commit

app.py

@@ -3,14 +3,11 @@ import numpy as np
 import time
 import PIL
 import PIL.Image as Image
-
-
-# from utils import make_pred_outside_india,getmodel_outside_india,load_prepare_img
 from utils import make_pred_outside_india
 from utils import getmodel_outside_india
 from utils import getmodel_india
 from utils import load_prepare_img
-from transformers import CLIPProcessor, CLIPModel
+from utils import food_nofood_pred
 import sys
 from RecipeData import fetchRecipeData
 
@@ -27,22 +24,11 @@ def model_prediction(model_path, img_file, rescale,selected_location):
         prediction = make_pred_outside_india(input_img, model, device, selected_location)
     elif(selected_location=='India'):
         model = getmodel_india(model_path)
+        
         prediction = make_pred_outside_india(input_img, model, device, selected_location)
+    print(prediction)
     sorceCode, recipe_data = fetchRecipeData(prediction)
-    return prediction, sorceCode, recipe_data 
-
-def food_pred(input_image):
-    # input labels for clip model
-        label = ['food ', 'Not food']
-
-        # CLIP Model for classification
-        model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
-        processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
-  
-        image = Image.open(requests.get(uploaded_file, stream=True).raw)
-        inputs = processor(text=label, images=image, return_tensors="pt", padding=True)
-        return inputs
-        
+    return prediction, sorceCode, recipe_data         
 
 def main():
     st.set_page_config(
@@ -76,59 +62,71 @@ def main():
 
     if predict:
         if uploaded_file is not None:
-            with st.spinner('Please Wait 👩‍🍳'):
-
-                # setting model and rescalling 
-                if selected_location == 'India':
-                    pred_model = model_V1 
-                    pred_rescale = True
-                if selected_location == 'Outside_India':
-                    pred_model = model_V2
-                    pred_rescale =True
-      
+            with st.spinner('getting image type'):
+                img_type=food_nofood_pred(uploaded_img)
+                print(img_type)
                 
-                # makeing prediction and fetching food recipe form api
-                food, source_code, recipe_data = model_prediction(pred_model, uploaded_img, pred_rescale,selected_location)
+            if(img_type=='food'):
                 
-                # 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)
-
-                    with col3:
-                        # Ingridents of recipie
-                        st.subheader('Ingredients')
-                        # st.info(recipe_data['ingridents'])
-                        for i in recipe_data['ingridents']:
-                            st.info(f"{i}")
-                    # Inctuction for recipe
-                    with col4:
-                        st.subheader('Instructions')
-                        st.info(recipe_data['instructions'])
-                        # st.subheader('Caloric Breakdown')
-                        '''
-                        ## Caloric Breakdown
-                        '''
-                        st.success(f'''
-                                    * Protien:  {percent_Protein}%
-                                    * Fat: {percent_fat}%
-                                    * Carbohydrates: {percent_carbs}%
-                                    ''')
+                with st.spinner('Please Wait 👩‍🍳'):
+
+                    # setting model and rescalling 
+                    if selected_location == 'India':
+                        pred_model = model_V1 
+                        pred_rescale = True
+                    if selected_location == 'Outside_India':
+                        pred_model = model_V2
+                        pred_rescale =True
+
+
+                    # makeing prediction and fetching food recipe form api
+                    food, source_code, recipe_data = model_prediction(pred_model, uploaded_img, pred_rescale,selected_location)
+
+                    # 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)
+
+                        with col3:
+                            # Ingridents of recipie
+                            st.subheader('Ingredients')
+                            # st.info(recipe_data['ingridents'])
+                            for i in recipe_data['ingridents']:
+                                st.info(f"{i}")
+                        # Inctuction for recipe
+                        with col4:
+                            st.subheader('Instructions')
+                            st.info(recipe_data['instructions'])
+                            # st.subheader('Caloric Breakdown')
+                            '''
+                            ## Caloric Breakdown
+                            '''
+                            st.success(f'''
+                                        * Protien:  {percent_Protein}%
+                                        * Fat: {percent_fat}%
+                                        * Carbohydrates: {percent_carbs}%
+                                        ''')
+
+
+                    else:
+                        st.error('Something went wrong please try again :(')
                         
-                       
-                else:
-                    st.error('Something went wrong please try again :(')
+            elif(img_type=='not food'):
+               
+                            # Ingridents of recipie
+                st.warning('This is not food image Please try again!!')
                 
 
+
         else:
             st.warning('Please Upload Image')