Update app.py

app.py

@@ -1,3 +1,37 @@
 import gradio as gr
+import torch
+from transformers import DetrForObjectDetection, DetrImageProcessor, AutoModel
+import supervision as sv
+from supervision.detection.annotate import BoxAnnotator
+from supervision.utils.notebook import plot_image
+
+og_model = 'facebook/detr-resnet-50'
+image_processor =  DetrImageProcessor.from_pretrained(og_model)
+model = AutoModel.from_pretrained("taroii/notfinetuned-detr-50")
+
+def query(image):
+    with torch.no_grad():
+        # load image and predict
+        inputs = image_processor(images=image, return_tensors='pt')
+        outputs = model(**inputs)
+    
+        # post-process
+        target_sizes = torch.tensor([image.shape[:2]])
+        results = image_processor.post_process_object_detection(
+            outputs=outputs, 
+            threshold=CONFIDENCE_TRESHOLD, 
+            target_sizes=target_sizes
+        )[0]
+    
+    # annotate
+    detections = sv.Detections.from_transformers(transformers_results=results).with_nms(threshold=0.5)
+    labels = [f"{id2label[class_id]} {confidence:.2f}" for _, confidence, class_id, _ in detections]
+    frame = box_annotator.annotate(scene=image.copy(), detections=detections, labels=labels)
+    
+    print('detections')
+    %matplotlib inline  
+    plot_image(frame, (16, 16))
+    
+    return labels, frame
 
 gr.Interface.load("models/taroii/notfinetuned-detr-50").launch()