(DEPLOY): unignore outputs/*.pth on space-deploy; continue ignoring output/logs

.gitignore

@@ -1,8 +1,6 @@
 # Ignore raw data and system clutter
 
-data
 datasets/
-depracated_scripts/
 __pycache__/
 *.pyc
 .DS_store
@@ -12,43 +10,15 @@ __pycache__/
 *.env
 *.yml
 *.json
-environment.yml
-test_env/
-_frozen_reference.txt
-
-_venv_docker_test/
-
 .streamlit
-logs/
-docs/scope_maintenance_log.yaml
-depracated_script/ftir_cv_diagnostics_run1.json
-depracated_script/ftir_cv_diagnostics.json
-depracated_script/ftir_model.pth
-depracated_script/plot_ftir_sample.py
-depracated_script/preprocess_ftir_legacy.py
-depracated_script/preprocess_ftir.py
-depracated_script/train_ftir_model_cv.py
-depracated_script/train_ftir_model.py
-depracated_script/train_model.py
-depracated_script/cnn_model.py
-models/cnn_model.py
-outputs\inference\test_prediction.json
-outputs\figure2_model.pth
-outputs\resnet_model.pth
-outputs\saliency
-outputs/plots/04_raman_diagnostics.ipynb
-outputs/figure2_model.pth
-outputs/inference/test_prediction.json
+outputs/logs/
 docs/PROJECT_REPORT.md
 wea-*.txt
 sta-*.txt
-scripts/generate_saliency.py
-scripts/compare_samples.py
+
 # --- Data (keep folder, ignore files) ---
 datasets/**
 !datasets/.gitkeep
 !datasets/.README.md
 # ---------------------------------------
-outputs/resnet18vision_model.pth
-requirements_0.txt
-requirements.txt
+

dashboard/app.py

@@ -1,171 +0,0 @@
-"""
-Streamlit UI for ml-polymer-recycling — Step 3b: Raman Upload → Parse → Preview
-- Adds real file uploader to Raman Inference page
-- Accepts .txt Raman spectra (single or batch)
-- Parses one- or two-column format
-- Displays file name and data table preview per upload
-- No inference or resampling yet
-"""
-
-import streamlit as st
-from pathlib import Path
-import pandas as pd
-import io
-
-# --- PAGE CONFIGURATION ---
-st.set_page_config(
-    page_title="ML Polymer Recycling",
-    page_icon="🧪",
-    layout="wide"
-)
-
-# --- SESSION STATE INITIALIZATION ---
-def init_session_state():
-    if "status_message" not in st.session_state:
-        st.session_state.status_message = "Ready."
-    if "status_type" not in st.session_state:
-        st.session_state.status_type = "ok"
-    if "modality" not in st.session_state:
-        st.session_state.modality = "Raman"
-
-# --- STATUS BANNER ---
-def display_status():
-    style_map = {
-        "ok": ("#e8f5e9", "#2e7d32"),
-        "warn": ("#fff8e1", "#f9a825"),
-        "err": ("#ffebee", "#c62828")
-    }
-    bg_color, text_color = style_map.get(st.session_state.status_type, ("#f0f0f0", "#333"))
-    st.markdown(f"""
-        <div style='background-color:{bg_color}; padding:0.75em 1em; border-radius:8px; color:{text_color};'>
-            <b>Status:</b> {st.session_state.status_message}
-        </div>
-    """, unsafe_allow_html=True)
-
-# --- SIDEBAR NAVIGATION ---
-def display_sidebar():
-    with st.sidebar:
-        st.header("🧪 ML Polymer Dashboard")
-
-        modality = st.radio("Modality", ["Raman", "Image", "FTIR"])
-        st.session_state.modality = modality
-
-        if modality == "Raman":
-            page = st.radio("Raman Pages", ["Dashboard", "Model Management", "Inference"])
-        elif modality == "Image":
-            page = st.radio("Image Pages", ["Model Management", "Inference"])
-        elif modality == "FTIR":
-            page = st.radio("FTIR Pages", ["Model Management", "Inference"])
-
-        return modality, page
-
-# --- HEADER BAR ---
-def display_header(title: str):
-    st.title(title)
-    display_status()
-    st.markdown("---")
-
-# --- MODEL DISCOVERY (Raman only for now) ---
-def discover_models(outputs_dir="outputs"):
-    out = []
-    root = Path(outputs_dir)
-    if not root.exists():
-        return []
-    for p in sorted(root.rglob("*.pth")):
-        out.append(p)
-    return out
-
-# --- RAMAN HELPERS ---
-def parse_txt_file(upload) -> pd.DataFrame:
-    try:
-        content = upload.read()
-        upload.seek(0)
-        buf = io.BytesIO(content)
-        try:
-            df = pd.read_csv(buf, sep=None, engine="python", header=None, comment="#")
-        except Exception:
-            buf.seek(0)
-            df = pd.read_csv(buf, delim_whitespace=True, header=None, comment="#")
-        return df
-    except Exception as e:
-        st.error(f"Failed to parse file: {upload.name}. Error: {e}")
-        return pd.DataFrame()
-
-# --- RAMAN PAGES ---
-def raman_dashboard():
-    display_header("Raman Dashboard")
-    st.write("This will house future metrics, model count, and version history.")
-
-def raman_model_management():
-    display_header("Raman Model Management")
-    models = discover_models()
-    if not models:
-        st.info("No model weights found in outputs/. Place .pth files there to make them discoverable.")
-    else:
-        st.markdown(f"**Discovered {len(models)} model weight file(s):**")
-        for m in models:
-            st.code(str(m), language="text")
-
-def raman_inference():
-    display_header("Raman Inference")
-
-    uploads = st.file_uploader(
-        "Upload one or more Raman .txt spectra (single- or two-column)",
-        type="txt",
-        accept_multiple_files=True
-    )
-
-    if uploads:
-        for file in uploads:
-            st.markdown(f"**Preview: {file.name}**")
-            df = parse_txt_file(file)
-            if not df.empty:
-                st.dataframe(df.head(10), use_container_width=True)
-            else:
-                st.warning("No data parsed or file unreadable.")
-            st.markdown("---")
-
-# --- IMAGE + FTIR PLACEHOLDERS ---
-def image_model_management():
-    display_header("Image Model Management")
-    st.info("Image-based model integration is coming soon.")
-
-def image_inference():
-    display_header("Image Inference")
-    st.info("This page will allow batch image upload and multi-model prediction.")
-
-def ftir_model_management():
-    display_header("FTIR Model Management")
-    st.info("FTIR model support is planned and will be developed after clarification with Dr. K.")
-
-def ftir_inference():
-    display_header("FTIR Inference")
-    st.info("FTIR input and prediction support will be added in a future phase.")
-
-# --- MAIN ENTRY POINT ---
-def main():
-    init_session_state()
-    modality, page = display_sidebar()
-
-    if modality == "Raman":
-        if page == "Dashboard":
-            raman_dashboard()
-        elif page == "Model Management":
-            raman_model_management()
-        elif page == "Inference":
-            raman_inference()
-
-    elif modality == "Image":
-        if page == "Model Management":
-            image_model_management()
-        elif page == "Inference":
-            image_inference()
-
-    elif modality == "FTIR":
-        if page == "Model Management":
-            ftir_model_management()
-        elif page == "Inference":
-            ftir_inference()
-
-if __name__ == "__main__":
-    main()