Upload product_similarity.py

product_similarity.py

@@ -0,0 +1,258 @@
+# 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)
+                        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}")
+                                st.write(f"Ürün ismi: {filename_without_extension}")
+
+                        break
+
+                    except Exception as e:
+                        st.write(f"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(3):
+                    try:
+                        takemura_output = takemura(st.session_state['filenames'], image, product_details)
+                        filenames = takemura_output.split('\n')
+                        filenames = [filename[filename.rfind(' ') + 1:] for filename in filenames if ' ' in filename]
+
+                        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)
+                                    # 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"No matching rows found for filename {filename_without_extension}")
+                        break
+
+                    except Exception as e:
+                        st.write(f"Lütfen 'Sonuçları Göster' butonuna tekrar basınız.. ...")
+
+                st.session_state['show_results'] = False
+
+
+
+    else:
+        st.write("Başlamak için sol tarafa lütfen ürün fotoğrafı yükleyin.")