Upload with huggingface_hub

DESCRIPTION.md

@@ -0,0 +1 @@
+Simple image classification in Pytorch with Gradio's Image input and Label output.

README.md

@@ -1,7 +1,7 @@
 
 ---
 title: image_classification 
-emoji: 🤗
+emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio

app.py

@@ -1,19 +1,12 @@
-# URL: https://huggingface.co/spaces/abidlabs/image_classification
-# DESCRIPTION: Simple image classification in Pytorch with Gradio's Image input and Label output.
-# imports
 import gradio as gr
 import torch
 import requests
 from torchvision import transforms
 
-# load the model 
 model = torch.hub.load('pytorch/vision:v0.6.0', 'resnet18', pretrained=True).eval()
-
-# download human-readable labels for ImageNet.
 response = requests.get("https://git.io/JJkYN")
 labels = response.text.split("\n")
 
-# define core function
 def predict(inp):
   inp = transforms.ToTensor()(inp).unsqueeze(0)
   with torch.no_grad():
@@ -21,12 +14,10 @@ def predict(inp):
     confidences = {labels[i]: float(prediction[i]) for i in range(1000)}    
   return confidences
 
-# define the interface 
 demo = gr.Interface(fn=predict, 
              inputs=gr.inputs.Image(type="pil"),
              outputs=gr.outputs.Label(num_top_classes=3),
              examples=[["cheetah.jpg"]],
              )
              
-# launch
 demo.launch()