app.py

from fastai.vision.all import *
from io import BytesIO
import requests
import streamlit as st

# 应用标题
st.title("能源類型分類器")
st.write("這是一個可以分類不同能源形式（如風能、太陽能、水能）的分類器。")

# 展示示例图片
st.write("## 範例圖")
st.image("exwind.jpg", caption="Example EKG Image", use_column_width=True)

def predict(img):
    st.image(img, caption="Your image", use_column_width=True)
    pred, key, probs = learn_inf.predict(img)

    result_message = f"""
    ### Prediction result: {pred}
    ### Probability of {pred}: {probs[key].item()*100: .2f}%
    """
    st.write(result_message)

# 加载模型
path = "./"
learn_inf = load_learner(path + "resnet34_stage_4_1.pkl")

# 用户上传图片或提供图片 URL
option = st.radio("", ["Upload Image", "Image URL"])

if option == "Upload Image":
    uploaded_file = st.file_uploader("Please upload an image.")

    if uploaded_file is not None:
        img = PILImage.create(uploaded_file)
        predict(img)

else:
    url = st.text_input("Please input a URL for an image.")

    if url != "":
        try:
            response = requests.get(url)
            pil_img = PILImage.create(BytesIO(response.content))
            predict(pil_img)
        except Exception as e:
            st.error(f"Problem reading image from the URL. Please check the URL and try again. Error: {str(e)}")