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import gradio as gr
import torch
from torchvision import transforms
model = torch.jit.load("./models/cat_dog_cnn.pt")
model.eval()
transform = transforms.Compose([
transforms.Resize((224,224)),
transforms.ToTensor(),
transforms.Normalize((0.485,0.456,0.406),(0.229,0.224,0.225))
])
CLASSES = ["Cat", "Dog", "Panda"]
def classify_image(inp):
inp = transform(inp).unsqueeze(0)
out = model(inp)
return CLASSES[out.argmax().item()]
iface = gr.Interface(fn=classify_image,
inputs=gr.Image(type="pil", label="Input Image"),
outputs="text",
examples=[
"./app_data/cat.jpg",
"./app_data/dog.jpg",
"./app_data/panda.jpg",
])
iface.launch()
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