app.py added cover image UI improvements

app.py

@@ -1,70 +1,67 @@
-# Importing the librarires
 import streamlit as st
 import cv2
 import matplotlib.pyplot as plt
 from deepface import DeepFace
-import streamlit as st
-import test
 import spotipy
+
 from spotipy.oauth2 import SpotifyClientCredentials
+import streamlit as st
+import test
 import random
 
-
 client_id = '8be5f0367b7a4b54b730b33faa7c1b2c'
 client_secret = '0bc78da67fa44fe985c2586aa74d7e1d'
 
 client_credentials_manager = SpotifyClientCredentials(client_id, client_secret)
 sp = spotipy.Spotify(client_credentials_manager =client_credentials_manager)
 
-# Creating the containers
 header  = st.beta_container()
 inp = st.beta_container()
 pred = st.beta_container()
 
 with header:
+    st.image('background.png')
     st.title('Emotion Detection and Song Recommendation')
-    st.text('Aim : To detect the emotion of the person and predict a song')
+    st.markdown('**Aim : To detect the emotion of the person and predict a song**')
 
-# Captures user's face as input
 with inp:
-    st.title("Taking the user's face as input")
-    st.markdown("**Press 'C' to capture the image**")
+    st.title("Image Capture")
+    st.markdown("**Capturing an image of your face**")
     faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
     test.take_input()
 
-# Predicting the dominant emotion
 with pred:
-    st.title("Prediction")
+    st.title("Let's see what songs you should listen to !!")
     img = cv2.imread('photo.jpg')
 
     plt.imshow(cv2.cvtColor(img,cv2.COLOR_BGR2RGB))
 
     predictions = DeepFace.analyze(img)
 
-    emotion = predictions['dominant_emotion']
-
-    st.markdown("<b>You don't look very happy!</b> ")  
+    #st.text("Your emotion is {}".format(predictions['dominant_emotion']))  
 
-# Recommending songs based on the dominant emotion
     if(predictions['dominant_emotion'] != 'happy'):
 
-        playlist_id = '42EL4koTAevxJ4R8IT8OHJ'
-        #func to extract all track ids
+        st.markdown("**You don't look too cheerful....Here are some songs to lift your mood up!!**")
+        playlist_id = '37i9dQZF1DX9XIFQuFvzM4'
+
         def get_track_ids(playlist_id):
             music_id_list = []
             playlist = sp.playlist(playlist_id)
-            # creating a list of track ids of all the songs in the playlist
+
             for item in playlist['tracks']['items']:
                 music_track = item['track']
                 music_id_list.append(music_track['id'])
             return music_id_list
-        
+
         track_ids = get_track_ids(playlist_id)
 
-        # looping over the entire track_ids list and returning 5 random songs
         for i in range(5):
+
             random.shuffle(track_ids)
-            embed = '<iframe src="https://open.spotify.com/embed/track/{}" width="300" height="380" frameborder="0" allowtransparency="true" allow="encrypted-media"></iframe>'.format(track_ids[0])
 
-            st.markdown(embed, unsafe_allow_html=True)
+            my_html = '<iframe src="https://open.spotify.com/embed/track/{}" width="300" height="100" frameborder="0" allowtransparency="true" allow="encrypted-media"></iframe>'.format(track_ids[0])
+
+            st.markdown(my_html, unsafe_allow_html=True)
+