Dealing with types

gradio-ocsai-d.py

@@ -58,8 +58,11 @@ def get_predictions(img):
 def classify_image(img_dict: dict):
     # gradio passes a dictionary with background, composite, and layers
     # the composite is what we want
-    img = img_dict['composite'].convert('RGB')
-    p = get_predictions(img)
+    img = img_dict['composite']
+    if img is None:
+        return None
+    
+    p = get_predictions(img.convert('RGB'))
 
     score_round = str(np.round(p['originality'], 2))
     label = f"Percentile: {p['percentile']}; Normalized Score: {score_round}"