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
 
model = load_model('Fusen_dataset.h5')
classnames = ['Normal', 'Kizu', 'Yogore']

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(3)}
                
image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label(num_top_classes=3)

gr.Interface(fn=predict_image, inputs=image,  title="ふせん外観検査",
    description="ふせんの写真を撮って「送信」ボタンを押して下さい！汚れや破れを検出します。",outputs=label,enable_queue=True,interpretation='default').launch()