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import gradio as gr
import tensorflow as tf
import numpy as np
from PIL import Image
import tensorflow.keras as keras
from tensorflow.keras.models import load_model
# load model
model = load_model('mmodelinusannekosan (1).h5')
classnames = ['neko','inu']
def predict_image(img):
img_4d=img.reshape(-1,224, 224,3)
prediction=model.predict(img_4d)[0]
return {classnames[i]: float(prediction[i]) for i in range(1)}
image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label(num_top_classes=2)
gr.Interface(fn=predict_image, inputs=image, title="Garbage Classifier V3",
description="ThiFaces using Gradio.",outputs=label,enable_queue=True,interpretation='default').launch() |