app.py

import streamlit as st
from PIL import Image
import numpy as np
import tensorflow as tf

# 事前訓練済みのモデルをロード
model = tf.keras.applications.MobileNetV2(weights='imagenet')

# 画像の前処理を行う関数
def preprocess_image(image):
    image = image.resize((224, 224))
    image = np.array(image)
    image = np.expand_dims(image, axis=0)
    image = tf.keras.applications.mobilenet_v2.preprocess_input(image)
    return image

# 予測を行う関数
def predict(image):
    processed_image = preprocess_image(image)
    predictions = model.predict(processed_image)
    decoded_predictions = tf.keras.applications.mobilenet_v2.decode_predictions(predictions, top=1)
    return decoded_predictions[0][0][1]

# Streamlitの設定
st.title("Image Classification with CNN")
st.write("Upload an image to classify it using MobileNetV2")

# ファイルアップロード
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])

if uploaded_file is not None:
    image = Image.open(uploaded_file)
    st.image(image, caption='Uploaded Image.', use_column_width=True)
    st.write("")
    st.write("Classifying...")
    label = predict(image)
    st.write(f"Prediction: {label}")