add resize note

app.py

@@ -1,5 +1,6 @@
 from pathlib import Path
 
+import albumentations as A
 import gradio as gr
 import numpy as np
 import torch
@@ -19,8 +20,17 @@ def greet(input_image):
     with torch.no_grad():
         image = input_image
         image = np.array(image)
+        h, w = image.shape[:2]
+        if max(h, w) > 1024:
+            transform = A.LongestMaxSize(1024)
+        else:
+            transform = None
+
         dsm_image = torch.from_numpy(image).permute(2, 0, 1)
+
         image_size = image.shape[:2]
+        if transform is not None:
+            image = transform(image=image)["image"]
         image = img_to_tensor(
             image,
             normalize={"mean": IMAGENET_DEFAULT_MEAN, "std": IMAGENET_DEFAULT_STD},
@@ -36,6 +46,9 @@ def greet(input_image):
                 f"No manipulation found (manipulation probability {pred:.2f})."
             )
 
+        if transform is not None:
+            output_string += f"\nNote: Image was too large ({h}, {w}) and was resized to fit the model, which may decrease accuracy. We recommend image size smaller than 1024x1024."
+
         overlay = draw_segmentation_masks(
             dsm_image, masks=out_map[0, ...] > opt.mask_threshold
         )

requirements.txt

@@ -25,3 +25,4 @@ termcolor==2.4.0
 timm==0.9.12
 tqdm
 markupsafe==2.0.1
+gradio