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

"""
# 分類花種
類別有櫻花 茶花 玫瑰 杜鵑 茉莉 梅花 康乃馨 向日葵 蘭花 牡丹 
"""

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"""
    ## This **{'is ' if pred == 'Cherry blossoms' else 'is not'}** an Cherry blossoms .
    ### Rediction result: {pred}
    ### Probability of {pred}: {probs[key].item()*100: .2f}%
    """


path = "./"
learn_inf = load_learner(path + "resnet34_stage-2-1.pkl")

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.")

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

        except:
            st.text("Problem reading image from", url)