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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]) | |
a = numb % 3 | |
return a, numb | |
def process_sketch(img): | |
img = np.expand_dims(img, axis=0) | |
output1 = np.argmax(model.predict(img)[0]) | |
output2 = (np.argmax(model.predict(img)[0]) % 3) | |
return output1, output2 | |
#demo = gr.Interface(fn=process_sketch, inputs="sketchpad", outputs=["text", "text"], title="Распознавание рисунка") | |
#demo.launch() | |
iface = gr.Interface( | |
fn=greet, | |
inputs="sketchpad", | |
outputs=[gr.outputs.Text(label="Среднее"), gr.outputs.Text(label="Стандартное отклонение")], | |
layout="vertical", | |
title="Распознавание рисунка" | |
) | |
iface.launch() |