from PIL import Image from utils import * from app_utils import * debug = False dir_path = os.path.dirname(os.path.realpath(__file__)) # os.environ['FLASK_APP'] = dir_path + 'app2.py' # if debug: os.environ['FLASK_ENV'] = 'development' # # # app = Flask(__name__) # app.config['SECRET_KEY'] = os.urandom(64) # app.config['SESSION_TYPE'] = 'filesystem' # app.config['SESSION_FILE_DIR'] = './.flask_session/' # Session(app) st.set_page_config( page_title="EmotionPlaylist", page_icon="🎧", ) st.title('Customize Emotional Playlists') def setup_streamlite(): setup_credentials() print('Here1') image = Image.open(dir_path + '/image.png') st.image(image) st.markdown("This app let's you quickly build playlists in a customized way: ") st.markdown("* **It's easy**: you won't have to add songs one by one,\n" "* **You're in control**: you provide a source of candidate songs, select a list of genres and choose the mood for the playlist.") st.subheader("Step 1: Connect to your Spotify app") st.markdown("Log into your Spotify account to let the app create the custom playlist.") print('Here2') if 'login' not in st.session_state: sp, user_id = new_get_client(session=st.session_state) if sp != None: print("USER", user_id) legit_genres = sp.recommendation_genre_seeds()['genres'] st.session_state['login'] = (sp, user_id, legit_genres) # if 'login' not in st.session_state: # login = centered_button(st.button, 'Log in', n_columns=7) # if login or debug: # sp, user_id = get_client(session=st.session_state) # user_id = sp.me()['id'] # legit_genres = sp.recommendation_genre_seeds()['genres'] # st.session_state['login'] = (sp, user_id, legit_genres) if 'login' in st.session_state or debug: print('Here8') if not debug: sp, user_id, legit_genres = st.session_state['login'] st.success('You are logged in.') st.subheader("Step 2: Select candidate songs") st.markdown("This can be done in three ways: \n" "1. Get songs from a list of artists\n" "2. Get songs from a list of users (and their playlists)\n" "3. Get songs from a list of playlists.\n" "For this you'll need to collect the urls of artists, users and/or playlists by clicking on 'Share' and copying the urls." "You need to provide at least one source of music.") label_artist = "Add a list of artist urls, one per line (optional)" artists_links = st.text_area(label_artist, value="") users_playlists = "Add a list of users urls, one per line (optional)" users_links = st.text_area(users_playlists, value="") label_playlists = "Add a list of playlists urls, one per line (optional)" playlist_links = st.text_area(label_playlists, value="https://open.spotify.com/playlist/1H7a4q8JZArMQiidRy6qon?si=529184bbe93c4f73") button = centered_button(st.button, 'Extract music', n_columns=5) if button or debug: if playlist_links != "": playlist_uris = extract_uris_from_links(playlist_links, url_type='playlist') else: raise ValueError('Please enter a list of playlists') # Scanning playlists st.spinner(text="Scanning music sources..") data_tracks = get_all_tracks_from_playlists(sp, playlist_uris, verbose=True) st.success(f'{len(data_tracks.keys())} tracks found!') # Extract audio features st.spinner(text="Extracting audio features..") all_tracks_uris = np.array(list(data_tracks.keys())) all_audio_features = [data_tracks[uri]['track']['audio_features'] for uri in all_tracks_uris] all_tracks_audio_features = dict(zip(relevant_audio_features, [[audio_f[k] for audio_f in all_audio_features] for k in relevant_audio_features])) genres = dict() for index, uri in enumerate(all_tracks_uris): track = data_tracks[uri] track_genres = track['track']['genres'] for g in track_genres: if g not in genres.keys(): genres[g] = [index] else: genres[g].append(index) genres = aggregate_genres(genres, legit_genres) genres_labels = sorted(genres.keys()) st.success(f'Audio features extracted!') st.session_state['music_extracted'] = dict(all_tracks_uris=all_tracks_uris, all_tracks_audio_features=all_tracks_audio_features, genres=genres, genres_labels=genres_labels) if 'music_extracted' in st.session_state.keys(): all_tracks_uris = st.session_state['music_extracted']['all_tracks_uris'] all_tracks_audio_features = st.session_state['music_extracted']['all_tracks_audio_features'] genres = st.session_state['music_extracted']['genres'] genres_labels = st.session_state['music_extracted']['genres_labels'] st.subheader("Step 3: Customize it!") st.markdown("##### Which genres?") st.markdown("Check boxes to select genres, see how many tracks were selected below. Note: to check all, first uncheck all (bug).") columns = st.columns(np.ones(5)) with columns[1]: check_all = st.button('Check all') with columns[3]: uncheck_all = st.button('Uncheck all') if 'checkboxes' not in st.session_state.keys(): st.session_state['checkboxes'] = [True] * len(genres_labels) empty_checkboxes = wall_of_checkboxes(genres_labels, max_width=5) if check_all: st.session_state['checkboxes'] = [True] * len(genres_labels) if uncheck_all: st.session_state['checkboxes'] = [False] * len(genres_labels) for i_emc, emc in enumerate(empty_checkboxes): st.session_state['checkboxes'][i_emc] = emc.checkbox(genres_labels[i_emc], value=st.session_state['checkboxes'][i_emc]) # filter songs by genres selected_labels = [genres_labels[i] for i in range(len(genres_labels)) if st.session_state['checkboxes'][i]] genre_selected_indexes = [] for label in selected_labels: genre_selected_indexes += genres[label] genre_selected_indexes = np.array(sorted(set(genre_selected_indexes))) if len(genre_selected_indexes) < 10: st.warning('Please select more genres or add more music sources.') else: st.success(f'{len(genre_selected_indexes)} candidate tracks selected.') st.markdown("##### What's the mood?") valence = st.slider('Valence (0 negative, 100 positive)', min_value=0, max_value=100, value=100, step=1) / 100 energy = st.slider('Energy (0 low, 100 high)', min_value=0, max_value=100, value=100, step=1) / 100 danceability = st.slider('Danceability (0 low, 100 high)', min_value=0, max_value=100, value=100, step=1) / 100 target_mood = np.array([valence, energy, danceability]).reshape(1, 3) candidate_moods = np.array([np.array(all_tracks_audio_features[feature])[genre_selected_indexes] for feature in ['valence', 'energy', 'danceability']]).T distances = np.sqrt(((candidate_moods - target_mood) ** 2).sum(axis=1)) min_dist_indexes = np.argsort(distances) n_candidates = distances.shape[0] if n_candidates < 25: st.warning('Please add more music sources or select more genres.') else: playlist_length = st.number_input(f'Pick a playlist length, given {n_candidates} candidates.', min_value=5, value=min(10, n_candidates//5), max_value=n_candidates//5) selected_tracks_indexes = genre_selected_indexes[min_dist_indexes[:playlist_length]] selected_tracks_uris = all_tracks_uris[selected_tracks_indexes] np.random.shuffle(selected_tracks_uris) playlist_name = st.text_input('Playlist name', value='Mood Playlist') if playlist_name == '': st.warning('Please enter a playlist name.') else: generation_button = centered_button(st.button, 'Generate playlist', n_columns=5) if generation_button: description = f'Emotion Playlist for Valence: {valence}, Energy: {energy}, Danceability: {danceability}). ' \ f'Playlist generated by the EmotionPlaylist app: https://huggingface.co/spaces/ccolas/EmotionPlaylist.' playlist_info = sp.user_playlist_create(user_id, playlist_name, public=True, collaborative=False, description=description) playlist_uri = playlist_info['uri'].split(':')[-1] sp.playlist_add_items(playlist_uri, selected_tracks_uris) st.write( f"""
""", unsafe_allow_html=True) st.success(f'The playlist has been generated, find it [here](https://open.spotify.com/playlist/{playlist_uri}).') stop = 1 if __name__ == '__main__': setup_streamlite()