W3.CSS

import streamlit as st import streamlit.components.v1 as components from PIL import Image import os import glob import random from random import shuffle import requests import time from multiprocessing import Process import json def load_image(image_file): img = Image.open(image_file) return img def start_server(): os.system("uvicorn InferenceServer:app --port 8080 --host 0.0.0.0 --workers 3") def load_models(): if not is_port_in_use(8080): with st.spinner(text="Loading models, please wait..."): proc = Process(target=start_server, args=(), daemon=True) proc.start() while not is_port_in_use(8080): time.sleep(1) st.success("Model server started.") else: st.success("Model server already running...") st.session_state['models_loaded'] = True def is_port_in_use(port): import socket with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: return s.connect_ex(('0.0.0.0', port)) == 0 def run_search(food_image): get_request = "http://0.0.0.0:8080/food?food_input="+food_image food_response = requests.get(get_request) food_response_obj = json.loads(food_response.text) results = food_response_obj["top3"] st.markdown("
", unsafe_allow_html=True) with col2: st.markdown("Top 3 predictions ", unsafe_allow_html=True) results_static_tag = 'W3.CSS

{}

' result_rows = "" for i, result in enumerate(results): results_dynamic_tag= '{}

' if i == 0: results_dynamic_tag = results_dynamic_tag.format("" + str(i+1) + "." + result[0].title() + "", 'w3-blue', result[1] * 100) else: results_dynamic_tag = results_dynamic_tag.format(str(i+1) + "." + result[0].title(), "w3-orange" ,result[1] * 100) result_rows += results_dynamic_tag results_static_tag = results_static_tag.format(result_rows) st.markdown(results_static_tag, unsafe_allow_html=True) recipe_response_obj = food_response_obj["recipe"] recipe_name = recipe_response_obj['recipe_name'] highlighted_ingredients =recipe_response_obj['highlighted_ingredients'] recipe = recipe_response_obj['recipe'] source = recipe_response_obj['source'] nutritional_facts = recipe_response_obj['nutritional_facts'] title_tag = '

Recipe for top result: ' + recipe_name + '

' st.markdown(title_tag, unsafe_allow_html=True) ing_hdr_tag = '

Ingredients

' ing_style= "{border: 3x outset white; background-color: #ccf5ff; color: black; text-align: left; font-size: 14px; padding: 5px;}" ing_tag = '

{}

' ing_tag = ing_tag.format(ing_style, highlighted_ingredients.strip()) st.markdown(ing_hdr_tag, unsafe_allow_html=True) st.markdown(ing_tag + "
", unsafe_allow_html=True) rec_hdr_tag = '

Recipe

' rec_style= "{border: 3x outset white; background-color: #ffeee6; color: black; text-align: left; font-size: 14px; padding: 5px;}" rec_tag = '

{}

' rec_tag = rec_tag.format(rec_style, recipe.strip()) st.markdown(rec_hdr_tag, unsafe_allow_html=True) st.markdown(rec_tag + "
", unsafe_allow_html=True) nut_hdr_tag = '

Nutritional facts

' nut_style= "{border: 3x outset white; background-color: #e6e6ff; color: black; text-align: left; font-size: 14px; padding: 5px;}" nut_tag = '

{}

' nut_tag = nut_tag.format(nut_style, nutritional_facts.strip()) st.markdown(nut_hdr_tag, unsafe_allow_html=True) st.markdown(nut_tag + "
", unsafe_allow_html=True) src_hdr_tag = '

Recipe source

' src_tag = '{}' src_tag = src_tag.format(source, source) st.markdown(src_hdr_tag, unsafe_allow_html=True) st.markdown(src_tag + "
", unsafe_allow_html=True) return 1 if 'models_loaded' not in st.session_state: st.session_state['models_loaded'] = False st.title('WTF - What The Food 🤬') st.subheader("Image to Recipe - 1.5M foods supported") st.markdown("Built for fun with 💙 by a quintessential foodie - Prithivi Da, The maker of [Gramformer](https://github.com/PrithivirajDamodaran/Gramformer), [Styleformer](https://github.com/PrithivirajDamodaran/Styleformer) and [Parrot paraphraser](https://github.com/PrithivirajDamodaran/Parrot_Paraphraser) | ✍️ [@prithivida](https://twitter.com/prithivida) |[[GitHub]](https://github.com/PrithivirajDamodaran)", unsafe_allow_html=True) st.markdown(""" (Read Me: The idea: Food Image => Recipe. So it works on single foods and platters
but May Not perform well on custom combinations or hyper-local foods. (NOT intended for commercial use.)
) """, unsafe_allow_html=True) if __name__ == '__main__': if not st.session_state['models_loaded']: load_models() random_button = st.button('⚡ Try a Random Food') st.write("(or)") st.info('Upload a HD, landscape image') image_file = st.file_uploader("", type=["jpg","jpeg"]) col1, col2 = st.columns(2) if random_button: with st.spinner(text="Detecting food..."): samples = glob.glob('./samples' + "/*") shuffle(samples) random_sample = random.choice(samples) pil_image = load_image(random_sample) with col1: st.image(pil_image, use_column_width='auto') return_code = run_search(random_sample) else: if image_file is not None: pil_image = load_image(image_file) with open(image_file.name, 'wb') as f: pil_image.save(f) with col1: st.image(pil_image, use_column_width='auto') with st.spinner(text="Detecting food..."): return_code = run_search(image_file.name) os.system('rm -r "' + image_file.name + '"')