Update app.py

app.py

@@ -10,13 +10,7 @@ import gradio as gr
 
 model = torch.load('best.pt')
 
-inv_normalize = transforms.Normalize(
-    mean = [-0.50/0.23, -0.50/0.23, -0.50/0.23],
-    std= [1/0.23, 1/0.23,1/0.23]
-)
-
-classes = ('plane', 'car', 'bird', 'cat', 'deer',
-           'dog', 'frog', 'horse', 'ship', 'truck')
+classes = ('ball', 'goalkeeper', 'player', 'referee')
 
 model_layer_names = ["1", "2", "3"]
 
@@ -97,8 +91,8 @@ demo = gr.Interface(
         gr.Image(width= 256, height=256,label="Output Image"),
         gr.Label(label="Confidences", container=True, show_label= True),
     ],
-    title = "CIFAR 10 trained on ResNet model in pytorch lightning with Gradcam",
-    description = " A simple gradio inference to infer on resnet18 model",
+    title = "Yolo v9 on custom fooball dataset",
+    description = " A simple gradio inference, and detection results for custom trained yolov9 model",
     examples = [["cat.jpg",1, True, 10, 0.4]]
 )