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foodreceipe
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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()