Update app.py

app.py

@@ -1,56 +1,60 @@
 import os
 
-def reconstruct(files: List[gr.File], max_img_size: int, threads: int) -> Tuple[str, str, str]:
-"""Main entry for Gradio. Returns (obj_path, obj_download, ply_download)."""
-ts = time.strftime("%Y%m%d_%H%M%S")
-run_dir = RUNS_DIR / f"run_{ts}"
-img_dir = run_dir / "images"
-run_dir.mkdir(parents=True, exist_ok=True)
+# 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)
 
-paths = [Path(f.name) for f in files]
-_save_images_to(img_dir, paths, int(max_img_size))
-
-fused = _colmap_pipeline(img_dir, run_dir, num_threads=int(threads))
-obj = _poisson_mesh_from_ply(fused)
-
-logs = run_dir / "logs.txt"
-if logs.exists():
-shutil.copy2(logs, OUT_DIR / f"logs_{ts}.txt")
-fused_out = OUT_DIR / f"fused_{ts}.ply"
-shutil.copy2(fused, fused_out)
-
-return str(obj), str(obj), str(fused_out)
+except Exception as e:
+logs.append(f"\n[ERROR]\n{e}")
+return None, None, "\n".join(logs), gr.update(visible=False)
 
 
 def ui():
-with gr.Blocks(title="Sparse2City3D: Urban massing from few photos") as demo:
+with gr.Blocks(title="Sparse Multi‑View 3D (Urban Planning)", theme=gr.themes.Soft()) as demo:
 gr.Markdown(
 """
-# Sparse2City3D
-Upload 5–30 photos of a street/building. The app runs **COLMAP** to reconstruct a dense point cloud and converts it into a coarse **OBJ** mesh for urban‑planning massing.
+# 🏙️ 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):
-files = gr.Files(label="Upload images", file_types=["image"], file_count="multiple")
-max_size = gr.Slider(800, 3200, value=2000, step=100, label="Max image size (px)")
-threads = gr.Slider(1, 8, value=4, step=1, label="# CPU threads")
-run_btn = gr.Button("Reconstruct 3D", variant="primary")
-with gr.Column(scale=3):
-model3d = gr.Model3D(label="3D preview (OBJ)")
-dl_mesh = gr.File(label="Download mesh (OBJ)")
-dl_ply = gr.File(label="Download point cloud (PLY)")
-
-def _wrap(files, max_size, threads):
-if not files:
-raise gr.Error("Please upload at least 5 images.")
-obj, obj_dl, ply_dl = reconstruct(files, int(max_size), int(threads))
-return obj, obj_dl, ply_dl
-
-run_btn.click(_wrap, inputs=[files, max_size, threads], outputs=[model3d, dl_mesh, dl_ply])
+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
 
 
 if __name__ == "__main__":
-demo = ui()
-demo.launch()
+ui().launch()