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from fastai.vision.all import *
import pathlib
import numpy as np
import cv2
from PIL import image
plt = platform.system()
if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath
learn=load_learner("CatvsDogmodel.pkl")
categories=('Cat','Dog')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
import gradio as gr
image=gr.inputs.Image(shape=(224, 224))
image = cv2.imread(image)
Image.open(image)
image = image/255
image = np.reshape(image, [1,224,224,3])
label=gr.outputs.Label()
intf=gr.Interface(fn=classify_image, inputs=image, outputs=label)
intf.launch(inline=False) |