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

"""
# 犬種分類器
將柴犬(Japan)、薩摩耶(Russia)、德國狼犬(Germany)、鬆獅犬(China)分類的模型。
"""

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

    f"""
    ### 預測結果: {pred}
    ### 預測{pred}的可能性: {probs[key].item()*100: .2f}%
    """


path = "./"
learn_inf = load_learner(path + "resnet34_stage-1.pkl")

option = st.radio("", ["上傳檔案", "上傳圖片連結"])

if option == "上傳檔案":
    uploaded_file = st.file_uploader("請上傳圖片")

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

else:
    url = st.text_input("請上傳連結")

    if url != "":
        try:
            response = requests.get(url)
            pil_img = PILImage.create(BytesIO(response.content))
            predict(pil_img)

        except:
            st.text("連結出現問題", url)