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import timm
from fastai.vision.all import PILImage, load_learner
import gradio as gr
import pathlib
import torch
pathlib.WindowsPath = pathlib.PosixPath
learn = load_learner('convnet_final3.pkl')
categories = ('audi', 'bmw', 'mercedes', 'volvo')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(300,300))
label = gr.outputs.Label()
intf = gr.Interface(fn=classify_image, inputs=image, outputs = label)
intf.launch(inline=False) |