Spaces:
Running
Running
Improve Streamlit sidebar collapse and processing state flow
Browse files
app.py
CHANGED
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@@ -15,6 +15,7 @@ if str(_PROJECT_ROOT) not in sys.path:
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import numpy as np
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import streamlit as st
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from photo_editor.config import get_settings
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from photo_editor.images import dng_to_rgb
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@@ -46,9 +47,66 @@ def _load_original_for_display(image_path: Path):
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return str(path)
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def main() -> None:
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st.set_page_config(page_title="LumiGrade AI", page_icon="📷", layout="wide")
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st.markdown(
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"""
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<style>
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@@ -120,6 +178,9 @@ h1 {
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[data-testid="stSidebar"] [data-testid="stSidebarContent"] {
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padding-top: 0 !important;
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}
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</style>
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""",
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unsafe_allow_html=True,
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@@ -127,6 +188,10 @@ h1 {
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st.title("📷 LumiGrade AI")
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st.caption("Upload an image to get expert-informed edit recommendations and an instant enhanced result.")
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# Config check
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s = get_settings()
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@@ -142,7 +207,7 @@ h1 {
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# control and wire it to this flag.
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use_editing_api = False
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image_path = None
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with st.sidebar:
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# Reliable spacing so only the Pipeline Inputs card moves down.
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@@ -152,7 +217,7 @@ h1 {
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uploaded = st.file_uploader(
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"Upload JPEG, PNG, DNG, HEIC, or HEIF",
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type=["jpg", "jpeg", "png", "dng", "heic", "heif"],
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help="
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)
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if uploaded is not None:
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suffix = Path(uploaded.name).suffix.lower()
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@@ -168,25 +233,30 @@ h1 {
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target = _STREAMLIT_INPUT_JPG_PATH
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target.write_bytes(uploaded.getvalue())
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image_path = target
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-
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-
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-
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-
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-
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if p.exists():
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image_path = p
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else:
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st.warning("File not found. Use a full path that exists, or upload a file.")
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-
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run_clicked = st.button("▶ Run Pipeline", type="primary", use_container_width=True)
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status = st.empty()
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if image_path is None:
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status.info("Provide an image to run.")
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-
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loading_box = st.empty()
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def _render_loading(current_stage: str, state: str = "running") -> None:
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@@ -264,6 +334,19 @@ h1 {
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st.session_state.pop("pipeline_input_path", None)
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st.session_state.pop("pipeline_current_params", None)
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_render_loading("consulting", "failed")
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with st.container(border=True):
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st.subheader("Results Dashboard")
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@@ -271,9 +354,9 @@ h1 {
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# Show result if available
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if (
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-
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and st.session_state.get("pipeline_result")
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and st.session_state.get("pipeline_input_path") == str(
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):
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result = st.session_state["pipeline_result"]
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out_path = st.session_state["pipeline_output_path"]
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@@ -331,9 +414,9 @@ h1 {
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# Keep this full-width and at the bottom, per request.
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if (
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-
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and st.session_state.get("pipeline_result")
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and st.session_state.get("pipeline_input_path") == str(
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):
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result = st.session_state["pipeline_result"]
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out_path = st.session_state["pipeline_output_path"]
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@@ -342,7 +425,7 @@ h1 {
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st.subheader("Original vs Result")
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col_orig, col_result = st.columns(2)
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with col_orig:
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st.image(_load_original_for_display(
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with col_result:
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st.image(str(out_path), caption="Edited", use_container_width=True)
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import numpy as np
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import streamlit as st
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import streamlit.components.v1 as components
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from photo_editor.config import get_settings
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from photo_editor.images import dng_to_rgb
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return str(path)
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def _collapse_sidebar() -> None:
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"""Collapse Streamlit sidebar via whichever toggle exists in this version."""
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components.html(
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"""
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<script>
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const doc = window.parent.document;
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function collapseIfOpen() {
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// Newer Streamlit versions expose a dedicated collapse button when sidebar is open.
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const closeBtn =
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doc.querySelector('[data-testid="stSidebarCollapseButton"]') ||
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doc.querySelector('button[aria-label="Close sidebar"]');
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if (closeBtn) {
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closeBtn.click();
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return true;
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}
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return false;
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}
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// Try immediately, then briefly retry in case elements mount after rerun.
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if (!collapseIfOpen()) {
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let tries = 0;
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const interval = setInterval(() => {
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tries += 1;
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if (collapseIfOpen() || tries > 20) {
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clearInterval(interval);
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}
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}, 100);
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}
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</script>
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""",
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height=0,
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width=0,
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)
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def main() -> None:
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st.set_page_config(page_title="LumiGrade AI", page_icon="📷", layout="wide")
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if "sidebar_collapsed" not in st.session_state:
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st.session_state["sidebar_collapsed"] = False
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if "run_pipeline_requested" not in st.session_state:
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st.session_state["run_pipeline_requested"] = False
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if "selected_image_path" not in st.session_state:
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st.session_state["selected_image_path"] = ""
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if "is_processing" not in st.session_state:
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st.session_state["is_processing"] = False
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if "refresh_after_run" not in st.session_state:
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st.session_state["refresh_after_run"] = False
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collapse_css = ""
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if st.session_state["sidebar_collapsed"]:
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collapse_css = """
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/* Force-hide sidebar after run is triggered; avoids version-specific JS toggles. */
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[data-testid="stSidebar"] {
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display: none !important;
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}
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"""
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st.markdown(
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"""
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<style>
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[data-testid="stSidebar"] [data-testid="stSidebarContent"] {
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padding-top: 0 !important;
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}
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"""
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+ collapse_css
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+ """
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</style>
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""",
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unsafe_allow_html=True,
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st.title("📷 LumiGrade AI")
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st.caption("Upload an image to get expert-informed edit recommendations and an instant enhanced result.")
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if st.session_state["sidebar_collapsed"]:
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if st.button("⚙️ Show Inputs", key="show_inputs_btn", disabled=st.session_state["is_processing"]):
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st.session_state["sidebar_collapsed"] = False
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st.rerun()
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# Config check
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s = get_settings()
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# control and wire it to this flag.
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use_editing_api = False
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image_path = Path(st.session_state["selected_image_path"]) if st.session_state["selected_image_path"] else None
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with st.sidebar:
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# Reliable spacing so only the Pipeline Inputs card moves down.
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uploaded = st.file_uploader(
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"Upload JPEG, PNG, DNG, HEIC, or HEIF",
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type=["jpg", "jpeg", "png", "dng", "heic", "heif"],
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help="Upload JPEG/PNG/DNG/HEIC/HEIF to run the edit recommendation pipeline.",
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)
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if uploaded is not None:
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suffix = Path(uploaded.name).suffix.lower()
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target = _STREAMLIT_INPUT_JPG_PATH
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target.write_bytes(uploaded.getvalue())
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image_path = target
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st.session_state["selected_image_path"] = str(target)
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run_clicked = st.button(
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"✨ Generate Edit Recommendations",
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type="primary",
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use_container_width=True,
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disabled=st.session_state["is_processing"],
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)
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status = st.empty()
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if image_path is None:
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status.info("Provide an image to run.")
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if run_clicked and image_path is not None:
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# Mark busy before rerun so any control rendered on next pass is disabled.
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st.session_state["is_processing"] = True
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st.session_state["sidebar_collapsed"] = True
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st.session_state["run_pipeline_requested"] = True
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st.rerun()
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should_run_pipeline = st.session_state.pop("run_pipeline_requested", False)
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if should_run_pipeline and st.session_state["selected_image_path"]:
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image_path = Path(st.session_state["selected_image_path"])
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if should_run_pipeline and image_path is not None:
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st.session_state["is_processing"] = True
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_collapse_sidebar()
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loading_box = st.empty()
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def _render_loading(current_stage: str, state: str = "running") -> None:
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st.session_state.pop("pipeline_input_path", None)
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st.session_state.pop("pipeline_current_params", None)
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_render_loading("consulting", "failed")
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finally:
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st.session_state["is_processing"] = False
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# Button states are computed at render time; rerun once so controls
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# immediately reflect processing completion (re-enable Show Inputs).
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st.session_state["refresh_after_run"] = True
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if st.session_state.get("refresh_after_run"):
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st.session_state["refresh_after_run"] = False
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st.rerun()
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display_input_path = image_path
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if display_input_path is None and st.session_state.get("pipeline_input_path"):
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display_input_path = Path(st.session_state["pipeline_input_path"])
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with st.container(border=True):
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st.subheader("Results Dashboard")
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# Show result if available
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if (
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display_input_path is not None
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and st.session_state.get("pipeline_result")
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and st.session_state.get("pipeline_input_path") == str(display_input_path)
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):
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result = st.session_state["pipeline_result"]
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out_path = st.session_state["pipeline_output_path"]
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# Keep this full-width and at the bottom, per request.
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if (
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display_input_path is not None
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and st.session_state.get("pipeline_result")
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and st.session_state.get("pipeline_input_path") == str(display_input_path)
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):
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result = st.session_state["pipeline_result"]
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out_path = st.session_state["pipeline_output_path"]
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st.subheader("Original vs Result")
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col_orig, col_result = st.columns(2)
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with col_orig:
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st.image(_load_original_for_display(display_input_path), caption="Original", use_container_width=True)
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with col_result:
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st.image(str(out_path), caption="Edited", use_container_width=True)
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