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@@ -33,3 +33,36 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Al_Pacino.jpg filter=lfs diff=lfs merge=lfs -text
+Angelina_Jolie.jpg filter=lfs diff=lfs merge=lfs -text
+Anne_Hathaway.jpg filter=lfs diff=lfs merge=lfs -text
+Anthony[[:space:]]Hopkins.png filter=lfs diff=lfs merge=lfs -text
+Arnold_Schwarzenegger.jpg filter=lfs diff=lfs merge=lfs -text
+Brad_Pitt.jpg filter=lfs diff=lfs merge=lfs -text
+Bruce_Willis.jpg filter=lfs diff=lfs merge=lfs -text
+Charlize_Theron.jpg filter=lfs diff=lfs merge=lfs -text
+Christian_Bale.jpg filter=lfs diff=lfs merge=lfs -text
+Daniel_Radcliffe.jpg filter=lfs diff=lfs merge=lfs -text
+Denzel_Washington.jpg filter=lfs diff=lfs merge=lfs -text
+Dwayne_Johnson.jpg filter=lfs diff=lfs merge=lfs -text
+Hugh_Jackman.jpg filter=lfs diff=lfs merge=lfs -text
+Jackie_Chan.jpg filter=lfs diff=lfs merge=lfs -text
+Jason_Statham.jpg filter=lfs diff=lfs merge=lfs -text
+Jennifer_Aniston.jpg filter=lfs diff=lfs merge=lfs -text
+Johnny_Depp.jpg filter=lfs diff=lfs merge=lfs -text
+Julia_Roberts.jpg filter=lfs diff=lfs merge=lfs -text
+Kate_Winslet.jpg filter=lfs diff=lfs merge=lfs -text
+Keanu_Reeves.jpg filter=lfs diff=lfs merge=lfs -text
+Leonardo_DiCaprio.jpg filter=lfs diff=lfs merge=lfs -text
+Liam_Neeson.jpg filter=lfs diff=lfs merge=lfs -text
+Meryl_Streep.jpg filter=lfs diff=lfs merge=lfs -text
+Morgan_Freeman.jpg filter=lfs diff=lfs merge=lfs -text
+Nicole_Kidman.jpg filter=lfs diff=lfs merge=lfs -text
+Penelope_Cruz.jpg filter=lfs diff=lfs merge=lfs -text
+Robert_De_Niro.jpg filter=lfs diff=lfs merge=lfs -text
+Sandra_Bullock.jpg filter=lfs diff=lfs merge=lfs -text
+Scarlett_Johansson.jpg filter=lfs diff=lfs merge=lfs -text
+Sylvester[[:space:]]Stallone.png filter=lfs diff=lfs merge=lfs -text
+Tom_Cruise.jpg filter=lfs diff=lfs merge=lfs -text
+Tom_Hanks.jpg filter=lfs diff=lfs merge=lfs -text
+Will_Smith.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,144 @@
+import streamlit as st
+import pickle
+from scipy import spatial
+import random
+import os
+
+# 1. MODELİ YÜKLE
+@st.cache_resource
+def load_data():
+    try:
+        with open('movie_model.pkl', 'rb') as f:
+            return pickle.load(f)
+    except:
+        return None
+
+model_data = load_data()
+movie_dict = model_data['movie_dict'] if model_data else {}
+
+# 2. TÜM OYUNCU DNA VERİTABANI
+tum_unlu_verileri = {
+    "Sylvester Stallone": {"c": "Male / Erkek", "v": [0.9, 0.2, 0.1, 0.1, 0.1, 0.8]},
+    "Robert De Niro": {"c": "Male / Erkek", "v": [0.2, 0.1, 0.1, 0.9, 0.1, 0.8]},
+    "Johnny Depp": {"c": "Male / Erkek", "v": [0.1, 0.9, 0.8, 0.4, 0.1, 0.1]},
+    "Jason Statham": {"c": "Male / Erkek", "v": [0.95, 0.3, 0.1, 0.1, 0.1, 0.7]},
+    "Keanu Reeves": {"c": "Male / Erkek", "v": [0.9, 0.4, 0.1, 0.2, 0.9, 0.6]},
+    "Brad Pitt": {"c": "Male / Erkek", "v": [0.7, 0.5, 0.3, 0.8, 0.2, 0.4]},
+    "Tom Cruise": {"c": "Male / Erkek", "v": [0.9, 0.8, 0.2, 0.1, 0.4, 0.5]},
+    "Anthony Hopkins": {"c": "Male / Erkek", "v": [0.1, 0.1, 0.1, 0.95, 0.1, 0.9]},
+    "Arnold Schwarzenegger": {"c": "Male / Erkek", "v": [0.95, 0.6, 0.2, 0.1, 0.8, 0.1]},
+    "Bruce Willis": {"c": "Male / Erkek", "v": [0.9, 0.2, 0.1, 0.3, 0.4, 0.7]},
+    "Christian Bale": {"c": "Male / Erkek", "v": [0.8, 0.2, 0.1, 0.9, 0.1, 0.7]},
+    "Tom Hanks": {"c": "Male / Erkek", "v": [0.2, 0.6, 0.5, 0.9, 0.1, 0.1]},
+    "Morgan Freeman": {"c": "Male / Erkek", "v": [0.1, 0.3, 0.1, 0.9, 0.1, 0.6]},
+    "Al Pacino": {"c": "Male / Erkek", "v": [0.2, 0.1, 0.1, 0.95, 0.1, 0.8]},
+    "Cillian Murphy": {"c": "Male / Erkek", "v": [0.4, 0.1, 0.1, 0.9, 0.4, 0.8]},
+    "Jackie Chan": {"c": "Male / Erkek", "v": [0.9, 0.7, 0.9, 0.1, 0.1, 0.1]},
+    "Denzel Washington": {"c": "Male / Erkek", "v": [0.8, 0.2, 0.1, 0.9, 0.1, 0.7]},
+    "George Clooney": {"c": "Male / Erkek", "v": [0.3, 0.4, 0.5, 0.8, 0.1, 0.6]},
+    "Jake Gyllenhaal": {"c": "Male / Erkek", "v": [0.6, 0.1, 0.1, 0.9, 0.2, 0.8]},
+    "Pierce Brosnan": {"c": "Male / Erkek", "v": [0.8, 0.7, 0.3, 0.4, 0.1, 0.6]},
+    "Angelina Jolie": {"c": "Female / Kadın", "v": [0.9, 0.7, 0.1, 0.8, 0.1, 0.6]},
+    "Natalie Portman": {"c": "Female / Kadın", "v": [0.3, 0.2, 0.1, 0.9, 0.6, 0.7]},
+    "Scarlett Johansson": {"c": "Female / Kadın", "v": [0.9, 0.6, 0.2, 0.7, 0.8, 0.5]},
+    "Charlize Theron": {"c": "Female / Kadın", "v": [0.8, 0.3, 0.1, 0.9, 0.2, 0.7]},
+    "Milla Jovovich": {"c": "Female / Kadın", "v": [0.9, 0.4, 0.1, 0.1, 0.9, 0.3]},
+    "Sandra Bullock": {"c": "Female / Kadın", "v": [0.2, 0.1, 0.9, 0.8, 0.1, 0.6]},
+    "Nicole Kidman": {"c": "Female / Kadın", "v": [0.1, 0.2, 0.1, 0.95, 0.1, 0.7]},
+    "Jennifer Lawrence": {"c": "Female / Kadın", "v": [0.7, 0.8, 0.3, 0.9, 0.4, 0.2]},
+    "Meryl Streep": {"c": "Female / Kadın", "v": [0.1, 0.1, 0.4, 0.95, 0.1, 0.1]},
+    "Salma Hayek": {"c": "Female / Kadın", "v": [0.6, 0.3, 0.5, 0.8, 0.1, 0.1]},
+    "Anne Hathaway": {"c": "Female / Kadın", "v": [0.2, 0.7, 0.8, 0.8, 0.1, 0.1]},
+    "Keira Knightley": {"c": "Female / Kadın", "v": [0.1, 0.8, 0.1, 0.95, 0.1, 0.1]},
+    "Julia Roberts": {"c": "Female / Kadın", "v": [0.1, 0.2, 0.9, 0.9, 0.1, 0.1]},
+    "Penelope Cruz": {"c": "Female / Kadın", "v": [0.2, 0.3, 0.6, 0.9, 0.1, 0.6]},
+    "Monica Bellucci": {"c": "Female / Kadın", "v": [0.6, 0.1, 0.1, 0.8, 0.5, 0.3]},
+    "Emily Blunt": {"c": "Female / Kadın", "v": [0.7, 0.6, 0.1, 0.8, 0.5, 0.6]},
+    "Cameron Diaz": {"c": "Female / Kadın", "v": [0.1, 0.2, 0.95, 0.7, 0.1, 0.1]}
+}
+
+# --- DİNAMİK FİLTRELEME (KLASÖRE GÖRE) ---
+resim_klasoru = os.path.join(os.getcwd(), "40 resim")
+
+def klasordeki_unluleri_getir():
+    mevcut_unlular = {}
+    if os.path.exists(resim_klasoru):
+        dosyalar = [f.lower() for f in os.listdir(resim_klasoru)]
+        for isim, veri in tum_unlu_verileri.items():
+            search_pattern1 = isim.lower().replace(" ", "_")
+            search_pattern2 = isim.lower()
+            if any(search_pattern1 in d or search_pattern2 in d for d in dosyalar):
+                mevcut_unlular[isim] = veri
+    return mevcut_unlular
+
+unlu_verileri = klasordeki_unluleri_getir()
+
+# --- ARAYÜZ AYARLARI ---
+st.set_page_config(page_title="CastMatch AI", layout="wide")
+
+# --- SOL PANEL (SIDEBAR) ---
+st.sidebar.title("🔍 Control Panel / Kontrol Paneli")
+st.sidebar.markdown("---")
+
+gender_choice = st.sidebar.radio(
+    "1. Select Category / Kategori Seçin:",
+    ["Male / Erkek", "Female / Kadın"]
+)
+
+filtered_names = [name for name, data in unlu_verileri.items() if data['c'] == gender_choice]
+
+st.sidebar.markdown(f"### 📋 Available Cast / Mevcut Oyuncular")
+if not filtered_names:
+    st.sidebar.warning("Bu kategoride resim bulunamadı. / No images in this category.")
+for n in filtered_names:
+    st.sidebar.write(f"• {n}")
+
+# --- ANA EKRAN ---
+st.title("🎬 CastMatch AI: Talent Matching System / Yetenek Eşleştirme Sistemi")
+st.markdown("#### Discover the perfect roles for global stars! / Dünya yıldızları için en ideal rolleri keşfedin!")
+st.markdown("---")
+
+col_actor, col_match = st.columns([1, 2])
+
+with col_actor:
+    st.subheader("👤 Pick an Actor / Oyuncu Seç")
+    selected_actor = st.selectbox("Select from list / Listeden seçin:", filtered_names if filtered_names else ["Yok"])
+    
+    if selected_actor != "Yok":
+        found_path = None
+        search_target = selected_actor.replace(" ", "_").lower()
+        for f in os.listdir(resim_klasoru):
+            if f.lower().startswith(search_target) or selected_actor.lower() in f.lower():
+                found_path = os.path.join(resim_klasoru, f)
+                break
+        
+        if found_path:
+            st.image(found_path, caption=f"Profile: {selected_actor}", use_container_width=True)
+        else:
+            st.error("Resim yüklenemedi. / Image could not be loaded.")
+
+with col_match:
+    st.subheader("🎯 Best Career Matches / En İyi Kariyer Eşleşmeleri")
+    st.write("Comparing the star's DNA with movie roles... / Yıldızın DNA'sı film rolleriyle karşılaştırılıyor...")
+    
+    if st.button("🚀 Match and Recommend / Eşleştir ve Öner") and selected_actor != "Yok":
+        if movie_dict:
+            actor_v = unlu_verileri[selected_actor]['v']
+            results = []
+            for i in movie_dict:
+                noise = random.uniform(0, 0.0001)
+                dist = spatial.distance.cosine(actor_v, movie_dict[i][1][:6]) + noise
+                results.append((movie_dict[i][0], dist))
+            
+            top_matches = sorted(results, key=lambda x: x[1])[:5]
+            for i, (film, score) in enumerate(top_matches, 1):
+                pct = round((1 - score) * 100, 1)
+                st.success(f"**{i}. {film}**")
+                st.write(f"Match Score / Uyum Skoru: **%{pct}**")
+                st.progress(pct / 100)
+        else:
+            st.error("Model dosyası eksik! / Model file missing!")
+
+st.markdown("---")
+# EN ALT BİLGİ NOTU DÜZELTİLDİ:
+st.info("💡 **How it works? / Nasıl çalışır?**: This AI analyzes career vectors based on available local assets. / Bu yapay zeka, mevcut yerel varlıklara (resimlere) dayanarak kariyer vektörlerini analiz eder.")

movie_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f23c6434420084b031d8c85df1038cde40522ac379d98b43b1e5ab7b1120ba95
+size 511551