Update app.py

app.py

@@ -3,14 +3,14 @@ import torch
 from ultralyticsplus import YOLO, render_result
 
 
-#torch.hub.download_url_to_file("img1.jpg", 'one.jpg')
-#torch.hub.download_url_to_file("img2.jpg", 'two.jpg')
-#torch.hub.download_url_to_file("img3.jpg", 'three.jpg')
-
-def yoloV8_func(image: gr.inputs.Image = None,
-                image_size: gr.inputs.Slider = 640,
-                conf_threshold: gr.inputs.Slider = 0.4,
-                iou_threshold: gr.inputs.Slider = 0.50):
+torch.hub.download_url_to_file("img1.jpg", 'one.jpg')
+torch.hub.download_url_to_file("img2.jpg", 'two.jpg')
+torch.hub.download_url_to_file("img3.jpg", 'three.jpg')
+
+def yoloV8_func(image: gr.Image = None,
+                image_size: gr.Slider = 640,
+                conf_threshold: gr.Slider = 0.4,
+                iou_threshold: gr.Slider = 0.50):
     """This function performs YOLOv8 object detection on the given image.
 
     Args:
@@ -41,24 +41,25 @@ def yoloV8_func(image: gr.inputs.Image = None,
 
 
 inputs = [
-    gr.inputs.Image(type="filepath", label="Input Image"),
-    gr.inputs.Slider(minimum=320, maximum=1280, default=640,
+    gr.Image(type="filepath", label="Input Image"),
+    gr.Slider(minimum=320, maximum=1280, default=640,
                      step=32, label="Image Size"),
-    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25,
+    gr.Slider(minimum=0.0, maximum=1.0, default=0.25,
                      step=0.05, label="Confidence Threshold"),
-    gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45,
+    gr.Slider(minimum=0.0, maximum=1.0, default=0.45,
                      step=0.05, label="IOU Threshold"),
 ]
 
 
-outputs = gr.outputs.Image(type="filepath", label="Output Image")
+outputs = gr.outputs.Image( label="Output Image")
+
 
 title = "YOLOv8 101: Custom Object Detection on Construction Workers"
 
 
 examples = [['img1.jpg', 640, 0.5, 0.7],
             ['img2.jpg', 800, 0.5, 0.6],
-            ['img13.jpg', 900, 0.5, 0.8]]
+            ['img3.jpg', 900, 0.5, 0.8]]
 
 yolo_app = gr.Interface(
     fn=yoloV8_func,