Update app.py

app.py

@@ -44,9 +44,9 @@ st.write(
 st.text("Upload an image. Then click on the Run OCR button.")
 
 # -----------------------
-# Hardcoded configuration (from your notebook)
+# Hardcoded configuration (your notebook params)
 # -----------------------
-INFERENCE_HOST_ADDRESS = "@cloud"          # <- changed from @local to @cloud
+INFERENCE_HOST_ADDRESS = "@cloud"          # <-- changed from @local to @cloud
 ZOO_URL = "degirum/hailo"
 DEVICE_TYPE = ["HAILORT/HAILO8"]
 
@@ -59,9 +59,9 @@ def load_crop_model():
     """
     Load Paddle OCR detection + recognition models and wrap them in a
     CroppingAndClassifyingCompoundModel so detection crops feed into OCR.
-    Uses the same params as your notebook, just with inference_host_address=@cloud.
+
+    IMPORTANT: We set image_backend="pil" because the app passes a PIL.Image.
     """
-    # Token for DeGirum Cloud (keep in st.secrets)
     token = st.secrets.get("DG_TOKEN", "")
 
     # Load paddle ocr text detection model
@@ -71,6 +71,7 @@ def load_crop_model():
         zoo_url=ZOO_URL,
         device_type=DEVICE_TYPE,
         token=token,
+        image_backend="pil",  # <-- key fix
     )
 
     # Load paddle ocr text recognition model
@@ -80,6 +81,7 @@ def load_crop_model():
         zoo_url=ZOO_URL,
         device_type=DEVICE_TYPE,
         token=token,
+        image_backend="pil",  # <-- key fix
     )
 
     # Create a compound cropping model (det → crops → rec)
@@ -115,14 +117,13 @@ with st.form("ocr_form"):
             # Run AI inference on image
             inference_result = crop_model(image)
 
-            # Display combined results (image with boxes, if available)
+            # Display image with boxes (if overlay is available)
             if hasattr(inference_result, "image_overlay"):
                 st.image(
                     inference_result.image_overlay,
                     caption="OCR Output (detected text regions)",
                 )
             else:
-                # Fallback if image_overlay is not present
                 st.image(
                     image,
                     caption="Input image (no overlay available)",