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main_app.py
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import pickle,os
import streamlit as st
import requests
import pandas as pd
from PIL import Image
# st.set_page_config(layout="wide")
# import streamlit as st
# st.write('<style>div.block-container{padding-top:0rem;}</style>', unsafe_allow_html=True)
css='''
<style>
section.main > div {max-width:70rem}
div.block-container{padding-top:2rem;}
</style>
'''
st.markdown(css, unsafe_allow_html=True)
# recomendation
def fetchPoster(movie_id):
path = "posters/"+str(movie_id)+".jpg"
directory_path='posters/'
file_name = str(movie_id)+".jpg"
if os.path.exists(os.path.join(directory_path, file_name)):
file_path = os.path.join(directory_path, file_name)
image = Image.open(path)
return image
else:
return Image.open('posters/default-movie-poster.jpg')
def recommend(movie):
index = movies[movies['title'] == movie].index[0]
distances = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda x: x[1])
recommended_movie_names = []
recommended_movie_posters = []
for i in distances[1:6]:
# fetch the movie poster
movie_id = movies.iloc[i[0]].movie_id
recommended_movie_posters.append(fetchPoster(movie_id))
recommended_movie_names.append(movies.iloc[i[0]].title)
return recommended_movie_names,recommended_movie_posters
similarity = pickle.load(open('similarity.pkl','rb'))
movies = pd.read_csv('movie_list.csv')
movie_list = movies['title'].values
selected_movie = st.selectbox(
"Type or select a movie from the dropdown",
movie_list
)
# based on user's history
user_data = pd.read_csv("user_data.csv")
def userWatchHistory(movie, cols):
recommended_movie_user = []
recommended_movie_user_posters = []
for col,mov in zip(cols, movie):
index = user_data[user_data[col] == mov].index[0]
distances = sorted(list(enumerate(user_history_similarity[index])),reverse=True,key = lambda x: x[1])
for i in distances[1:6]:
recommended_movie_user.append(movies.iloc[i[0]].title)
# recommended_movie_user_posters.append(fetch_poster(movies.iloc[i[0]].movie_id))
recommended_movie_user_posters.append(fetchPoster(movies.iloc[i[0]].movie_id))
# print(user_data.iloc[i[0]].watch_history1,user_data.iloc[i[0]].watch_history2,user_data.iloc[i[0]].watch_history3)
return recommended_movie_user,recommended_movie_user_posters
user_history_similarity = pickle.load(open('user_history_similarity.pkl','rb'))
user_list = user_data['user_id'].values
select_user = st.selectbox(
"select user's ID",
user_list
)
user_data1 = user_data.set_index('user_id')
mov1 = user_data1.loc[select_user,'watch_history1']
mov2 = user_data1.loc[select_user,'watch_history2']
mov3 = user_data1.loc[select_user,'watch_history3']
recommended_movie_user,recommended_movie_user_posters = userWatchHistory([mov1, mov2,mov3],['watch_history1','watch_history2','watch_history3'])
# top genres
top_gnr = pd.read_csv("top_genres.csv").head(5)
top_gnr.drop("Unnamed: 0", inplace=True, axis=1)
top_gnr_poster_list = []
top_gnr_title_list = []
for i in range(len(top_gnr)):
top_gnr_poster_list.append(fetchPoster(top_gnr.iloc[i]['movie_id']))
top_gnr_title_list.append(top_gnr.iloc[i]['title'])
# top trending movies
top_mov = pd.read_csv("top_trend_mov.csv")
top_mov_poster_list = []
top_mov_title_list = []
for i in range(5):
top_mov_poster_list.append(fetchPoster(top_mov.iloc[i]['movie_id']))
top_mov_title_list.append(top_mov.iloc[i]['title'])
# webpage
if st.button('Show Recommendation'):
recommended_movie_names,recommended_movie_posters = recommend(selected_movie)
searched_movie_id = movies[movies['title'] == selected_movie]['movie_id'].values[0]
searched_movie_poster = fetchPoster(searched_movie_id)
st.subheader(
"Results based on search"
)
st.image(searched_movie_poster, caption=selected_movie,width=220)
st.subheader(
"Recomendation similar to {}".format(selected_movie)
)
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
# image = Image.open('posters/10733.jpg')
# st.image(image, caption='Sunrise by the mountains')
st.image(recommended_movie_posters[0],caption=recommended_movie_names[0])
with col2:
st.image(recommended_movie_posters[1],caption=recommended_movie_names[1])
with col3:
st.image(recommended_movie_posters[2],caption=recommended_movie_names[2])
with col4:
st.image(recommended_movie_posters[3],caption=recommended_movie_names[3])
with col5:
st.image(recommended_movie_posters[4],caption=recommended_movie_names[4])
st.subheader(
"For you:"
)
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
# image = Image.open('posters/10733.jpg')
# st.image(image, caption='Sunrise by the mountains')
st.image(recommended_movie_user_posters[0],caption=recommended_movie_user[0])
with col2:
st.image(recommended_movie_user_posters[1],caption=recommended_movie_user[1])
with col3:
st.image(recommended_movie_user_posters[2],caption=recommended_movie_user[2])
with col4:
st.image(recommended_movie_user_posters[3],caption=recommended_movie_user[3])
with col5:
st.image(recommended_movie_user_posters[4],caption=recommended_movie_user[4])
st.subheader(
"Recomendation based on Top Genres!"
)
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
st.image(top_gnr_poster_list[0],caption=top_gnr_title_list[0])
with col2:
st.image(top_gnr_poster_list[1],caption=top_gnr_title_list[1])
with col3:
st.image(top_gnr_poster_list[2],caption=top_gnr_title_list[2])
with col4:
st.image(top_gnr_poster_list[3],caption=top_gnr_title_list[3])
with col5:
st.image(top_gnr_poster_list[4],caption=top_gnr_title_list[4])
st.subheader(
"Top Trending:"
)
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
st.image(top_mov_poster_list[0],caption=top_mov_title_list[0])
with col2:
st.image(top_mov_poster_list[1],caption=top_mov_title_list[1])
with col3:
st.image(top_mov_poster_list[2],caption=top_mov_title_list[2])
with col4:
st.image(top_mov_poster_list[3],caption=top_mov_title_list[3])
with col5:
st.image(top_mov_poster_list[4],caption=top_mov_title_list[4])