Speed up Gradio image previews

app.py

@@ -3,6 +3,7 @@ import zipfile
 from pathlib import Path
 from uuid import uuid4
 
+import cv2
 import gradio as gr
 
 from cleaning import (
@@ -13,8 +14,9 @@ from cleaning import (
 )
 
 _BATCH_OUTPUTS = tempfile.TemporaryDirectory(prefix="ihc-cleaner-")
-_EXAMPLE_IMAGES = [["data/dirty.png"], ["data/dirty.tiff"]]
+_EXAMPLE_IMAGES = [["data/dirty_example.png"]]
 _IMAGE_FILE_TYPES = ["image", ".tif", ".tiff"]
+_PREVIEW_MAX_DIMENSION = 1200
 
 
 def _uploaded_path(file_path: str | Path | None) -> Path:
@@ -24,11 +26,23 @@ def _uploaded_path(file_path: str | Path | None) -> Path:
     return Path(file_path)
 
 
+def _preview_image(image):
+    height, width = image.shape[:2]
+    largest_dimension = max(height, width)
+
+    if largest_dimension <= _PREVIEW_MAX_DIMENSION:
+        return image
+
+    scale = _PREVIEW_MAX_DIMENSION / largest_dimension
+    preview_size = (round(width * scale), round(height * scale))
+    return cv2.resize(image, preview_size, interpolation=cv2.INTER_AREA)
+
+
 def preview_image(file_path: str | Path | None):
     if not file_path:
         return None, None, None
 
-    return read_image_rgb(file_path), None, None
+    return _preview_image(read_image_rgb(file_path)), None, None
 
 
 def clean_uploaded_image(file_path: str | Path | None):
@@ -41,7 +55,7 @@ def clean_uploaded_image(file_path: str | Path | None):
     cleaned_path = output_dir / cleaned_image_name(image_path)
     write_image_rgb(cleaned_path, cleaned_rgb)
 
-    return image_rgb, cleaned_rgb, str(cleaned_path)
+    return _preview_image(image_rgb), _preview_image(cleaned_rgb), str(cleaned_path)
 
 
 def clean_directory(image_paths: list[str] | None) -> tuple[str, str]: