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import streamlit as st
from PIL import Image
import os
import cv2
from modules import *
def processImage():
"""
UI Part if the users chooses
to proceess a image.
"""
# load the model
model = setup()
# load the image
image_file = st.file_uploader("Upload An Image",type=['png','jpeg','jpg'])
# check if the image is uploaded
if image_file is not None:
# get the file details
file_details = {"FileName":image_file.name,"FileType":image_file.type}
file_type = (image_file.type).split('/')[1]
# make a directory to store the image
if not os.path.exists(os.path.join(os.getcwd(),"data")):
os.makedirs(os.path.join(os.getcwd(),"data"))
# save the image
input_file_name = f"data/Input.{file_type}"
with open(input_file_name,mode = "wb") as f:
f.write(image_file.getbuffer())
# predict the image and save it
result_frame, labels = predict(input_file_name,model)
cv2.imwrite('data/result.jpg', result_frame)
# display the image and class
img_ = Image.open(f"data/result.jpg")
result_class = " ".join(labels).split()[0]
confidence = float(" ".join(labels).split()[1])
st.subheader(f"Result {result_class} with confidence {confidence * 100 :.2f}%")
st.image(img_)
# To download the image
with open("data/result.jpg", "rb") as file:
st.download_button(
label="Download image",
data=file,
file_name="predicted.jpg",
mime="image/jpg"
)
def main():
"""
UI Part of the entire application.
"""
st.set_page_config(
page_title ="Parkinson-X",
page_icon = "🧊",
menu_items={
'About': "# Parkinson's Prediction"
}
)
st.markdown("<h1 style='text-align: center;'>Parkinson's <span style='color: #9eeade;'>Prediction</span></h1>", unsafe_allow_html=True)
st.subheader("Early Parkinson's detection")
st.title('Drawing Analysis')
processImage()
with st.expander("Parkinson's Prediction"):
st.markdown( "<p style='font-size: 30px;'><strong>Welcome to the Parkinson's \
<span style='color: #9eeade;'>Prediction</span> App!</strong></p>", unsafe_allow_html= True)
st.markdown("<p style = 'font-size : 20px; color : white;'>This application was \
built to analyse the <strong>spiral drawings</strong> \
to predict and suggest parkinson diagnosis.</p>", unsafe_allow_html=True)
if __name__ == '__main__':
__author__ = 'Mahimai Raja J'
__version__ = "1.0.0"
main()
# 📌 NOTE :
# Do not modify the credits unless you have
# legal permission from the authorizing authority .
# Thank you for helping to maintain the integrity of the
# open source community by promoting fair and ethical
# use of open source software 💎. |