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import tensorflow as tf
from tensorflow.keras.utils import load_img, img_to_array
import numpy as np
import gradio as gr
class_names=['Ayam Goreng','Bakso','Bubur Ayam','Ikan Lele Goreng','Mi Goreng','Nasi','Sate','Soto','Telur dadar','Telur mata sapi','Ikan mujahir goreng','Lontong','Pempek telur','Singkong Goreng','Tempe kedelai murni, goreng']
model=tf.keras.models.load_model('./my_model')
def import_and_predict(image_data):
x = image_data.reshape((-1, 224, 224, 3))
x = tf.keras.applications.imagenet_utils.preprocess_input(x, mode="tf")
prediction = model.predict(x)
labels=class_names
confidences = {labels[i]: float(prediction[0][i]) for i in range(15)}
return confidences
#test
gr.Interface(fn=import_and_predict,
inputs=gr.inputs.Image(shape=(224, 224)),
outputs=gr.outputs.Label(num_top_classes=3),
cache_examples=False,
examples=["Bakso.jpeg", "Sate.jpeg"]).launch()