init

app.py

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+import streamlit as st
+import numpy as np
+import time
+
+import tensorflow as tf
+from utils import load_prepare_image, model_pred, fetch_recipe
+
+import sys
+sys.path.insert(1, 'Api Data')
+from RecipeData import fetchRecipeData
+
+IMG_SIZE = (224, 224)
+model_V1 = 'models/Seefood_model_v1.tflite'
+model_V2 = 'models/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)
+    return prediction, sorceCode, recipe_data 
+
+
+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_model = st.selectbox('Select Model',('model 1', 'model 2'), index=1)
+        if uploaded_file is not None:
+            uploaded_img = uploaded_file.read()
+
+            col2.image(uploaded_file, width=500)
+
+        # butoon to make predictions
+        predict = st.button('Get Recipe!')
+
+    if predict:
+        if uploaded_file is not None:
+            with st.spinner('Please Wait 👩‍🍳'):
+
+                # setting model and rescalling 
+                if selected_model == 'model 2':
+                    pred_model = model_V2 
+                    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)
+                
+                # 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()