Added proper details impl

app.py

@@ -166,13 +166,20 @@ def get_predicted_attributes(image_urls, category):
         # Get the predicted values for the attribute
         responses = pipe(image_urls, candidate_labels=values_formatted)
         result = [response[0]['label'].split(", clothing:")[0] for response in responses]
-
-        # If attribute is details, then get the top 2 most common labels
-        if attribute_formatted == "details":
-            result += [response[1]['label'].split(", clothing:")[0] for response in responses]
-            common_result.append(Counter(result).most_common(2))
-        else:
-            common_result.append(Counter(result).most_common(1))
+        common_result.append(Counter(result).most_common(1))
+
+        # If attribute is details, then remove the obtained label from the values, and get the next most common
+        if attribute == "details":
+            values_formatted.remove(result[0])
+            responses = pipe(image_urls, candidate_labels=values_formatted)
+            i = 0
+            while len(responses) > 0 and responses[0][0]['score'] > 0.8 and i < 2:
+                result = [response[0]['label'].split(", clothing:")[0] for response in responses]
+                common_result.append(Counter(result).most_common(1))
+
+                responses = pipe(image_urls, candidate_labels=values_formatted)
+                i += 1
+            
 
     # Clean up the results into one long string
     for i, result in enumerate(common_result):