import functools import os import shutil import sys import git import gradio as gr import numpy as np import torch as torch from PIL import Image from gradio_imageslider import ImageSlider def process( pipe, path_input, ensemble_size, denoise_steps, processing_res, path_out_16bit=None, path_out_fp32=None, path_out_vis=None, _input_3d_plane_near=None, _input_3d_plane_far=None, _input_3d_embossing=None, _input_3d_filter_size=None, _input_3d_frame_near=None, ): if path_out_vis is not None: return ( [path_out_16bit, path_out_vis], [path_out_16bit, path_out_fp32, path_out_vis], ) input_image = Image.open(path_input) pipe_out = pipe( input_image, ensemble_size=ensemble_size, denoising_steps=denoise_steps, processing_res=processing_res, batch_size=1 if processing_res == 0 else 0, show_progress_bar=True, ) depth_pred = pipe_out.depth_np depth_colored = pipe_out.depth_colored depth_16bit = (depth_pred * 65535.0).astype(np.uint16) path_output_dir = os.path.splitext(path_input)[0] + "_output" os.makedirs(path_output_dir, exist_ok=True) name_base = os.path.splitext(os.path.basename(path_input))[0] path_out_fp32 = os.path.join(path_output_dir, f"{name_base}_depth_fp32.npy") path_out_16bit = os.path.join(path_output_dir, f"{name_base}_depth_16bit.png") path_out_vis = os.path.join(path_output_dir, f"{name_base}_depth_colored.png") np.save(path_out_fp32, depth_pred) Image.fromarray(depth_16bit).save(path_out_16bit, mode="I;16") depth_colored.save(path_out_vis) return ( [path_out_16bit, path_out_vis], [path_out_16bit, path_out_fp32, path_out_vis], ) def process_3d( input_image, files, size_longest_px, size_longest_cm, filter_size, plane_near, plane_far, embossing, frame_thickness, frame_near, frame_far, ): if input_image is None or len(files) < 1: raise gr.Error("Please upload an image (or use examples) and compute depth first") if plane_near >= plane_far: raise gr.Error("NEAR plane must have a value smaller than the FAR plane") # sanitize 3d viewer glb path to keep babylon.js happy path_viewer_glb_sanitized = os.path.join(os.path.dirname(path_viewer_glb), "preview.glb") if path_viewer_glb_sanitized != path_viewer_glb: os.rename(path_viewer_glb, path_viewer_glb_sanitized) path_viewer_glb = path_viewer_glb_sanitized return path_viewer_glb, [path_files_glb, path_files_stl] def run_demo_server(pipe): process_pipe = functools.partial(process, pipe) os.environ["GRADIO_ALLOW_FLAGGING"] = "never" with gr.Blocks( analytics_enabled=False, title="Geowizard Depth and Normal Estimation", css=""" #download { height: 118px; } .slider .inner { width: 5px; background: #FFF; } .viewport { aspect-ratio: 4/3; } """, ) as demo: gr.Markdown( """ """ ) with gr.Row(): with gr.Column(): input_image = gr.Image( label="Input Image", type="filepath", ) with gr.Accordion("Advanced options", open=False): ensemble_size = gr.Slider( label="Ensemble size", minimum=1, maximum=20, step=1, value=10, ) denoise_steps = gr.Slider( label="Number of denoising steps", minimum=1, maximum=20, step=1, value=10, ) processing_res = gr.Radio( [ ("Native", 0), ("Recommended", 768), ], label="Processing resolution", value=768, ) input_output_16bit = gr.File( label="Predicted depth (16-bit)", visible=False, ) input_output_fp32 = gr.File( label="Predicted depth (32-bit)", visible=False, ) input_output_vis = gr.File( label="Predicted depth (red-near, blue-far)", visible=False, ) with gr.Row(): submit_btn = gr.Button(value="Compute Depth", variant="primary") clear_btn = gr.Button(value="Clear") with gr.Column(): output_slider = ImageSlider( label="Predicted depth (red-near, blue-far)", type="filepath", show_download_button=True, show_share_button=True, interactive=False, elem_classes="slider", position=0.25, ) files = gr.Files( label="Depth outputs", elem_id="download", interactive=False, ) demo_3d_header = gr.Markdown( """
TBD result (see Pro Tips below).
""", render=False, ) demo_3d = gr.Row(render=False) with demo_3d: with gr.Column(): with gr.Accordion("3D printing demo: Main options", open=True): plane_near = gr.Slider( label="Relative position of the near plane (between 0 and 1)", minimum=0.0, maximum=1.0, step=0.001, value=0.0, ) plane_far = gr.Slider( label="Relative position of the far plane (between near and 1)", minimum=0.0, maximum=1.0, step=0.001, value=1.0, ) embossing = gr.Slider( label="Embossing level", minimum=0, maximum=100, step=1, value=20, ) with gr.Accordion("3D printing demo: Advanced options", open=False): size_longest_px = gr.Slider( label="Size (px) of the longest side", minimum=256, maximum=1024, step=256, value=512, ) size_longest_cm = gr.Slider( label="Size (cm) of the longest side", minimum=1, maximum=100, step=1, value=10, ) filter_size = gr.Slider( label="Size (px) of the smoothing filter", minimum=1, maximum=5, step=2, value=3, ) frame_thickness = gr.Slider( label="Frame thickness", minimum=0, maximum=100, step=1, value=5, ) frame_near = gr.Slider( label="Frame's near plane offset", minimum=-100, maximum=100, step=1, value=1, ) frame_far = gr.Slider( label="Frame's far plane offset", minimum=1, maximum=10, step=1, value=1, ) with gr.Row(): submit_3d = gr.Button(value="Create 3D", variant="primary") clear_3d = gr.Button(value="Clear 3D") gr.Markdown( """