Pulling from 2 different places to get this to work and not updating variable names

app.py

@@ -32,12 +32,12 @@ def detect_objects(model_name,url_input,image_input,threshold):
         model = MaskFormerForInstanceSegmentation.from_pretrained(model_name)
 
         target_size = (image.size[0], image.size[1])
-        inputs = preprocessor(images=image, return_tensors="pt")
+        inputs = processor(images=image, return_tensors="pt")
         with torch.no_grad():
             outputs = model(**inputs)
         outputs.class_queries_logits = outputs.class_queries_logits.cpu()
         outputs.masks_queries_logits = outputs.masks_queries_logits.cpu()
-        results = preprocessor.post_process_segmentation(outputs=outputs, target_size=target_size)[0].cpu().detach()
+        results = processor.post_process_segmentation(outputs=outputs, target_size=target_size)[0].cpu().detach()
         results = torch.argmax(results, dim=0).numpy()
         results = visualize_instance_seg_mask(results)
         return results, "EMPTY"