Update app.py

app.py

@@ -1,109 +1,22 @@
-import streamlit as st
-import pickle
-from scipy.spatial.distance import cosine
-import os
+if st.button("🚀 Match and Recommend / Eşleştir ve Öner") and selected_actor != "Yok":
+    if movie_dict:
+        actor_v = unlu_verileri[selected_actor]['v']
+        results = []
 
-# -------------------------------
-# 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
+        for i in movie_dict:
+            dist = spatial.distance.cosine(actor_v, movie_dict[i][1][:6])
 
-model_data = load_data()
-movie_dict = model_data['movie_dict'] if model_data else {}
+            # skor = benzerlik yüzdesi
+            score = (1 - dist) * 100
 
-# -------------------------------
-# 2. AKTÖR DNA VERİLERİ
-# -------------------------------
-actors = {
-    "Sylvester Stallone": {"gender": "Male", "vec": [0.9,0.2,0.1,0.1,0.1,0.8]},
-    "Robert De Niro": {"gender": "Male", "vec": [0.2,0.1,0.1,0.9,0.1,0.8]},
-    "Johnny Depp": {"gender": "Male", "vec": [0.1,0.9,0.8,0.4,0.1,0.1]},
-    "Jason Statham": {"gender": "Male", "vec": [0.95,0.3,0.1,0.1,0.1,0.7]},
-    "Keanu Reeves": {"gender": "Male", "vec": [0.9,0.4,0.1,0.2,0.9,0.6]},
-    "Angelina Jolie": {"gender": "Female", "vec": [0.9,0.7,0.1,0.8,0.1,0.6]},
-    "Scarlett Johansson": {"gender": "Female", "vec": [0.9,0.6,0.2,0.7,0.8,0.5]},
-    "Meryl Streep": {"gender": "Female", "vec": [0.1,0.1,0.4,0.95,0.1,0.1]},
-    "Jennifer Lawrence": {"gender": "Female", "vec": [0.7,0.8,0.3,0.9,0.4,0.2]}
-}
+            results.append((movie_dict[i][0], score))
 
-# -------------------------------
-# 3. RESİM KLASÖRÜ
-# -------------------------------
-image_folder = "40 resim"
+        top_matches = sorted(results, key=lambda x: x[1], reverse=True)[:5]
 
-def get_actor_image(name):
-    if not os.path.exists(image_folder):
-        return None
-    for f in os.listdir(image_folder):
-        if name.lower().replace(" ", "_") in f.lower():
-            return os.path.join(image_folder, f)
-    return None
-
-# -------------------------------
-# 4. STREAMLIT UI
-# -------------------------------
-st.set_page_config(page_title="CastMatch AI", layout="wide")
-
-st.title("🎬 CastMatch AI")
-st.markdown("### Actor → Movie Matching System")
-st.markdown("Oyuncuya en uygun filmi bulur / Finds best movie for actor")
-
-# Sidebar
-gender = st.sidebar.radio("Select Gender / Cinsiyet", ["Male", "Female"])
-
-filtered = [a for a in actors if actors[a]["gender"] == gender]
-
-actor_name = st.selectbox("Choose Actor / Oyuncu Seç", filtered)
-
-col1, col2 = st.columns(2)
-
-# -------------------------------
-# 5. AKTÖR GÖSTER
-# -------------------------------
-with col1:
-    st.subheader("Actor / Oyuncu")
-
-    img_path = get_actor_image(actor_name)
-    if img_path:
-        st.image(img_path, use_container_width=True)
+        for i, (film, score) in enumerate(top_matches, 1):
+            pct = round(score, 1)
+            st.success(f"**{i}. {film}**")
+            st.write(f"Match Score / Uyum Skoru: **%{pct}**")
+            st.progress(pct / 100)
     else:
-        st.warning("Image not found")
-
-# -------------------------------
-# 6. ÖNERİ SİSTEMİ
-# -------------------------------
-with col2:
-    st.subheader("Best Matches / En İyi Eşleşmeler")
-
-    if st.button("Recommend / Öner"):
-        if not movie_dict:
-            st.error("Model bulunamadı!")
-        else:
-            actor_vec = actors[actor_name]["vec"]
-
-            results = []
-
-            for i in movie_dict:
-                movie_vec = movie_dict[i][1][:6]
-
-                # COSINE DISTANCE (DAHA STABİL)
-                dist = cosine(actor_vec, movie_vec)
-
-                # SCORE (0-100)
-                score = (1 - dist) * 100
-
-                results.append((movie_dict[i][0], score))
-
-            # EN İYİ 5
-            results = sorted(results, key=lambda x: x[1], reverse=True)[:5]
-
-            for i, (movie, score) in enumerate(results, 1):
-                st.write(f"### {i}. {movie}")
-                st.write(f"Score: %{round(score,2)}")
-                st.progress(score / 100)
+        st.error("Model dosyası eksik! / Model file missing!")