Update src/streamlit_app.py

src/streamlit_app.py

@@ -4,24 +4,31 @@ import numpy as np
 import os
 from PIL import Image
 
-# --- YAPILANDIRMA / CONFIGURATION ---
-base_path = r'C:\Users\MERGEN\OneDrive\Documents\Yapay Zeka Kursu\Prework\14\Car_Logo_Dataset'
+# --- AKILLI YOL YAPILANDIRMASI / SMART PATH CONFIGURATION ---
+# Kendi bilgisayarındaki yol
+local_path = r'C:\Users\MERGEN\OneDrive\Documents\Yapay Zeka Kursu\Prework\14\Car_Logo_Dataset'
+# Hugging Face veya genel bulut yolu
+cloud_path = 'Car_Logo_Dataset'
+
+# Bilgisayarında mısın yoksa bulutta mı kontrol et
+if os.path.exists(local_path):
+    base_path = local_path
+else:
+    base_path = cloud_path
 
 st.set_page_config(page_title="Car Logo AI", layout="wide")
 
 # --- BAŞLIK / TITLE ---
 st.markdown("<h1 style='text-align: center;'>🚗 Araba Logosu Tanıma / Car Logo Recognition</h1>", unsafe_allow_html=True)
-st.markdown("<p style='text-align: center;'> Computer Vision Project</p>", unsafe_allow_html=True)
+st.markdown("<p style='text-align: center;'>Computer Vision Project</p>", unsafe_allow_html=True)
 st.markdown("---")
 
-# --- RECOGNITION FUNCTION / --- LOGO TANIMA FONKSİYONU
+# --- LOGO TANIMA FONKSİYONU / RECOGNITION FUNCTION ---
 def predict_logo(uploaded_file):
-    # Kritik Düzeltme: Dosyayı okumadan önce başına sarıyoruz
     uploaded_file.seek(0) 
     file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
     query_img = cv2.imdecode(file_bytes, 0)
     
-    # Resim başarıyla okundu mu kontrolü
     if query_img is None:
         return None, 0
         
@@ -30,6 +37,10 @@ def predict_logo(uploaded_file):
     best_brand = None
 
     # Veri setini tara
+    if not os.path.exists(base_path):
+        st.error(f"Klasör bulunamadı! / Folder not found: {base_path}")
+        return None, 0
+
     for brand in os.listdir(base_path):
         brand_path = os.path.join(base_path, brand)
         if os.path.isdir(brand_path):
@@ -48,7 +59,7 @@ def predict_logo(uploaded_file):
 
     return best_brand, best_score
 
-# --- YÜKLEME VE GÖRÜNTÜLEME / UPLOAD & DISPLAY ---
+# --- ARAYÜZ / UI ---
 col_left, col_right = st.columns(2)
 
 with col_left:
@@ -63,15 +74,12 @@ if uploaded_file is not None:
 
     st.markdown("---")
     
-    # ANALİZ BUTONU / ANALYSIS BUTTON
     if st.button('Analiz Et / Analyze'):
         with st.spinner('İşleniyor... / Processing...'):
             brand, score = predict_logo(uploaded_file)
         
         if brand and score > 0.4:
-            # BAŞARI! BALONLAR / SUCCESS! BALLOONS
             st.balloons()
-            
             brand_clean = brand.split('-')[-1]
             
             res_col1, res_col2 = st.columns(2)