TuringsSolutions/Fibonacci-Compressor

1import streamlit as st2import os3import tempfile4import numpy as np5from PIL import Image6from flc_core import flc_encode_file, flc_decode_file, cosine_similarity_bytes7 8st.set_page_config(page_title="FLC v1.3 | How it Works", layout="wide")9 10# Styling for a "Scientific Laboratory" look11st.markdown("""12    <style>13    .reportview-container { background: #0e1117; }14    .main { color: #e0e0e0; }15    h1, h2, h3 { color: #f1c40f !important; }16    .stAlert { background-color: #1a1c24; border: 1px solid #f1c40f; }17    </style>18    """, unsafe_allow_html=True)19 20st.title("🌀 Fibonacci Lattice Compression (FLC)")21st.markdown("""22    **FLC v1.3** is a bio-inspired data compression architecture. Unlike standard ZIP or JPEG formats, 23    FLC uses the **Golden Ratio ($\Phi$)** to decide which parts of your data are "essential" and which are "noise."24""")25 26# --- PILLAR 1: THE EXPLAINER ---27with st.expander("📖 Step-by-Step: How does the 'Secret Sauce' work?"):28    col1, col2, col3 = st.columns(3)29    30    with col1:31        st.markdown("### 1. Spectral Projection")32        st.write("""33            We treat your data like a sound wave. Using a **DCT (Discrete Cosine Transform)**, 34            we project the bits into frequency space. 35            * **Low Frequencies:** The "skeleton" of your data.36            * **High Frequencies:** The "dust" and fine details.37        """)38 39    with col2:40        st.markdown("### 2. The Golden Filter")41        st.write("""42            Instead of treating all frequencies equally, FLC uses **Fibonacci Bands**. 43            We compress the 'dust' using steps based on the **Golden Ratio ($\Phi \approx 1.618$)**. 44            As the frequency increases, the compression gets exponentially more aggressive.45        """)46 47    with col3:48        with st.container():49            st.markdown("### 3. Fibonacci Coding")50            st.write("""51                Standard computers use 8-bit bytes. FLC uses **Fibonacci Binary**. 52                It's a "universal code" that uses the sum of Fibonacci numbers to represent values, 53                making the compressed stream incredibly resilient and dense.54            """)55 56st.divider()57 58# --- PILLAR 2: THE INTERACTIVE DEMO ---59st.header("🧪 Test the Horizon")60with st.sidebar:61    st.header("🎛️ Architecture Params")62    st.info("Adjusting these changes how the 'Secret Sauce' math is applied.")63    64    quality_map = {65        "High Compression (Lossy)": {"bands": 6, "step": 0.08, "desc": "Aggressive $\Phi$-scaling."},66        "Balanced": {"bands": 12, "step": 0.005, "desc": "The Golden Mean of fidelity."},67        "Near-Lossless": {"bands": 24, "step": 0.0001, "desc": "Full spectral recovery."}68    }69    70    tier = st.radio("Fidelity Tier", list(quality_map.keys()), index=1)71    st.caption(quality_map[tier]["desc"])72    73    st.subheader("Visual Overlays")74    show_spiral = st.checkbox("Fibonacci Spiral Outlines", value=True)75    show_ring = st.checkbox("Event Horizon Ring", value=True)76 77uploaded_file = st.file_uploader("Upload a file (Image, Text, or Binary)", type=["bin", "png", "jpg", "txt"])78 79if uploaded_file is not None:80    with tempfile.TemporaryDirectory() as tmpdir:81        in_path = os.path.join(tmpdir, "input.bin")82        out_flc = os.path.join(tmpdir, "output.flc")83        out_gif = os.path.join(tmpdir, "unzip.gif")84        recovered_path = os.path.join(tmpdir, "recovered.bin")85        86        with open(in_path, "wb") as f:87            f.write(uploaded_file.getbuffer())88            89        if st.button("RUN HOLOGRAPHIC RECONSTRUCTION"):90            with st.status("Initializing Fibonacci Manifolds...", expanded=True) as status:91                st.write("Transforming data to Frequency Space...")92                enc = flc_encode_file(93                    in_path, out_flc, unzip_gif=out_gif,94                    n_bands=quality_map[tier]["bands"], 95                    base_step=quality_map[tier]["step"]96                )97                98                st.write("Applying $\Phi$-scaled quantization...")99                dec = flc_decode_file(out_flc, recovered_path)100                101                st.write("Generating Holographic Unzip visualization...")102                status.update(label="Reconstruction Complete!", state="complete", expanded=False)103 104            # Results Section105            st.subheader("📊 Compression Performance")106            c1, c2, c3, c4 = st.columns(4)107            c1.metric("Original Size", f"{enc['n_bytes']} B")108            c2.metric("Compressed Size", f"{enc['payload_len']} B")109            c3.metric("Ratio", f"{enc['ratio']:.2%}")110            111            # Calculate Similarity112            orig_data = open(in_path, "rb").read()113            reco_data = open(recovered_path, "rb").read()114            fidelity = cosine_similarity_bytes(orig_data, reco_data)115            c4.metric("Data Fidelity", f"{fidelity*100:.2f}%")116 117            st.divider()118 119            # Visualization120            st.header("🎞️ The Unzip Sequence")121            st.markdown("""122                This animation shows the **Progressive Reconstruction**. 123                The 'Hologram' on the left shows the frequency data being added band-by-band. 124                The 'Spiral' on the right shows the bits filling the Fibonacci tiles in real-time.125            """)126            127            if os.path.exists(out_gif):128                st.image(out_gif, use_container_width=True)129            130            st.info("💡 Notice how the general shape appears first, and the fine details (noise) appear last. This is the hallmark of Spectral Compression.")131 132            with open(out_flc, "rb") as f:133                st.download_button("📥 Download Encoded .FLC File", f, file_name="demo.flc")134 135else:136    st.warning("Please upload a file to visualize the Fibonacci transformation.")