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

"""
# 珊瑚疾病狀態
使用卷積神經網路分類珊瑚疾病狀態以支持保護海洋生態系統目標

分類包括珊瑚白化（Coral bleaching）、珊瑚扁蟲（Coral Flatworm）、黑帶病（Black Band Disease）、蝕骨海綿（Cliona spp）、骨骼侵蝕病（Skeletal Eroding Band coral）。

#可以複製上述五種疾病的英文名稱查詢圖片，來此驗證。
"""

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 == 'mi' else 'is not'}** an MI (heart attack).
    ### Rediction result: {pred}
    ### Probability of {pred}: {probs[key].item()*100: .2f}%
    """


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