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from fastai.vision.all import *
import gradio as gr
import pathlib, os
categories = ['daisy', 'dandelion', 'rose', 'sunflower', 'tulip']
def classify_image(img):
if os.name == 'posix': # workaround for Linux
pathlib.WindowsPath = pathlib.PosixPath
learn = load_learner('flowers.pkl')
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = [
'dandelion+seeds.jpg',
'common-dandelion-seeds-medical-herb-taraxacum-officinale.jpg',
'dandelion-seedhead.jpg',
'dandelion.jpg',
'how-to-draw-sunflower.jpg',
'sunflower.jpg',
'sunflower1.jpg',
'tulip-drawing.jpg',
'broken-tulip-flower.jpg',
'rose01.jpg',
'rose02-blue.jpg',
'top-25-most-beautiful-daisy-flowers.jpg',
'daisy-varieties.jpg'
]
iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch() |