Upload app.py

app.py

@@ -0,0 +1,139 @@
+import streamlit as st
+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
+import sys
+from RecipeData import fetchRecipeData
+
+IMG_SIZE = (224, 224)
+model_V2 = 'efficientnet_b0.pt'
+model_V1 = 'indian_efficientnet_b0.pt'
+
+
+@st.cache()
+def model_prediction(model_path, img_file, rescale,selected_location):
+    input_img, device = load_prepare_img(img_file)
+    if(selected_location=='Outside_India'):
+        model = getmodel_outside_india(model_path)
+        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)
+    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
+        
+
+def main():
+    st.set_page_config(
+        page_title="SeeFood",
+        page_icon="🍔",
+        layout="wide",
+        initial_sidebar_state="expanded"
+    )
+
+    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)
+
+    with col1: 
+        # image uploading button
+        uploaded_file = st.file_uploader("Choose a file")
+        selected_location = st.selectbox('Select loaction',('India', 'Outside_India'), index=1)
+        if uploaded_file is not None:
+            display_img = uploaded_file.read()
+            uploaded_img = Image.open(uploaded_file)
+            col2.image(display_img, width=500)
+            
+            
+        
+
+       
+        predict = st.button('Get Recipe!')
+        
+        
+
+    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
+      
+                
+                # 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.warning('Please Upload Image')
+
+                
+
+
+if __name__=='__main__': 
+    main()