product_similarity.py

import pandas as pd
import streamlit as st
from tensorflow.keras.preprocessing import image as kimage
from cryptography.fernet import Fernet
import os

from io import BytesIO
from dotenv import load_dotenv



load_dotenv()


dec_key =os.getenv("FERNET_KEY")

cipher_suite=Fernet(dec_key)

st.set_page_config(
    layout="wide",
    initial_sidebar_state="expanded",
)


@st.cache_data
def load_data():
    # Read the encrypted content from the Excel file
    with open('pantolon-v3.xlsx.enc', 'rb') as file:
        encrypted_data = file.read()

    # Decrypt the data
    decrypted_data = cipher_suite.decrypt(encrypted_data)

    # Load the decrypted data into a pandas DataFrame
    df = pd.read_excel(BytesIO(decrypted_data))

    return df


# Read the encrypted content from model.py.enc file
with open('model_takemura.py.enc', 'rb') as file:
    encrypted_model_takemura = file.read()

decrypted_model_takemura = cipher_suite.decrypt(encrypted_model_takemura)
decrypted_model_str_takemura = decrypted_model_takemura.decode()

# Execute the decrypted model string
exec(decrypted_model_str_takemura)


# Read the encrypted content from model.py.enc file
with open('model_hayabusa.py.enc', 'rb') as file:
    encrypted_model_hayabusa = file.read()

decrypted_model_hayabusa = cipher_suite.decrypt(encrypted_model_hayabusa)
decrypted_model_str_hayabusa = decrypted_model_hayabusa.decode()

# Execute the decrypted model string
exec(decrypted_model_str_hayabusa)


# Read the encrypted content from model.py.enc file
with open('model_shogun.py.enc', 'rb') as file:
    encrypted_model_shogun = file.read()

decrypted_model_shogun = cipher_suite.decrypt(encrypted_model_shogun)
decrypted_model_str_shogun = decrypted_model_shogun.decode()

# Execute the decrypted model string
exec(decrypted_model_str_shogun)

#
# # Read the encrypted content from model.py.enc file
# with open('preprocessing.py.enc', 'rb') as file:
#     encrypted_preprocessing = file.read()
#
# decrypted_preprocessing = cipher_suite.decrypt(encrypted_preprocessing)
# decrypted_str_preprocessing = decrypted_preprocessing.decode()
#
# # Execute the decrypted model string
# exec(decrypted_str_preprocessing)
#

def page1():
    st.title("Ürün Benzerlik Analizi")
    st.write(
        "Ürün benzerlik analizi, ürününüzün fotoğrafını yükleyerek benzer ürünleri ve verilerini bulmanızı sağlar.")

    image = st.sidebar.file_uploader("Lütfen ürününüzün fotoğrafını yükleyin:")

    st.markdown("""
    <style>

        .stTabs [data-baseweb="tab-list"] {
            gap: 20px;
            padding: 10px/* Increase the gap between tabs */

        }

        .stTabs [data-baseweb="tab-list"] button [data-testid="stMarkdownContainer"] p {
        font-size:1.5rem;
        font-family: "Segoe UI", Tahoma, Geneva, Verdana, sans-serif;
        }

        .stTabs [data-baseweb="tab"] {
            height: 50px;
            white-space: pre-wrap;
            border-radius: 12px;  /* Make the tabs look like pills */
            padding: 10px 20px;  /* Add padding to the tabs */
            box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06); /* Add shadow to the tabs */
            transition: background-color 0.3s ease; /* Add transition effect */
            color: #333; /* Change the text color to a soft black */
        }

        .stTabs [aria-selected="true"] {
            background-color: #e0e0e0; /* Change the background color to a soft gray */
            border-color: #3d5afe; /* Add border color to the selected tab */
            color: #ffffff; /* Change the text color to a soft blue */;
        }

        .stTabs [aria-selected="true"]:hover {
            background-color: #d0d0d0; /* Change background color when hover on the selected tab */
        }

    </style>""", unsafe_allow_html=True)

    tab1, tab2 = st.tabs(["Benzer Ürün Analizi", "Ürün Özellik Analizi"])

    if image is not None:
        st.sidebar.success("Görsel başarıyla yüklendi.")

        product_category = st.sidebar.selectbox("Lütfen ürün kategorisi seçin:",
                                                ["Pantolon", "Gömlek - (Test)", "Elbise - (Test)", "Ceket - (Test)",
                                                 "Hırka - (Test)"])
        if product_category == "Pantolon":

            default_product_details = ["Desen", "Bel", "Paça"]  # Assign a default value

            product_details = st.sidebar.multiselect("Benzerlik için öncelik sırasına göre detay seçin:",
                                                     ["Bel", "Desen", "Paça"],
                                                     default=default_product_details)

            if not product_details:  # If product_details is an empty list
                st.sidebar.error("En az 1 özellik seçilmelidir.")

        with tab1:
            # Create placeholders for both buttons
            analyse_button_placeholder = st.empty()
            show_results_button_placeholder = st.empty()

            # Check if 'analysis_done' is in session state and if it's True
            if 'analysis_done' not in st.session_state or not st.session_state['analysis_done']:
                # Display the "Hayabusa ile Analiz Yap" button
                analyse_button = analyse_button_placeholder.button("Hayabusa ile Analiz Yap")
                if analyse_button:
                    # Clear the "Hayabusa ile Analiz Yap" button
                    analyse_button_placeholder.empty()

                    status_placeholder = st.empty()
                    status_placeholder.status("Analizi yapılıyor...")

                    filenames = model_2(image)
                    st.session_state['filenames'] = filenames
                    st.session_state['image'] = image
                    st.session_state['analysis_done'] = True

                    status_placeholder.success("Analiz tamamlandı.")

            if 'analysis_done' in st.session_state and st.session_state['analysis_done']:
                # Check if 'show_results' is in session state and if it's True
                if 'show_results' not in st.session_state or not st.session_state['show_results']:
                    # Display the "Hayabusa Sonuçlarını Göster" button
                    show_results_button = show_results_button_placeholder.button("Hayabusa Sonuçlarını Göster",
                                                                                 key='button2')
                    if show_results_button:
                        # Clear the "Hayabusa Sonuçlarını Göster" button
                        show_results_button_placeholder.empty()
                        st.session_state['show_results'] = True
                        status_placeholder_2 = st.empty()
                        status_placeholder_2.status("Sonuçlar toplanıyor...")

            if 'show_results' in st.session_state and st.session_state['show_results']:
                image_dir = "general/PANTOLON"
                df = load_data()
                st.empty()

                for _ in range(5):
                    try:
                        takemura_output = takemura(st.session_state['filenames'], image, product_details)
                        filenames = takemura_output.split('\n')

                        for filename in filenames:
                            filename_without_extension = os.path.splitext(filename)[0]
                            filename_without_extension = filename_without_extension.split('_')[0]

                            matching_rows = df.loc[df['ItemOption'] == filename_without_extension]

                            if not matching_rows.empty:
                                for _, row in matching_rows.iterrows():
                                    cols = st.columns([2, 8])  # Adjust these values for desired widths
                                    img_path = os.path.join(image_dir, filename)
                                    img = kimage.load_img(img_path)
                                    cols[0].image(img, width=200)
                                    # cols[1].dataframe(pd.DataFrame(row).T)
                                    half = len(row) // 2  # Find the midpoint of the row

                                    # Split the row into two parts
                                    row_upper_half = row.iloc[:half]
                                    row_lower_half = row.iloc[half:]

                                    # Display the two parts in two separate dataframes
                                    cols[1].dataframe(pd.DataFrame(row_upper_half).T)
                                    cols[1].dataframe(pd.DataFrame(row_lower_half).T)

                                    status_placeholder_2.success("Sonuçlar başarıyla toplandı.")
                            else:
                                st.write(f"Ürün isimlerini maalesef eşleştiremedim {filename_without_extension}")
                        break

                    except Exception as e:
                        st.write(f"Hayabusa için Lütfen 'Sonuçları Göster' butonuna tekrar basınız.. ...")

                st.session_state['show_results'] = False

        with tab2:
            shogun(image)



    else:
        st.write("Please upload an image.")