Update app.py

app.py

@@ -5,8 +5,7 @@ import cv2
 import numpy as np
 import tempfile
 
-# List of unusual labels to detect
-unusual_labels = ['weapon', 'fighting', 'suspicious_activity']  # Extend as needed
+unusual_labels = ['weapon', 'fighting', 'suspicious_activity']  # Example unusual labels
 
 def yolo_inference(input_type, image, video, model_id, conf_threshold, iou_threshold, max_detection):
     unusual_detected = False
@@ -43,7 +42,6 @@ def yolo_inference(input_type, image, video, model_id, conf_threshold, iou_thres
             image_array = r.plot()
             annotated_image = Image.fromarray(image_array[..., ::-1])
 
-            # Get detected object labels
             for label in r.names:
                 detected_objects.append(label)
                 if label in unusual_labels:
@@ -125,12 +123,9 @@ def yolo_inference(input_type, image, video, model_id, conf_threshold, iou_thres
 with gr.Blocks() as app:
     with gr.Sidebar():
         gr.Markdown("# Inference Provider")
-        gr.Markdown(
-            "This Space showcases the facebook/detr-resnet-50 model, "
-            "served by the hf-inference API. Sign in with your Hugging Face account to use this API."
-        )
-        button = gr.LoginButton("Sign in")
-    gr.load("models/facebook/detr-resnet-50", accept_token=button, provider="hf-inference")
+        gr.Markdown("This Space showcases the facebook/detr-resnet-50 model, served by the hf-inference API.")
+    # Note: removed LoginButton and accept_token usage here
+    gr.load("models/facebook/detr-resnet-50", provider="hf-inference")
 
     gr.Markdown("# Yolo11: Object Detection, Instance Segmentation, Pose/Keypoints, Oriented Detection, Classification")
     gr.Markdown("Upload image(s) or video(s) for inference using the latest Ultralytics YOLO11 models.")
@@ -166,7 +161,6 @@ with gr.Blocks() as app:
             unusual_detected_flag = gr.Textbox(label="Unusual Detected Flag", visible=True)
             gr.DeepLinkButton()
 
-    # Toggle visibility based on input type
     input_type.change(
         fn=lambda t: [
             gr.update(visible=(t == "Image")),
@@ -178,7 +172,6 @@ with gr.Blocks() as app:
         outputs=[image, video, output_image, output_video]
     )
 
-    # Run inference on button click
     infer_button.click(
         fn=yolo_inference,
         inputs=[input_type, image, video, model_id, conf_threshold, iou_threshold, max_detection],