Update app.py

app.py

@@ -169,23 +169,23 @@ def get_predicted_attributes(image_urls, category):
             continue
 
        # Adjust labels for the pipeline
-    attribute = attribute.replace("colartype", "collar").replace("sleevelength", "sleeve length").replace("fabricstyle", "fabric")
-    values = [f"{attribute}: {value.strip()}, clothing: {category}" for value in values]
-
-    # Get the predicted values for the attribute
-    responses = pipe(image_urls, candidate_labels=values)
-    most_common, score = get_most_common_label(responses)
-    common_result.append(most_common)
-    print(common_result)
-
-    if attribute == "details":
-        # Process additional details labels if the score is higher than 0.8
-        for _ in range(2):
-            values = [value for value in values if value != f"{most_common}, clothing: {category}"]
-            responses = pipe(image_urls, candidate_labels=values)
-            most_common, score = get_most_common_label(responses)
-            if score > 0.8:
-                common_result.append(most_common)
+        attribute = attribute.replace("colartype", "collar").replace("sleevelength", "sleeve length").replace("fabricstyle", "fabric")
+        values = [f"{attribute}: {value.strip()}, clothing: {category}" for value in values]
+
+        # Get the predicted values for the attribute
+        responses = pipe(image_urls, candidate_labels=values)
+        most_common, score = get_most_common_label(responses)
+        common_result.append(most_common)
+        print(common_result)
+
+        if attribute == "details":
+            # Process additional details labels if the score is higher than 0.8
+            for _ in range(2):
+                values = [value for value in values if value != f"{most_common}, clothing: {category}"]
+                responses = pipe(image_urls, candidate_labels=values)
+                most_common, score = get_most_common_label(responses)
+                if score > 0.8:
+                    common_result.append(most_common)
 
     # Convert common_result into a dictionary
     final = {}