Delete product_similarity.py

product_similarity.py

@@ -1,256 +0,0 @@
-# VGG16
-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)
-
-# Read the encrypted content from model.py.enc file
-with open('model.py.enc', 'rb') as file:
-    encrypted_model = file.read()
-
-decrypted_model = cipher_suite.decrypt(encrypted_model)
-decrypted_model_str = decrypted_model.decode()
-
-# Execute the decrypted model string
-exec(decrypted_model_str)
-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)
-
-# from model_takemura import *
-
-
-# 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)
-
-#
-# from model_hayabusa import *
-
-
-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(["Takemura", "Hayabusa"])
-
-    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:
-            if st.button("Takemura ile Analiz Yap"):
-                status_placeholder = st.empty()
-                status_placeholder.status("Analizi yapılıyor...")
-
-                filenames = model_1(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']:
-                show_results_button = st.button("Sonuçları Göster", key='button1')
-
-                if show_results_button and ('show_results' not in st.session_state or not st.session_state['show_results']):
-                    st.session_state['show_results'] = True
-
-            if 'show_results' in st.session_state:
-                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, 9])  # 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)
-                                    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)
-                            else:
-                                st.write(f"Ürün isimlerini maalesef eşleştiremedim {filename_without_extension}")
-                        break
-
-                    except Exception as e:
-                        st.write(f"An error occurred: {e}")
-                        st.write(f"Takemura için Lütfen 'Sonuçları Göster' butonuna tekrar basınız.. ...")
-
-                st.session_state['show_results'] = False
-
-        with tab2:
-            if st.button("Hayabusa ile Analiz Yap"):
-                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']:
-                show_results_button = st.button("Hayabusa Sonuçlarını Göster", key='button2')
-                if show_results_button and ('show_results' not in st.session_state or not st.session_state['show_results']):
-                    st.session_state['show_results'] = True
-
-            if 'show_results' in st.session_state:
-                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)
-                            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
-
-
-
-    else:
-        st.write("Please upload an image.")