Update app.py

app.py

@@ -45,20 +45,18 @@ def inference(input_image):
     #with open("dog_cat.txt", "r") as f:
         #categories = [s.strip() for s in f.readlines()]
     #with open("dog_cat.txt", "r") as f:
-    categories = []
-    categories.append("cat")
-    categories.append("dog")
+    categories = ["cat","dog"]
 
     #categories = [s.strip() for s in f.readlines()]
     # Show top categories per image
-    top5_prob, top5_catid = torch.topk(probabilities, 2)
+    top1_prob, top1_catid = torch.topk(probabilities, 1)
     result = {}
-    for i in range(top5_prob.size(0)):
-        result[categories[top5_catid[i]]] = top5_prob[i].item()
+    for i in range(top1_prob.size(0)):
+        result[categories[top1_catid[i]]] = top1_prob[i].item()
     return result
 
 inputs = gr.inputs.Image(type='pil')
-outputs = gr.outputs.Label(type="confidences",num_top_classes=2)
+outputs = gr.outputs.Label(type="confidences",num_top_classes=1)
 
 title = "GHOSTNET"
 description = "Gradio demo for GHOSTNET, Efficient networks by generating more features from cheap operations. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."