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app.py

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+import streamlit as st
+from PIL import Image
+import torch
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+import pandas as pd
+
+st.set_page_config(
+    page_title="CALIX",
+    page_icon="apple",
+    layout="centered",
+    initial_sidebar_state="collapsed"
+)
+
+# === MAKE IT A PHONE APP ===
+st.markdown("""
+<meta name="apple-mobile-web-app-capable" content="yes">
+<meta name="apple-mobile-web-app-status-bar-style" content="black">
+<meta name="apple-mobile-web-app-title" content="CALIX">
+<link rel="manifest" href="/manifest.json">
+""", unsafe_allow_html=True)
+
+# === DARK THEME ===
+st.markdown("""
+<style>
+    body, .stApp {background:#121212 !important; color:#FFF !important;}
+    .stTextInput input {background:#1E1E1E !important; color:#FFF !important; border:1px solid #444 !important;}
+    .stFileUploader > div {background:#1E1E1E !important; border:2px dashed #444 !important;}
+    .stButton>button {background:#FF9800; color:white; border-radius:20px; padding:10px 24px; font-weight:bold;}
+    .stButton>button:hover {background:#F57C00;}
+    .nav {background:#1E1E1E; padding:15px; box-shadow:0 2px 10px rgba(0,0,0,0.3); display:flex; justify-content:center; flex-wrap:wrap; margin-bottom:20px;}
+    .logo {font-size:32px; color:#4CAF50; font-weight:bold; margin-right:30px;}
+    .link {margin:0 15px; color:#BBB; text-decoration:none; padding:8px 16px; border-radius:8px;}
+    .link:hover {background:#333; color:#4CAF50;}
+    .card {background:#1E1E1E; padding:25px; border-radius:12px; border:1px solid #333; margin:15px 0;}
+    .title {color:#4CAF50; font-size:42px; text-align:center; margin:30px 0;}
+    .footer {text-align:center; color:#666; font-size:14px; margin-top:60px; padding:15px; border-top:1px solid #333;}
+    .nav-btn {background:#333; color:#FFF; padding:8px 16px; border-radius:8px; border:none; margin:0 5px;}
+    .nav-btn:hover {background:#555;}
+    .stDataFrame td, .stDataFrame th {color:#FFF !important; background:#1E1E1E !important;}
+</style>
+""", unsafe_allow_html=True)
+
+# === FOOTER ===
+def footer():
+    st.markdown('<div class="footer">©2025 CALIX|AMC CSE-AIML|Open Source Powered</div>', unsafe_allow_html=True)
+
+# === NAV BAR ===
+def nav_bar():
+    st.markdown("""
+    <div class="nav">
+        <div class="logo">CALIX</div>
+        <a href="/?page=home" class="link">Home</a>
+        <a href="/?page=estimate" class="link">Estimate</a>
+        <a href="/?page=food_library" class="link">Food Library</a>
+        <a href="/?page=health_tips" class="link">Health Tips</a>
+        <a href="/?page=about" class="link">About</a>
+    </div>
+    """, unsafe_allow_html=True)
+
+page = st.query_params.get("page", "home")
+
+# === BETTER MODEL: eslamxm/vit-base-food101 (Fine-tuned Food-101 + 88% Accuracy) ===
+@st.cache_resource(show_spinner="Loading AI...")
+def load_model():
+    processor = AutoImageProcessor.from_pretrained("eslamxm/vit-base-food101")
+    model = AutoModelForImageClassification.from_pretrained("eslamxm/vit-base-food101")
+    return processor, model
+
+processor, model = load_model()
+food_names = [model.config.id2label[i].replace("_", " ").title() for i in range(len(model.config.id2label))]
+
+# === LOCAL NUTRITION ===
+nutrition_db = {
+    "Pizza": {"cal": 285, "carb": "36g", "prot": "12g", "fat": "10g"},
+    "Biryani": {"cal": 320, "carb": "45g", "prot": "15g", "fat": "12g"},
+    "Appam": {"cal": 180, "carb": "32g", "prot": "3g", "fat": "5g"},
+    "Samosa": {"cal": 250, "carb": "25g", "prot": "5g", "fat": "15g"},
+    "Idli": {"cal": 60, "carb": "12g", "prot": "2g", "fat": "0.5g"},
+    "Dosa": {"cal": 170, "carb": "28g", "prot": "4g", "fat": "6g"},
+    "Burger": {"cal": 500, "carb": "45g", "prot": "25g", "fat": "28g"},
+    "Pancakes": {"cal": 220, "carb": "32g", "prot": "6g", "fat": "8g"},
+    "Chicken Curry": {"cal": 320, "carb": "15g", "prot": "25g", "fat": "18g"},
+    "default": {"cal": 250, "carb": "30g", "prot": "10g", "fat": "10g"}
+}
+
+# === HISTORY ===
+if "history" not in st.session_state:
+    st.session_state.history = []
+
+# === 50 TIPS ===
+health_tips = [
+    "Drink 8 glasses of water daily.", "Eat 5 servings of fruits and vegetables.", "Walk 30 minutes every day.",
+    "Avoid sugary drinks.", "Sleep 7-8 hours per night.", "Choose whole grains over refined.",
+    "Limit processed foods.", "Eat protein with every meal.", "Reduce salt intake.",
+    "Cook at home more often.", "Read food labels.", "Eat slowly and mindfully.",
+    "Include healthy fats like avocado.", "Limit alcohol consumption.", "Practice portion control.",
+    "Add spices instead of salt.", "Eat breakfast daily.", "Stay hydrated during exercise.",
+    "Choose lean proteins.", "Include fiber-rich foods.", "Limit fried foods.",
+    "Eat more plant-based meals.", "Avoid late-night snacking.", "Chew food thoroughly.",
+    "Include omega-3 rich foods.", "Reduce caffeine after noon.", "Eat colorful foods.",
+    "Plan meals ahead.", "Keep healthy snacks handy.", "Avoid emotional eating.",
+    "Exercise in the morning.", "Stand more, sit less.", "Take stairs instead of elevator.",
+    "Practice yoga or meditation.", "Get sunlight daily.", "Limit screen time before bed.",
+    "Eat fermented foods for gut health.", "Include nuts and seeds.", "Drink green tea.",
+    "Avoid trans fats.", "Eat fish twice a week.", "Include legumes in diet.",
+    "Reduce red meat intake.", "Eat seasonal foods.", "Grow your own herbs.",
+    "Share meals with family.", "Practice gratitude before eating.", "Try new healthy recipes.",
+    "Keep a food journal.", "Celebrate small wins.", "Stay consistent, not perfect."
+]
+
+# === NAV BUTTONS ===
+def nav_buttons(prev=None, next=None):
+    col1, col2, col3 = st.columns([1,1,1])
+    with col1:
+        if prev and st.button("Back", key=f"back_{page}"):
+            st.query_params["page"] = prev
+            st.rerun()
+    with col3:
+        if next and st.button("Next", key=f"next_{page}"):
+            st.query_params["page"] = next
+            st.rerun()
+
+# === PAGES ===
+nav_bar()
+
+# === HOME ===
+if page == "home":
+    st.markdown('<h1 class="title">Know What You Eat - Instantly.</h1>', unsafe_allow_html=True)
+    col1, col2 = st.columns(2)
+    with col1:
+        st.markdown('<div class="card">', unsafe_allow_html=True)
+        uploaded = st.file_uploader("Upload food photo", type=["jpg","png","jpeg"])
+        if uploaded:
+            st.session_state.uploaded_image = uploaded
+            st.image(uploaded, width=250)
+        st.markdown('</div>', unsafe_allow_html=True)
+    with col2:
+        st.markdown('<div class="card"><p><b>Detects 101 Foods:</b><br>Pizza, Biryani, Appam, Samosa, Idli, Dosa, Burger, etc.</p></div>', unsafe_allow_html=True)
+    nav_buttons(next="estimate")
+    footer()
+
+# === ESTIMATE ===
+elif page == "estimate":
+    st.markdown('<h1 class="title">Estimate Calories</h1>', unsafe_allow_html=True)
+    uploaded = st.session_state.get("uploaded_image") or st.file_uploader("Upload photo", type=["jpg","png","jpeg"])
+    
+    if uploaded:
+        img = Image.open(uploaded).convert("RGB")
+        st.image(img, width=300)
+        
+        with st.spinner("Detecting food..."):
+            inputs = processor(images=img, return_tensors="pt")
+            with torch.no_grad():
+                outputs = model(**inputs)
+            idx = outputs.logits.argmax(-1).item()
+            name = food_names[idx]
+
+        st.success(f"*Detected:* {name}")
+
+        nut = nutrition_db.get(name, nutrition_db["default"])
+
+        st.markdown(f"""
+        <div class="card">
+            <p><b>Calories:</b> {nut['cal']} kcal/100g</p>
+            <p><b>Carbs:</b> {nut['carb']}</p>
+            <p><b>Protein:</b> {nut['prot']}</p>
+            <p><b>Fat:</b> {nut['fat']}</p>
+        </div>
+        """, unsafe_allow_html=True)
+
+        if st.button("Add to Daily Log"):
+            st.session_state.history.append({
+                "Food": name,
+                "Calories": nut['cal'],
+                "Carbs": nut['carb'],
+                "Protein": nut['prot'],
+                "Fat": nut['fat']
+            })
+            st.success("Added!")
+
+        nav_buttons(prev="home", next="food_library")
+    else:
+        nav_buttons(prev="home")
+    footer()
+
+# === FOOD LIBRARY ===
+elif page == "food_library":
+    st.markdown('<h1 class="title">Food Library (History)</h1>', unsafe_allow_html=True)
+    if st.session_state.history:
+        df = pd.DataFrame(st.session_state.history)
+        st.dataframe(df, use_container_width=True)
+        total_cal = sum([x for x in df["Calories"] if isinstance(x, (int, float))])
+        st.info(f"*Total Calories Logged:* {total_cal} kcal")
+    else:
+        st.info("No food logged yet.")
+    nav_buttons(prev="estimate", next="health_tips")
+    footer()
+
+# === HEALTH TIPS ===
+elif page == "health_tips":
+    st.markdown('<h1 class="title">Health Tips</h1>', unsafe_allow_html=True)
+    tip_idx = st.session_state.get("tip_idx", 0)
+    st.markdown(f'<div class="card"><p>{health_tips[tip_idx]}</p></div>', unsafe_allow_html=True)
+    col1, col2, col3 = st.columns([1,1,1])
+    with col1:
+        if st.button("Previous"):
+            st.session_state.tip_idx = (tip_idx - 1) % len(health_tips)
+            st.rerun()
+    with col3:
+        if st.button("Next"):
+            st.session_state.tip_idx = (tip_idx + 1) % len(health_tips)
+            st.rerun()
+    nav_buttons(prev="food_library", next="about")
+    footer()
+
+# === ABOUT ===
+elif page == "about":
+    st.markdown('<h1 class="title">About CALIX</h1>', unsafe_allow_html=True)
+    st.markdown("""
+    *CALIX* is an AI food detector that identifies *101 foods* from photos.
+
+    ### Features
+    - *Detects exact names*: Pizza, Biryani, Appam, Samosa, Idli, Dosa, etc.
+    - *Local nutrition*: Calories, Carbs, Protein, Fat (no internet needed)
+    - *History log*: Saves all scans with full details
+    - *50 Health Tips*
+    - *Dark theme + navigation*
+
+    ### AI Model
+    - eslamxm/vit-base-food101 (Public, 101 classes from Food-101 dataset)
+    - Dataset: 101,000 images, 101 classes
+
+    *Built by:*  
+    Rudhreshwaran, Shreyas, Tiya Singh, Shubham Prasad, Shubham Raj  
+    *AMC CSE-AIML | 2025*
+    """)
+    nav_buttons(prev="health_tips")
+    footer()

requirements.txt

@@ -1,3 +1,6 @@
-altair
-pandas
-streamlit
+streamlit==1.35.0
+torch==2.0.1
+torchvision==0.15.2
+transformers==4.35.0
+Pillow==10.0.0
+pandas==2.1.0