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import numpy as np
import gradio as gr
from tensorflow import keras
from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras("ISYS/MyNewModel")
def greet(img):
img = np.expand_dims(img, axis=0)
#return np.argmax(model.predict(img)[0])
numb = np.argmax(model.predict(img)[0])
return numb % 3
def rasp_numb(img):
img = np.expand_dims(img, axis=0)
return np.argmax(model.predict(img)[0])
output1 = gr.outputs.Text((np.argmax(model.predict(img)[0])% 3) )
output2 = gr.outputs.Text(np.argmax(model.predict(img)[0]))
demo = gr.Interface(fn=greet, inputs="sketchpad", outputs=[output1, output2])
demo.launch() |