Update app.py

app.py

@@ -26,8 +26,8 @@ MAX_NUM_FRAMES = 300
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 checkpoint = "IDEA-Research/dab-detr-resnet-50-dc5-pat3"
-image_processor = AutoProcessor.from_pretrained(person_detector_name)
-model = RTDetrForObjectDetection.from_pretrained(person_detector_name, device_map=device)
+image_processor = AutoProcessor.from_pretrained(checkpoint)
+model = RTDetrForObjectDetection.from_pretrained(checkpoint, device_map=device)
 
 
 @spaces.GPU(duration=5)
@@ -35,7 +35,7 @@ model = RTDetrForObjectDetection.from_pretrained(person_detector_name, device_ma
 def process_image(image: PIL.Image.Image) -> tuple[PIL.Image.Image, list[dict]]:
     inputs = image_processor(images=image, return_tensors="pt").to(device)
     outputs = model(**inputs)
-    results = person_image_processor.post_process_object_detection(
+    results = image_processor.post_process_object_detection(
         outputs, target_sizes=torch.tensor([(image.height, image.width)]), threshold=0.3
     )
     result = results[0]  # take first image results