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DESCRIPTION.md

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+Simple image classification in Pytorch with Gradio's Image input and Label output.

README.md

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+
 ---
-title: Image Classification Main
-emoji: 📈
-colorFrom: purple
+title: image_classification_main 
+emoji: 🔥
+colorFrom: indigo
 colorTo: indigo
 sdk: gradio
 sdk_version: 3.6
-app_file: app.py
+app_file: run.py
 pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

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+torch
+torchvisionhttps://gradio-main-build.s3.amazonaws.com/c3bec6153737855510542e8154391f328ac72606/gradio-3.6-py3-none-any.whl

run.py

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+import gradio as gr
+import torch
+import requests
+from torchvision import transforms
+
+model = torch.hub.load('pytorch/vision:v0.6.0', 'resnet18', pretrained=True).eval()
+response = requests.get("https://git.io/JJkYN")
+labels = response.text.split("\n")
+
+def predict(inp):
+  inp = transforms.ToTensor()(inp).unsqueeze(0)
+  with torch.no_grad():
+    prediction = torch.nn.functional.softmax(model(inp)[0], dim=0)
+    confidences = {labels[i]: float(prediction[i]) for i in range(1000)}    
+  return confidences
+
+demo = gr.Interface(fn=predict, 
+             inputs=gr.inputs.Image(type="pil"),
+             outputs=gr.outputs.Label(num_top_classes=3),
+             examples=[["cheetah.jpg"]],
+             )
+             
+demo.launch()