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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) | |