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# import gradio as gr
#
# def greet(name):
# return "Hello " + name + "!!"
#
# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()
# Cell
from fastai.vision.all import *
import gradio as gr
import timm
import dill
def is_catan(x):
# print(x[:5])
# print(x[:5] == 'Catan')
return x[:5] == 'Catan'
# Cell
learn = load_learner('catan-model-paperspace.pkl', pickle_module=dill)
# Cell
# categories = learn.dls.vocab
categories = ('Not Catan', 'Catan')
def classify_image(img):
pred, idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
# Cell
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['board-game-catan-IMG_4671.jpg', 'photo-of-macbook-catan-IMG_4817.jpg']
# Cell
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch()
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