Update app.py

app.py

@@ -3,22 +3,31 @@ import numpy as np
 import time
 
 import tensorflow as tf
-from utils import load_prepare_image, model_pred, fetch_recipe
+from utils import load_prepare_image_tf, model_pred_tf, fetch_recipe, load_prepare_image_pt, model_pred_pt
 from FoodNoFood import food_not_food
 from PIL import Image
 
 import sys
+sys.path.insert(1, 'Api Data')
 from RecipeData import fetchRecipeData
 
 IMG_SIZE = (224, 224)
 model_V1 = 'Seefood_model_v1.tflite'
 model_V2 = 'Seefood_model_V2.tflite'
-
-@st.cache()
-def model_prediction(model, img_file, rescale):
-    img = load_prepare_image(img_file, IMG_SIZE, rescale=rescale)
-    prediction = model_pred(model, img)
-    sorceCode, recipe_data = fetchRecipeData(prediction)
+ViT_model = 'ViT-101-1.pt'
+
+@st.cache(show_spinner=False)
+def model_prediction(model, img_file, rescale, model_tensor_type):
+    if model_tensor_type == 'TF':
+        img = load_prepare_image_tf(img_file, IMG_SIZE, rescale=rescale)
+        prediction = model_pred_tf(model, img)
+        sorceCode, recipe_data = fetchRecipeData(prediction)
+    elif model_tensor_type == 'Pt':
+        img = load_prepare_image_pt(img_file)
+        prediction = model_pred_pt(img, model)
+        print(prediction)
+        sorceCode, recipe_data = fetchRecipeData(prediction)
+        
     return prediction, sorceCode, recipe_data 
 
 
@@ -33,17 +42,18 @@ def main():
     st.title('SeeFood🍔')
     st.write('Upload a food image and get the recipe for that food and other details of that food')
 
-    col1, col2 = st.columns(2)
+    col1, col2 = st.columns(2, gap='large')
 
     with col1: 
         # image uploading button
         uploaded_file = st.file_uploader("Choose a file")
-        selected_model = st.selectbox('Select Model',('model 1', 'model 2'), index=1)
+        selected_model = st.selectbox('Select Model',( 'ViT Model', 'model 1', 'model 2'), index=0)
+        
         if uploaded_file is not None:
             uploaded_img = uploaded_file.read()
             pil_img = Image.open(uploaded_file)
 
-            col2.image(uploaded_file, width=500)
+            col2.image(uploaded_file, width=700)
 
         # butoon to make predictions
         predict = st.button('Get Recipe!')
@@ -57,29 +67,37 @@ def main():
                 with st.spinner('Please Wait 👩‍🍳'):
 
                     # setting model and rescalling 
-                    if selected_model == 'model 2':
-                        pred_model = model_V2 
+                    if selected_model in ['model 1', 'model 2']:
+                        
+                        if selected_model == 'model 2':
+                            pred_model = model_V2 
+                            pred_rescale = True
+                        elif selected_model == 'model 1':
+                            pred_model = model_V1 
+                            pred_rescale = False
+                        
+                        # makeing prediction and fetching food recipe form api
+                        food, source_code, recipe_data = model_prediction(pred_model, uploaded_img, pred_rescale, 'TF')
+                        
+                    elif selected_model == 'ViT Model':
+                        pred_model = ViT_model 
                         pred_rescale = True
-                    else:
-                        pred_model = model_V1 
-                        pred_rescale = False
-                    
-                    # makeing prediction and fetching food recipe form api
-                    food, source_code, recipe_data = model_prediction(pred_model, uploaded_img, pred_rescale)
-                    
+                        # makeing prediction and fetching food recipe form api
+                        food, source_code, recipe_data = model_prediction(pred_model, pil_img, pred_rescale, 'Pt')
+                        
                     # asssigning caleoric breakdown data
                     percent_Protein = recipe_data['percentProtein']
                     percent_fat = recipe_data['percentFat']
                     percent_carbs = recipe_data['percentCarbs'] 
-                    
+                        
                     # food name message
                     col1.success(f"It's an {food}")
-                    
+                        
                     if source_code == 200:
                         # desplay food recipe
                         st.header(recipe_data['title']+" Recipe")
-                    
-                        col3, col4 = st.columns(2)
+                        
+                        col3, col4 = st.columns(2, gap='medium')
 
                         with col3:
                             # Ingridents of recipie
@@ -99,11 +117,12 @@ def main():
                                         * Protien:  {percent_Protein}%
                                         * Fat: {percent_fat}%
                                         * Carbohydrates: {percent_carbs}%
-                                        ''')
+                                    ''')
+                                
                             
-                        
                     else:
                         st.error('Something went wrong please try again :(')
+                    
                         
         elif food_cat == 'not food':
             with col1: