v3.0.2-Code fix and triage

app.py

@@ -1,8 +1,8 @@
 import gradio as gr
-import numpy as np
+# import numpy as np
 import torch
 import requests
-from PIL import Image
+# from PIL import Image
 from torchvision import transforms
 
 model = torch.hub.load('pytorch/vision:v0.6.0', 'resnet18', pretrained=True).eval()
@@ -33,8 +33,8 @@ def predict(inp):
 
 # demo = gr.Interface(fn=sepia, inputs="image", outputs="image")
 demo = gr.Interface(fn=predict,
-                    inputs=gr.Image(type="pil"),
-                    outputs=gr.Label(num_top_classes=3),
+                    inputs=gr.inputs.Image(type="pil"),
+                    outputs=gr.outputs.Label(num_top_classes=3),
                     examples=["lion.jpg", "cheetah.jpg"])
 demo.launch()
 

requirements.txt

@@ -1,6 +1,4 @@
 gradio
-numpy
 torch
 requests
-PIL 
 torchvision