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File size: 348 Bytes
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import gradio as gr]
import pickle
import numpy as np
model = pickle.load(open("model.pkl","rb"))
def predict_v(input_value):
try:
if input_value == None: pass
except:
return np.argmax(model.predict(input_value / 255.))
gr.Interface(fn=predict_v,
inputs = gr.SketchPad(),
outputs="number").launch() |