Update app.py

app.py

@@ -605,9 +605,26 @@ def init_state() -> Dict:
 def cb_load_image(upload, state):
     if upload is None:
         return None, state, "Upload a floor-plan image to begin."
-    img_bgr = cv2.imdecode(
-        np.frombuffer(upload, dtype=np.uint8), cv2.IMREAD_COLOR
-    )
+    # Gradio 6: UploadButton returns a NamedString (file path) or a dict
+    try:
+        if hasattr(upload, "name"):
+            file_path = upload.name          # NamedString / tempfile path
+        elif isinstance(upload, dict) and "name" in upload:
+            file_path = upload["name"]
+        elif isinstance(upload, str):
+            file_path = upload
+        else:
+            # bytes fallback
+            img_bgr = cv2.imdecode(
+                np.frombuffer(bytes(upload), dtype=np.uint8), cv2.IMREAD_COLOR
+            )
+            file_path = None
+
+        if file_path is not None:
+            img_bgr = cv2.imread(file_path)
+    except Exception as e:
+        return None, state, f"❌ Error reading upload: {e}"
+
     if img_bgr is None:
         return None, state, "❌ Could not decode image."
     state = init_state()
@@ -699,25 +716,25 @@ def cb_undo_door_line(state):
     return vis, state, f"↩ Last line removed. Remaining: {len(state['user_lines'])}"
 
 
-def cb_run_sam(state, progress=gr.Progress()):
+def cb_run_sam(state):
     walls = state.get("walls")
     img   = state.get("img_cropped")
     if walls is None or img is None:
         return None, None, state, "Run preprocessing first."
 
-    progress(0.1, desc="Downloading SAM checkpoint…")
+    print("[SAM] Downloading checkpoint if needed…")
     ckpt = download_sam_if_needed()
     if ckpt is None:
         return None, None, state, "❌ SAM checkpoint download failed."
 
-    progress(0.3, desc="Segmenting rooms…")
+    print("[SAM] Segmenting rooms…")
     img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
     raw     = segment_with_sam(img_rgb, walls.copy(), ckpt)
 
-    progress(0.6, desc="Filtering rooms…")
+    print("[SAM] Filtering rooms…")
     filtered = filter_room_masks(raw, img.shape)
 
-    progress(0.75, desc="Running OCR…")
+    print("[SAM] Running OCR…")
     rooms = []
     for idx, entry in enumerate(filtered, 1):
         cnt   = entry["contour"]
@@ -748,7 +765,7 @@ def cb_run_sam(state, progress=gr.Progress()):
     state["rooms"]       = rooms
     state["selected_ids"] = []
 
-    progress(0.9, desc="Rendering…")
+    print("[SAM] Rendering…")
     annotated = build_annotated_image(img, rooms)
     state["annotated"] = annotated
 
@@ -854,29 +871,37 @@ CSS = """
 #title { text-align: center; font-size: 1.8em; font-weight: 700; color: #1F4E79; }
 #subtitle { text-align: center; color: #555; margin-top: -8px; margin-bottom: 16px; }
 .step-card { border-left: 4px solid #1F4E79 !important; padding-left: 10px !important; }
-#status-box textarea { font-size: 0.95em !important; color: #1a6b2e !important; font-weight: 600 !important; }
 """
 
-with gr.Blocks(css=CSS, title="FloorPlan Analyser") as app:
+
+def _walls_to_rgb(s):
+    """Helper used in .then() — must be a named function for Gradio 6."""
+    w = s.get("walls")
+    if w is None:
+        return None
+    return cv2.cvtColor(w, cv2.COLOR_GRAY2RGB)
+
+
+with gr.Blocks(title="FloorPlan Analyser") as app:
     state = gr.State(init_state())
 
     gr.Markdown("# 🏢 Floor Plan Room Analyser", elem_id="title")
     gr.Markdown(
         "Upload a floor-plan → auto-extract walls → close doors → SAM segmentation → OCR labels → export Excel",
-        elem_id="subtitle"
+        elem_id="subtitle",
     )
 
-    status_box = gr.Textbox(label="Status", interactive=False,
-                            value="Idle — upload a floor plan to begin.",
-                            elem_id="status-box")
+    status_box = gr.Textbox(
+        label="Status",
+        interactive=False,
+        value="Idle — upload a floor plan to begin.",
+    )
 
     # ── Row 1: Upload + Preprocessing ───────────────────────────────────────
     with gr.Row():
         with gr.Column(scale=1, elem_classes="step-card"):
             gr.Markdown("### 1️⃣  Upload Floor Plan")
-            upload_btn = gr.UploadButton(
-                "📂 Upload Image", file_types=["image"], size="sm"
-            )
+            upload_btn  = gr.UploadButton("📂 Upload Image", file_types=["image"], size="sm")
             raw_preview = gr.Image(label="Loaded Image", height=320)
 
         with gr.Column(scale=1, elem_classes="step-card"):
@@ -893,14 +918,15 @@ with gr.Blocks(css=CSS, title="FloorPlan Analyser") as app:
         with gr.Column(elem_classes="step-card"):
             gr.Markdown("### 3️⃣  Draw Door-Closing Lines  *(click start → click end)*")
             gr.Markdown(
-                "Click on the **Walls** image below to define start/end of a door-closing line. "
-                "Drawn lines are applied to the wall mask before SAM runs, preventing segment leakage."
+                "Click the wall image below: **first click** = line start, "
+                "**second click** = line end. Lines are burned into the wall mask "
+                "before SAM runs to prevent room leakage through open doors."
             )
-            with gr.Row():
-                undo_line_btn   = gr.Button("↩ Undo Last Line", size="sm")
+            undo_line_btn = gr.Button("↩ Undo Last Line", size="sm")
             wall_draw_img = gr.Image(
-                label="Wall mask — click to draw door lines",
-                height=380, interactive=False
+                label="Wall mask — click to draw door-closing lines",
+                height=380,
+                interactive=False,
             )
 
     # ── Row 3: SAM + Annotation ──────────────────────────────────────────────
@@ -909,8 +935,9 @@ with gr.Blocks(css=CSS, title="FloorPlan Analyser") as app:
             gr.Markdown("### 4️⃣  SAM Segmentation + OCR")
             sam_btn = gr.Button("🤖 Run SAM + OCR", variant="primary")
             ann_img = gr.Image(
-                label="Annotated rooms — click to select/deselect",
-                height=480, interactive=False
+                label="Annotated rooms — click to select / deselect",
+                height=480,
+                interactive=False,
             )
 
         with gr.Column(scale=1, elem_classes="step-card"):
@@ -918,81 +945,80 @@ with gr.Blocks(css=CSS, title="FloorPlan Analyser") as app:
             room_table = gr.Dataframe(
                 headers=["ID", "Label", "Area", "SAM Score"],
                 datatype=["number", "str", "str", "str"],
-                interactive=False, label="Detected Rooms"
+                interactive=False,
+                label="Detected Rooms",
             )
             with gr.Group():
                 gr.Markdown("**Edit selected room(s)**")
-                rename_txt = gr.Textbox(
-                    placeholder="New label…", label="Rename Label"
-                )
+                rename_txt = gr.Textbox(placeholder="New label…", label="Rename Label")
                 with gr.Row():
                     rename_btn = gr.Button("✏ Rename", size="sm")
                     remove_btn = gr.Button("🗑 Remove Selected", size="sm", variant="stop")
 
             gr.Markdown("---")
-            export_btn  = gr.Button("📊 Export to Excel", variant="secondary")
-            excel_file  = gr.File(label="Download Excel", visible=True)
+            export_btn = gr.Button("📊 Export to Excel", variant="secondary")
+            excel_file = gr.File(label="Download Excel", visible=True)
 
-    # ── Wiring ───────────────────────────────────────────────────────────────
+    # ── Event Wiring ─────────────────────────────────────────────────────────
 
     upload_btn.upload(
         cb_load_image,
         inputs=[upload_btn, state],
-        outputs=[raw_preview, state, status_box]
+        outputs=[raw_preview, state, status_box],
     )
 
     preprocess_btn.click(
         cb_preprocess,
         inputs=[state],
-        outputs=[clean_img, walls_img, state, status_box]
+        outputs=[clean_img, walls_img, state, status_box],
     ).then(
-        lambda s: cv2.cvtColor(s["walls"], cv2.COLOR_GRAY2RGB)
-                  if s.get("walls") is not None else None,
+        _walls_to_rgb,
         inputs=[state],
-        outputs=[wall_draw_img]
+        outputs=[wall_draw_img],
     )
 
     wall_draw_img.select(
         cb_add_door_line,
         inputs=[state],
-        outputs=[wall_draw_img, state, status_box]
+        outputs=[wall_draw_img, state, status_box],
     )
 
     undo_line_btn.click(
         cb_undo_door_line,
         inputs=[state],
-        outputs=[wall_draw_img, state, status_box]
+        outputs=[wall_draw_img, state, status_box],
     )
 
     sam_btn.click(
         cb_run_sam,
         inputs=[state],
-        outputs=[ann_img, room_table, state, status_box]
+        outputs=[ann_img, room_table, state, status_box],
     )
 
     ann_img.select(
         cb_click_room,
         inputs=[state],
-        outputs=[ann_img, state, status_box]
+        outputs=[ann_img, state, status_box],
     )
 
     remove_btn.click(
         cb_remove_selected,
         inputs=[state],
-        outputs=[ann_img, room_table, state, status_box]
+        outputs=[ann_img, room_table, state, status_box],
     )
 
     rename_btn.click(
         cb_rename_selected,
         inputs=[rename_txt, state],
-        outputs=[ann_img, room_table, state, status_box]
+        outputs=[ann_img, room_table, state, status_box],
     )
 
     export_btn.click(
         cb_export_excel,
         inputs=[state],
-        outputs=[excel_file, status_box]
+        outputs=[excel_file, status_box],
     )
 
+
 if __name__ == "__main__":
-    app.launch(share=False, debug=True)
+    app.launch(share=False, debug=True, css=CSS)