large file

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+.pkl filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,48 @@
+import streamlit as st
+import pickle
+import pandas  as pd
+from PIL import Image
+import requests
+from bs4 import BeautifulSoup
+
+st.title('Game Recommendation System')
+
+game_list=pickle.load(open('games.pkl','rb'))
+similarity_list=pickle.load(open('similarities.pkl','rb'))
+games=pd.DataFrame(game_list)
+
+def game_recommender(game):
+    game_index=games[games['name']==game].index[0]
+    distances=sorted(list(enumerate(similarity_list[game_index])),reverse=True, key=lambda x:x[1])[1:10]
+    game_recs=[]
+    for i in distances:
+        game_recs.append(games.iloc[i[0]]['name'])
+    return game_recs
+    
+
+game_selected=st.selectbox('',(games['name']))
+
+
+if st.button('Recommend'):
+   
+    game_recs=game_recommender(game_selected)
+    for i in game_recs:
+        word = f'latest {i} video game cover photo'
+        url = 'https://www.google.com/search?q={0}&tbm=isch'.format(word)
+        content = requests.get(url).content
+        soup = BeautifulSoup(content,'lxml')
+        images = soup.findAll('img')
+        c=0
+        img_link=''
+        for image in images:
+            if c==1:
+                img_link=image.get('src')
+                break
+            c+=1
+
+        im = Image.open(requests.get(img_link, stream=True).raw)
+        st.header(i)
+        st.image(im)
+        
+
+

games.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2037db698235f5aa1ed7b1f1543342275bb6ff6abc8e81cbf87521ab95328f9
+size 1889758

similarities.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:27b4b32d6be09813d0627cab171a36444445f9c0445e23535c31a6b8d5a4b45c
+size 975406275