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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)") 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()
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