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app.py
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import streamlit as st
import pickle
import numpy as np
import requests
import streamlit.components.v1 as components
from streamlit_elements import elements, mui, html, sync
from streamlit_star_rating import st_star_rating
import pandas as pd
import pymongo
st.set_page_config(page_title="Movie Web", layout="wide")
st.header("Sản phẩm demo Web Application")
st.markdown("***")
poster_data = pd.read_csv("movie_poster.csv", names=["itemID", "url"])
movies = pickle.load(open("movie_list.pkl", 'rb'))
similarity = np.load("similarity.npy")
movies_list=movies['title'].values
#import top 15 popular movies
top15 = pd.read_csv('top15_popular.csv',delimiter=',')
# @st.cache()
# Hàm liên kết với mongodb
def get_collection(connection_str):
myclient = pymongo.MongoClient(connection_str)
mydb = myclient["result"]
mycol = mydb["06-12-2023"]
return mycol
# Hàm lấy hình ảnh - bổ sung thêm title các thứ
def fetchposter(movie_id):
url = str(poster_data[poster_data["itemID"] == movie_id]["url"].values[0])
return url
# Nhập userID
def fetch_img_url(id):
connection_str = "mongodb://longnguyenuit:ZkhrACfJflUhurRi1xUBFVLXMxNQrn2czSp5yHvomR4pvzmRPJX4niIdQT0FxdJCRVUtTx0eUkv4ACDbiTmXsQ%3D%3D@longnguyenuit.mongo.cosmos.azure.com:10255/?ssl=true&retrywrites=false&replicaSet=globaldb&maxIdleTimeMS=120000&appName=@longnguyenuit@"
res_collection = get_collection(connection_str)
# Duyệt qua từng dòng trên collection dựa trên userID, duyệt qua các movieID trong list 10 movieID
data = res_collection.find({"userID": id})
img_urls = []
for row in data:
for movieID in row["itemIDs"]:
try:
img_urls.append(fetchposter(movieID))
except: continue
return img_urls
def fetch_topmovies():
title = []
id = []
for i in top15['title']:
title.append(i)
for i in top15['id']:
id.append(fetch_poster(i))
return title,id
def fetch_poster(movie_id):
url = "https://api.themoviedb.org/3/movie/{}?api_key=c7ec19ffdd3279641fb606d19ceb9bb1&language=en-US".format(movie_id)
data=requests.get(url)
data= data.json()
poster_path = data['poster_path']
full_path = "https://image.tmdb.org/t/p/w500/"+poster_path
return full_path
# st.header("Recent hot movies")
st.subheader("Các bộ phim nổi tiếng gần đây")
imageCarouselComponent1 = components.declare_component("image-carousel-component", path="frontend/public")
top_title,top_id = fetch_topmovies()
top_poster=[]
for i in top_id:
top_poster.append(i)
# imageUrls = [
# fetch_poster(1632),
# fetch_poster(299536),
# fetch_poster(17455),
# fetch_poster(2830),
# fetch_poster(429422),
# fetch_poster(9722),
# fetch_poster(13972),
# fetch_poster(240),
# fetch_poster(155),
# fetch_poster(598),
# fetch_poster(914),
# fetch_poster(255709),
# fetch_poster(572154)
# ]
imageCarouselComponent1(imageUrls=top_poster, height=200)
st.markdown('***')
st.subheader('Đề xuất phim theo ID người dùng')
userID = st.number_input("Nhập vào id người dùng: ", min_value=1, max_value=6040, step=1)
# st.header("Recent hot movies")
imageCarouselComponent = components.declare_component("image-carousel-component", path="frontend/public")
image_urls = fetch_img_url(userID)
# imageUrls = [
# fetch_poster(1632),
# fetch_poster(299536),
# fetch_poster(17455),
# fetch_poster(2830),
# fetch_poster(429422),
# fetch_poster(9722),
# fetch_poster(13972),
# fetch_poster(240),
# fetch_poster(155),
# fetch_poster(598),
# fetch_poster(914),
# fetch_poster(255709),
# fetch_poster(572154)
# ]
imageCarouselComponent(imageUrls=image_urls, height=200)
st.markdown('***')
def recommend(movie):
index=movies[movies['title']== movie].index[0]
distance = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda vector:vector[1])
recommend_movie=[]
recommend_poster = []
recommend_genre = []
recommend_overview = []
recommend_vote = []
recommend_date = []
for i in distance[0:9]:
movies_id = movies.iloc[i[0]].id
recommend_movie.append(movies.iloc[i[0]].title)
recommend_genre.append(movies.iloc[i[0]].genre)
recommend_overview.append(movies.iloc[i[0]].overview)
recommend_vote.append(movies.iloc[i[0]].vote_average)
recommend_date.append(movies.iloc[i[0]].release_date)
recommend_poster.append(fetch_poster(movies_id))
return recommend_movie,recommend_poster,recommend_overview,recommend_genre,recommend_vote,recommend_date
# board, sidebar = st.columns((6,2))
# with board:
# Initialize session state
st.session_state.text = st.session_state.get('text', 'selectvalue')
st.subheader("Đề xuất phim dựa trên phim được chọn")
selectvalue=st.selectbox("Nhập hoặc tìm kiếm tên phim", movies_list)
st.session_state['text']=selectvalue
movie_name,movie_poster,movies_overview,movie_genre,movie_vote,movie_date = recommend(st.session_state['text'])
movie_1,movie_2 = st.columns(2)
with movie_1:
with elements(f'image'):
html.img(src=movie_poster[0], css={"display": "block","margin-left": "auto","margin-right": "auto", "width":"50%",})
with movie_2:
st.header(movie_name[0])
st_star_rating("",maxValue=10,defaultValue=movie_vote[0],key="rating",read_only=True,size=20)
st.write("""\n\n\n\n\n\n\n
""")
st.write("Thể loại: " + movie_genre[0])
st.write("Tóm tắt: " + movies_overview[0])
st.write("Ngày ra mắt: " + movie_date[0])
st.write("Đánh giá trung bình: " + movie_vote[0].astype("str"))
st.markdown("***")
if st.button("Đề xuất phim"):
movie_name,movie_poster,movies_overview,movie_genre,movie_vote,movie_date = recommend(st.session_state['text'])
col1,col2,col3,col4=st.columns(4)
with col1:
st.text(movie_name[1])
st.image(movie_poster[1])
with col2:
st.text(movie_name[2])
st.image(movie_poster[2])
with col3:
st.text(movie_name[3])
st.image(movie_poster[3])
with col4:
st.text(movie_name[4])
st.image(movie_poster[4])
with col1:
st.text(movie_name[5])
st.image(movie_poster[5])
with col2:
st.text(movie_name[6])
st.image(movie_poster[6])
with col3:
st.text(movie_name[7])
st.image(movie_poster[7])
with col4:
st.text(movie_name[8])
st.image(movie_poster[8])
# with sidebar:
# st.write("sidebar")
# top_title,top_id = fetch_topmovies()
# i = 0
# col1,col2,col3 = st.columns([1,2,2])
# with elements(f'top'):
# while(i<15):
# col1.write(i+1,unsafe_allow_html=True,)
# col2.image(top_id[i],width=20)
# col3.write(top_title[i])
# i = i + 1