Update app.py

app.py

@@ -1,60 +1,37 @@
-import os
-
-# For preview, prefer GLB (compact)
-return str(glb_path), [str(glb_path), str(obj_path), str(fused)], "\n".join(logs[-6:]), gr.update(visible=True)
-
-except Exception as e:
-logs.append(f"\n[ERROR]\n{e}")
-return None, None, "\n".join(logs), gr.update(visible=False)
-
+import gradio as gr
+from PIL import Image
+
+def run_pipeline(gallery, max_px, match_mode, use_gpu_sift, voxel, depth, tris):
+    try:
+        logs = []
+        # TODO: your pipeline here
+        # return (preview_path, [file_paths...], "\n".join(logs[-6:]), gr.update(visible=True))
+        return None, [], "Ready.", gr.update(visible=False)
+    except Exception as e:
+        return None, None, f"[ERROR]\n{e}", gr.update(visible=False)
 
 def ui():
-with gr.Blocks(title="Sparse Multi‑View 3D (Urban Planning)", theme=gr.themes.Soft()) as demo:
-gr.Markdown(
-"""
-# 🏙️ Sparse Multi‑View 3D for Urban Planning
-Upload **3–30 photos** of a scene (streetscape, plaza, façade). We estimate camera poses with **COLMAP**, build a **dense point cloud**, and **mesh** it with Open3D.
-**Tips for sparse captures:** overlap ~60–70%, varying viewpoints (walk an arc), avoid moving cars/people when possible.
-"""
-)
-with gr.Row():
-with gr.Column(scale=2):
-imgs = gr.UploadButton("Upload images (JPG/PNG)", file_types=["image"], file_count="multiple")
-gallery = gr.Gallery(label="Selected", columns=6, height=160)
-imgs.upload(lambda files: [(f.name, Image.open(f).convert('RGB')) for f in files], imgs, gallery)
-
-with gr.Accordion("Reconstruction settings", open=False):
-max_px = gr.Slider(1024, 4096, value=2400, step=64, label="Max image size (px, longest side)")
-match_mode = gr.Radio(["exhaustive", "sequential", "spatial"], value="sequential", label="Matching mode")
-use_gpu_sift = gr.Checkbox(True, label="Use GPU for SIFT (if available)")
-with gr.Accordion("Meshing", open=True):
-voxel = gr.Slider(0.0, 0.05, value=0.01, step=0.005, label="Voxel downsample (m, approx units)")
-depth = gr.Slider(6, 12, value=9, step=1, label="Poisson depth (higher → more detail)")
-tris = gr.Slider(0, 500_000, value=150_000, step=10_000, label="Target triangles (0 = keep)")
-
-run = gr.Button("▶ Reconstruct 3D")
-with gr.Column(scale=1):
-preview = gr.Model3D(label="Mesh preview", visible=False)
-files_out = gr.Files(label="Downloads (GLB/OBJ/PLY)")
-logs = gr.Markdown("Logs will appear here after running…")
-
-run.click(
-run_pipeline,
-[gallery, max_px, match_mode, use_gpu_sift, voxel, depth, tris],
-[preview, files_out, logs, preview],
-queue=True,
-)
-
-gr.Markdown(
-"""
-### Notes & Scaling
-- Results are in **arbitrary units** (SfM scale). For metric scale, align the mesh in GIS/CAD using known distances.
-- Outdoor scenes with repetitive textures (glass, trees) can be challenging—add a few more oblique views if possible.
-"""
-)
-
-return demo
-
+    with gr.Blocks(title="Sparse Multi-View 3D (Urban Planning)") as demo:
+        gr.Markdown("# Sparse Multi-View 3D for Urban Planning")
+        with gr.Row():
+            with gr.Column(scale=2):
+                imgs = gr.UploadButton("Upload images (JPG/PNG)", file_types=["image"], file_count="multiple")
+                gallery = gr.Gallery(label="Selected", columns=6, height=160)
+                imgs.upload(lambda files: [(f.name, Image.open(f).convert('RGB')) for f in files], imgs, gallery)
+                max_px = gr.Slider(1024, 4096, value=2400, step=64, label="Max image size (px)")
+                match_mode = gr.Radio(["exhaustive", "sequential", "spatial"], value="sequential", label="Matching mode")
+                use_gpu_sift = gr.Checkbox(True, label="Use GPU for SIFT (if available)")
+                voxel = gr.Slider(0.0, 0.05, value=0.01, step=0.005, label="Voxel downsample")
+                depth = gr.Slider(6, 12, value=9, step=1, label="Poisson depth")
+                tris = gr.Slider(0, 500_000, value=150_000, step=10_000, label="Target triangles")
+                run = gr.Button("▶ Reconstruct 3D")
+            with gr.Column(scale=1):
+                preview = gr.Model3D(label="Mesh preview", visible=False)
+                files_out = gr.Files(label="Downloads (GLB/OBJ/PLY)")
+                logs = gr.Markdown("Logs will appear here after running…")
+        run.click(run_pipeline, [gallery, max_px, match_mode, use_gpu_sift, voxel, depth, tris],
+                  [preview, files_out, logs, preview], queue=True)
+    return demo
 
 if __name__ == "__main__":
-ui().launch()
+    ui().launch()