ESMATUGBA's picture
Update app.py
2686c63 verified
Raw
History Blame
5.18 kB
import streamlit as st
import pickle
from scipy import spatial
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 ---
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():
if any(isim.lower().replace(" ", "_") in d or isim.lower() in d for d in dosyalar):
mevcut_unlular[isim] = veri
return mevcut_unlular
unlu_verileri = klasordeki_unluleri_getir()
# --- ARAYÜZ ---
st.set_page_config(page_title="CastMatch AI", layout="wide")
st.sidebar.title("🔍 Control Panel / Kontrol Paneli")
gender_choice = st.sidebar.radio(
"Select Category / Kategori:",
["Male / Erkek", "Female / Kadın"]
)
filtered_names = [n for n, d in unlu_verileri.items() if d['c'] == gender_choice]
st.title("🎬 CastMatch AI")
col1, col2 = st.columns([1,2])
with col1:
selected_actor = st.selectbox("Actor / Oyuncu", filtered_names)
if selected_actor:
for f in os.listdir(resim_klasoru):
if selected_actor.lower().replace(" ","_") in f.lower():
st.image(os.path.join(resim_klasoru, f))
break
with col2:
if st.button("🚀 Match"):
actor_v = unlu_verileri[selected_actor]['v']
results = []
for i in movie_dict:
dist = spatial.distance.cosine(actor_v, movie_dict[i][1][:6])
results.append((movie_dict[i][0], dist))
top = sorted(results, key=lambda x: x[1])[:5]
for film, score in top:
pct = max(0, min(100, (1 - score) * 100))
st.write(f"{film} → %{round(pct,1)}")
st.progress(pct/100)