Update app.py

app.py

@@ -11,54 +11,40 @@ if "memory" not in st.session_state:
 
 @st.cache_resource
 def load_model():
-    try:
-        model = AutoModel.from_pretrained("ragavsachdeva/magi", trust_remote_code=True)
-        device = "cuda" if torch.cuda.is_available() else "cpu"
-        model.to(device)
-        return model
-    except Exception as e:
-        st.error(f"Error loading model: {e}")
-        return None
+    model = AutoModel.from_pretrained("ragavsachdeva/magi", trust_remote_code=True)
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model.to(device)
+    return model
 
 @st.cache_data
 def read_image_as_np_array(image_path):
-    try:
-        if "http" in image_path:
-            image = Image.open(urllib.request.urlopen(image_path)).convert("L").convert("RGB")
-        else:
-            image = Image.open(image_path).convert("L").convert("RGB")
-        image = np.array(image)
-        return image
-    except Exception as e:
-        st.error(f"Error reading image: {e}")
-        return None
+    if "http" in image_path:
+        image = Image.open(urllib.request.urlopen(image_path)).convert("L").convert("RGB")
+    else:
+        image = Image.open(image_path).convert("L").convert("RGB")
+    image = np.array(image)
+    return image
 
 @st.cache_data
 def predict_detections_and_associations(
-    image_path,
-    char_detect_thresh,
-    panel_detect_thresh,
-    text_detect_thresh,
-    char_char_match_thresh,
-    text_char_match_thresh,
+        image_path,
+        character_detection_threshold,
+        panel_detection_threshold,
+        text_detection_threshold,
+        character_character_matching_threshold,
+        text_character_matching_threshold,
 ):
     image = read_image_as_np_array(image_path)
-    if image is None:
-        return None
-    try:
-        with torch.no_grad():
-            result = model.predict_detections_and_associations(
-                [image],
-                character_detection_threshold=char_detect_thresh,
-                panel_detection_threshold=panel_detect_thresh,
-                text_detection_threshold=text_detect_thresh,
-                character_character_matching_threshold=char_char_match_thresh,
-                text_character_matching_threshold=text_char_match_thresh,
+    with torch.no_grad():
+        result = model.predict_detections_and_associations(
+            [image],
+            character_detection_threshold=character_detection_threshold,
+            panel_detection_threshold=panel_detection_threshold,
+            text_detection_threshold=text_detection_threshold,
+            character_character_matching_threshold=character_character_matching_threshold,
+            text_character_matching_threshold=text_character_matching_threshold,
             )[0]
-        return result
-    except Exception as e:
-        st.error(f"Error during prediction: {e}")
-        return None
+    return result
 
 @st.cache_data
 def predict_ocr(