Update app.py

app.py

@@ -14,28 +14,26 @@ __class_name_to_number = {}
 __class_number_to_name = {}
 __model = None
 
-st.header("Welcome to Sports Person Classifier!")
-col1,col2,col3,col4,col5 = st.columns(5)
+st.header("Welcome to Indian Cricketers Classifier!")
+col1,col2,col3,col4,col5,col6 = st.columns(6)
 with col1: 
-    messi = cv2.imread("messi.jpeg")
-    #st.header("Lionel Messi")
-    st.image(messi,width=150, caption='Lionel Messi')
+    dhoni = cv2.imread("messi.jpeg")
+    st.image(dhoni,width=100, caption='MS Dhoni')
 with col2:
-    maria = cv2.imread("sharapova.jpeg")
-    #st.header("Maria Sharapova")
-    st.image(maria,width=150, caption='Maria Sharapova')
+    dravid = cv2.imread("sharapova.jpeg")
+    st.image(dravid,width=100, caption='Rahul Dravid')
 with col3:
-    roger = cv2.imread("federer.jpeg")
-    #st.header("Roger Federer")
-    st.image(roger,width=150, caption='Roger Federer')
+    sachin = cv2.imread("federer.jpeg")
+    st.image(sachin,width=100, caption='Sachin Tendulkar')
 with col4:
-    serena = cv2.imread("serena.jpeg")
-    #st.header("Serena Williams")
-    st.image(serena,width=150, caption='Serena Williams')
+    ganguly = cv2.imread("serena.jpeg")
+    st.image(ganguly,width=100, caption='Saurav Ganguly')
 with col5:
     virat = cv2.imread("virat.jpeg")
-    #st.header("Virat Kohli")
-    st.image(virat,width=150, caption='Virat Kohli')
+    st.image(virat,width=100, caption='Virat Kohli')
+with col5:
+    sehwag = cv2.imread("virat.jpeg")
+    st.image(sehwag,width=100, caption='Virendra Sehwag')
 
 
 
@@ -119,17 +117,17 @@ def get_cv2_image_from_base64_string(b64str):
     return img
 
 def load_saved_artifacts():
-    print("loading saved artifacts...start")
+    #print("loading saved artifacts...start")
     global __class_name_to_number
     global __class_number_to_name
 
-    with open("class_dictionary.json", "r") as f:
+    with open("class_cri_dictionary.json", "r") as f:
         __class_name_to_number = json.load(f)
         __class_number_to_name = {v:k for k,v in __class_name_to_number.items()}
 
     global __model
     if __model is None:
-        __model = joblib.load('saved_model.pkl') 
+        __model = joblib.load('cri_saved_model.pkl') 
     #st.text("loading saved artifacts...done")
     return True
 
@@ -163,30 +161,9 @@ if uploaded_image is not None:
             img = cv2.resize(img, (130, 130))
             
             result = classify_image(get_b64_test_image_for_virat(), display_image)
-            #st.text(result[0])
+            st.text(result[0])
+            
             
-            col6,col7 = st.columns(2)
-            with col6:
-                st.header("Uploded Image: ")
-                st.image(img,width=130, caption='Uploaded Image')
-            with col7:
-                celeb = result[0]['class']
-                st.header("Predicted Image: ")
-                if celeb == "lionel_messi":
-                    messi = cv2.imread("messi.jpeg")
-                    st.image(messi,width=150, caption='Lionel Messi')
-                elif celeb == "maria_sharapova":
-                    maria = cv2.imread("sharapova.jpeg")
-                    st.image(maria,width=150, caption='Maria Sharapova')
-                elif celeb == "roger_federer":
-                    roger = cv2.imread("federer.jpeg")
-                    st.image(roger,width=150, caption='Roger Federer')
-                elif celeb == "serena_williams":
-                    serena = cv2.imread("serena.jpeg")
-                    st.image(serena,width=150, caption='Serena Williams')
-                elif celeb == "virat_kohli":
-                    virat = cv2.imread("virat.jpeg")
-                    st.image(virat,width=150, caption='Virat Kohli')