import streamlit as st
from PIL import Image
import numpy as np
import plotly.graph_objects as go
from models import predict
import cv2



google_form_link = 'https://docs.google.com/forms/d/1xKeveRFf90_wCX-tjMInFC48XmFF8HOsPSQ47ruOFk0/edit'
# Load the pre-trained Haar Cascade for eye detection
eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')

# Function to check if the image contains an eye
def contains_eye(image):
    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    eyes = eye_cascade.detectMultiScale(gray_image, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
    return len(eyes) > 0

# Function to load the image
def load_image(image_file):
    img = Image.open(image_file)
    return img

# Streamlit app title
st.title("Eye Cataract Detection")

# Streamlit header and subheader
st.header('Upload the image')

# File uploader widget
image_file = st.file_uploader("Upload Images", type=["png", "jpg", "jpeg"])

# Check if an image file is uploaded
if image_file is not None:
    img = load_image(image_file)

    # Display the uploaded image
    st.image(img, width=250)

    # Convert image to OpenCV format
    open_cv_image = np.array(img)

    if contains_eye(open_cv_image):
        # Button for detection
        if st.button('Detect'):  # This line adds a 'Detect' button
            # Predict the label and probability
            label, prob = predict(open_cv_image)

            # Use markdown to style the text and include emojis
            if prob > 0.5:
                st.markdown(f"<h2 style='color: red;'>Cataract Detected 😟</h2>", unsafe_allow_html=True)
                #st.markdown(f"### Probability: **{prob:.2f}**")
            else:
                st.markdown(f"<h2 style='color: green;'>No Cataract Detected 😄</h2>", unsafe_allow_html=True)
                #st.markdown(f"### Probability: **{prob:.2f}**")

            # Pie chart visualization
            fig = go.Figure(data=[go.Pie(labels=['Cataract', 'No Cataract'], 
                                        values=[prob, 1 - prob],
                                        hoverinfo='label+percent', 
                                        pull=[0, 0])])
            fig.update_layout(title_text='Cataract Detection Probability')
            st.plotly_chart(fig)

            st.subheader("Doctor's Verification")
            st.markdown(f"[Click here to provide feedback on the cataract detection results]({google_form_link})", unsafe_allow_html=True)

    else:
        st.error("No eyes detected in the image. Please upload a relevant eye image.")