[ImageRef] = None
+    
+    if not output_up_path and not output_down_path:
+        raise ValueError("At least one of output_up and output_down must be specified.")
+    
+    if output_up_path:
+        output_image = ImageRef(Image.new("RGB", input_image.size))
+
+    extracted_boxes = extract_boxes(control_image)
+    
+    if output_down_path:
+        down_image = ImageRef(Image.new("RGB", extracted_boxes.down_dimensions()))
+        
+    boxes = extracted_boxes.boxes()
+    downsample_all(input_image=input_image, output_image=output_image, down_image=down_image, boxes=boxes, sample_radius=sample_radius, downsampler=downsampler, trim_cropped_edges=trim_cropped_edges)
+    
+    if output_image:
+        assert output_up_path
+        output_image.ref.save(output_up_path)
+    if down_image:
+        assert output_down_path
+        down_image.ref.save(output_down_path)
+
+
 def main(cli_args: List[str]) -> None:
     parser = argparse.ArgumentParser(description="Downsample and rescale image.")
     parser.add_argument("--control", required=True, help="Path to control image.")
@@ -246,31 +288,17 @@ def main(cli_args: List[str]) -> None:
     parser.add_argument("--trim-cropped-edges", type=str2bool, default=False, help="Drop mapped checker grid elements that are cropped in the control image.")
 
     args = parser.parse_args(cli_args)
-
-    control_image = Image.open(args.control).convert("1")
-    input_image = Image.open(args.input)
-    if control_image.size != input_image.size:
-        raise ValueError("Control image and input image must have the same dimensions.")
     downsampler = Image.Resampling[args.downsampler.upper()]
-    output_image: Optional[ImageRef] = None
-    down_image: Optional[ImageRef] = None
-    if not args.output_up and not args.output_down:
-        raise ValueError("At least one of --output-up and --output-down must be specified.")
-    if args.output_up:
-        output_image = ImageRef(Image.new("RGB", input_image.size))
-    extracted_boxes = extract_boxes(control_image)
-    if args.output_down:
-        down_image = ImageRef(Image.new("RGB", extracted_boxes.down_dimensions()))
-
-    boxes = extracted_boxes.boxes()
-
-    print(args.trim_cropped_edges)
-
-    downsample_all(input_image=input_image, output_image=output_image, down_image=down_image, boxes=boxes, sample_radius=args.sample_radius, downsampler=downsampler, trim_cropped_edges=args.trim_cropped_edges)
-    if output_image:
-        output_image.ref.save(args.output_up)
-    if down_image:
-        down_image.ref.save(args.output_down)
+    
+    mapped_downscale(
+        control_path=args.control,
+        input_path=args.input,
+        output_up_path=args.output_up,
+        output_down_path=args.output_down,
+        sample_radius=args.sample_radius,
+        downsampler=downsampler,
+        trim_cropped_edges=args.trim_cropped_edges
+    )
 
 
 if __name__ == "__main__":