Update app.py

app.py

@@ -8,22 +8,6 @@ import numpy as np
 from ultralytics import YOLO
 import yolov5
 
-# Image download
-# file_urls = [
-# ]
-
-# def download_file(url, save_name):
-#     url = url
-#     if not os.path.exists(save_name):
-#         file = requests.get(url)
-#         open(save_name, 'wb').write(file.content)
-
-# for i, url in enumerate(file_urls):    
-#     download_file(
-#         file_urls[i],
-#         f"image_{i}.jpg"
-#     )
-
 # Function for inference
 def yolov5_inference(
     image: gr.inputs.Image = None,
@@ -62,8 +46,7 @@ inputs = [
 outputs = gr.outputs.Image(type="filepath", label="Output Image")
 outputs_crops = gr.Gallery(label="Object crop")
 
-title = "Crime detection using custom trained Yolo model"
-description = "YOLOv5 is a family of object detection models pretrained on COCO dataset. This model is a pip implementation of the original YOLOv5 model."
+title = "Perimeter security - to monitor suspicious human gestures"
 
 # gradio examples: "Image", "Model", "Image Size", "Confidence Threshold", "IOU Threshold"
 examples = [['1.jpg', 'Crime_Y5.pt', 640, 0.35, 0.45]