Update app.py

app.py

@@ -24,8 +24,8 @@ def predict(image):
     
     label , confidence = imgResult[0]['label'] , float(imgResult[1]['label'])
 
-    if confidence > 0.90:
-        return ["hate" , label]
+    if confidence > 0.95:
+        return ["hate" , f"label: {label}, confidence: {confidence}"]
     else:
  
         ocr_text = extract_text(image).lower()
@@ -41,15 +41,24 @@ def predict(image):
         )
 
         profanityFound = any(word in ocr_text.split() for word in profanity_hn)
-        
-        if not profanityFound and engResult[0] == "NEITHER" and hingResult[0] == "NAG":
-            return ["not_hate" , "No Hate Symbols Detected"]
+
+        if profanityFound:
+            return ["hate", "Profanity Found"]
+        elif engResult[0] != "NEITHER":
+            return ["hate", engResult[0]]
+        elif hingResult[0] != "NAG":
+            return ["hate", hingResult[0]]
         else:
-            return ["hate" , "No Hate Symbols Detected"]
+            return ["not_hate", "No hate found, yay!"]
+        
+        # if not profanityFound and engResult[0] == "NEITHER" and hingResult[0] == "NAG":
+        #     return ["not_hate" , "No Hate Symbols Detected"]
+        # else:
+        #     return ["hate" , "No Hate Symbols Detected"]
         
 iface = gr.Interface(fn=predict,
                      inputs = gr.Image(type='filepath'),
-                     outputs=[gr.Label(label = "Class") , gr.Label(label = "Hate Symbol(if any)")],
+                     outputs=[gr.Label(label = "Class (Hate or Not Hate)") , gr.Label(label = "Hate Symbol (if any)")],
                      title = "Hate Speech Detection in Image",
                      description = "Detect hateful symbols or text in Image"
         )