Spaces:
Running
Running
initial commit
Browse files- README.md +1 -1
- app.py +410 -0
- extrude.py +387 -0
- files/einstein_depth_16bit.png +3 -0
- files/einstein_rgb.jpg +3 -0
- gradio_patches/examples.py +14 -0
- requirements.txt +7 -0
README.md
CHANGED
@@ -1,5 +1,5 @@
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---
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-
title: Depth To
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emoji: π
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colorFrom: blue
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colorTo: pink
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---
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title: Depth To 3D Print
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emoji: π
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colorFrom: blue
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colorTo: pink
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app.py
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# Copyright 2023-2025 Marigold Team, ETH ZΓΌrich. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# --------------------------------------------------------------------------
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# More information about Marigold:
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# https://marigoldmonodepth.github.io
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# https://marigoldcomputervision.github.io
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# Efficient inference pipelines are now part of diffusers:
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# https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage
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# https://huggingface.co/docs/diffusers/api/pipelines/marigold
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# Examples of trained models and live demos:
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# https://huggingface.co/prs-eth
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# Related projects:
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# https://rollingdepth.github.io/
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# https://marigolddepthcompletion.github.io/
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# Citation (BibTeX):
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# https://github.com/prs-eth/Marigold#-citation
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# If you find Marigold useful, we kindly ask you to cite our papers.
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# --------------------------------------------------------------------------
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import os
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import tempfile
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import gradio as gr
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from PIL import Image
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from extrude import extrude_depth_3d
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from gradio_patches.examples import Examples
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default_seed = 2024
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default_batch_size = 4
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default_bas_plane_near = 0.0
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default_bas_plane_far = 1.0
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default_bas_embossing = 20
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default_bas_size_longest_px = 512
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default_bas_size_longest_cm = 10
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default_bas_filter_size = 3
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default_bas_frame_thickness = 5
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default_bas_frame_near = 1
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default_bas_frame_far = 1
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+
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+
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def process_bas(
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path_input_depth,
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path_input_rgb=None,
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plane_near=default_bas_plane_near,
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plane_far=default_bas_plane_far,
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embossing=default_bas_embossing,
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size_longest_px=default_bas_size_longest_px,
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size_longest_cm=default_bas_size_longest_cm,
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filter_size=default_bas_filter_size,
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frame_thickness=default_bas_frame_thickness,
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frame_near=default_bas_frame_near,
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frame_far=default_bas_frame_far,
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):
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if path_input_depth is None:
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raise gr.Error(
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"Missing image in the first pane: upload a file or use one from the gallery below."
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)
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input_depth = Image.open(path_input_depth)
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if input_depth.mode not in ("I", "I;16"):
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raise gr.Error(
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f"Input depth must be a 16-bit PNG image of a depth map, found {input_depth.mode}"
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)
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depth_longest_px = max(input_depth.size)
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+
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input_rgb = None
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if path_input_rgb is not None:
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input_rgb = Image.open(path_input_rgb).convert("RGB")
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if (
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input_depth.size[0] * input_rgb.size[1]
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!= input_depth.size[0] * input_rgb.size[1]
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):
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raise gr.Error(
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f"Inputs have incompatible dimensions: {input_depth.size} and {input_rgb.size}"
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)
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+
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if plane_near >= plane_far:
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raise gr.Error("NEAR plane must have a value smaller than the FAR plane")
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+
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name_base, name_ext = os.path.splitext(os.path.basename(path_input_depth))
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print(f"Processing bas-relief {name_base}{name_ext}")
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+
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path_output_dir = tempfile.mkdtemp()
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def _process_3d(
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size_longest_px,
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filter_size,
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vertex_colors,
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+
scene_lights,
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+
output_model_scale=None,
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prepare_for_3d_printing=False,
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zip_outputs=False,
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+
):
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image_new_w = size_longest_px * input_depth.width // depth_longest_px
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image_new_h = size_longest_px * input_depth.height // depth_longest_px
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image_new_sz = (image_new_w, image_new_h)
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108 |
+
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+
path_depth_new = os.path.join(
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path_output_dir, f"{name_base}_depth_{size_longest_px}.png"
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)
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+
(
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input_depth.convert(mode="F")
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114 |
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.resize(image_new_sz, Image.BILINEAR)
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.convert("I")
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.save(path_depth_new)
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)
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path_rgb_new = None
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119 |
+
if input_rgb is not None:
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+
path_rgb_new = os.path.join(
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path_output_dir, f"{name_base}_rgb_{size_longest_px}{name_ext}"
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)
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123 |
+
input_rgb.resize(image_new_sz, Image.LANCZOS).save(path_rgb_new)
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124 |
+
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125 |
+
path_glb, path_stl, path_obj = extrude_depth_3d(
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path_depth_new,
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+
path_rgb_new,
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+
output_model_scale=(
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size_longest_cm * 10
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130 |
+
if output_model_scale is None
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+
else output_model_scale
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),
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133 |
+
filter_size=filter_size,
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+
coef_near=plane_near,
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135 |
+
coef_far=plane_far,
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136 |
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emboss=embossing / 100,
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137 |
+
f_thic=frame_thickness / 100,
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138 |
+
f_near=frame_near / 100,
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139 |
+
f_back=frame_far / 100,
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+
vertex_colors=vertex_colors,
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141 |
+
scene_lights=scene_lights,
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+
prepare_for_3d_printing=prepare_for_3d_printing,
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zip_outputs=zip_outputs,
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+
)
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145 |
+
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return path_glb, path_stl, path_obj
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147 |
+
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148 |
+
path_viewer_glb, _, _ = _process_3d(
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149 |
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256, filter_size, vertex_colors=False, scene_lights=True, output_model_scale=1
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150 |
+
)
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151 |
+
path_files_glb, path_files_stl, path_files_obj = _process_3d(
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152 |
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size_longest_px,
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filter_size,
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154 |
+
vertex_colors=True,
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155 |
+
scene_lights=False,
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156 |
+
prepare_for_3d_printing=True,
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zip_outputs=True,
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158 |
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)
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159 |
+
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return path_viewer_glb, [path_files_glb, path_files_stl, path_files_obj]
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161 |
+
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162 |
+
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163 |
+
with gr.Blocks(
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title="Depth To 3D Print",
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165 |
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css="""
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#download {
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height: 118px;
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168 |
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}
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.viewport {
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170 |
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aspect-ratio: 4/3;
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}
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h1 {
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173 |
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text-align: center;
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display: block;
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175 |
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}
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h2 {
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text-align: center;
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178 |
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display: block;
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179 |
+
}
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180 |
+
h3 {
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181 |
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text-align: center;
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182 |
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display: block;
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183 |
+
}
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184 |
+
.md_feedback li {
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185 |
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margin-bottom: 0px !important;
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186 |
+
}
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187 |
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""",
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188 |
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head="""
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189 |
+
<script async src="https://www.googletagmanager.com/gtag/js?id=G-1FWSVCGZTG"></script>
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190 |
+
<script>
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191 |
+
window.dataLayer = window.dataLayer || [];
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192 |
+
function gtag() {dataLayer.push(arguments);}
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193 |
+
gtag('js', new Date());
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194 |
+
gtag('config', 'G-1FWSVCGZTG');
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195 |
+
</script>
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196 |
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""",
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197 |
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) as demo:
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198 |
+
gr.Markdown(
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199 |
+
"""
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200 |
+
# Depth To 3D Print
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201 |
+
<p align="center">
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202 |
+
<a title="Get Depth" href="https://huggingface.co/spaces/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
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203 |
+
<img src="https://img.shields.io/badge/π€%20Create%20Your%20-Depth%20from%20Image-blue" alt="Get Depth">
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204 |
+
</a>
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205 |
+
<a title="Website" href="https://marigoldmonodepth.github.io/" target="_blank" rel="noopener noreferrer"
|
206 |
+
style="display: inline-block;">
|
207 |
+
<img src="https://img.shields.io/badge/%F0%9F%A4%8D%20Project%20-Website-af2928" alt="Website Badge">
|
208 |
+
</a>
|
209 |
+
<a title="Social" href="https://twitter.com/antonobukhov1" target="_blank" rel="noopener noreferrer"
|
210 |
+
style="display: inline-block;">
|
211 |
+
<img src="https://www.obukhov.ai/img/badges/badge-social.svg" alt="social">
|
212 |
+
</a><br>
|
213 |
+
Start exploring the interactive bas-relief examples at the bottom of the page!
|
214 |
+
The models are watertight and exported in a variety of formats, which makes them 3D-printable.
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215 |
+
</p>
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216 |
+
"""
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217 |
+
)
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+
with gr.Row():
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219 |
+
with gr.Column():
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220 |
+
bas_depth = gr.Image(
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221 |
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label="Depth",
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222 |
+
type="filepath",
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223 |
+
format="png",
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224 |
+
image_mode=None,
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225 |
+
sources=["upload", "clipboard"],
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226 |
+
show_fullscreen_button=False,
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227 |
+
)
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228 |
+
bas_rgb = gr.Image(
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229 |
+
label="Image (optional)",
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230 |
+
type="filepath",
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231 |
+
sources=["upload", "clipboard"],
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232 |
+
show_fullscreen_button=False,
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233 |
+
)
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234 |
+
with gr.Row():
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235 |
+
bas_submit_btn = gr.Button(value="Create 3D", variant="primary")
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236 |
+
bas_reset_btn = gr.Button(value="Reset")
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237 |
+
with gr.Accordion("3D printing demo: Main options", open=True):
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238 |
+
bas_plane_near = gr.Slider(
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239 |
+
label="Near plane",
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240 |
+
minimum=0.0,
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241 |
+
maximum=1.0,
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242 |
+
step=0.001,
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243 |
+
value=default_bas_plane_near,
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244 |
+
)
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245 |
+
bas_plane_far = gr.Slider(
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246 |
+
label="Far plane",
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247 |
+
minimum=0.0,
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248 |
+
maximum=1.0,
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249 |
+
step=0.001,
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250 |
+
value=default_bas_plane_far,
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251 |
+
)
|
252 |
+
bas_embossing = gr.Slider(
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253 |
+
label="Embossing level",
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254 |
+
minimum=0,
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255 |
+
maximum=100,
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256 |
+
step=1,
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257 |
+
value=default_bas_embossing,
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258 |
+
)
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259 |
+
with gr.Accordion("3D printing demo: Advanced options", open=False):
|
260 |
+
bas_size_longest_px = gr.Slider(
|
261 |
+
label="Longest side (px)",
|
262 |
+
minimum=256,
|
263 |
+
maximum=1024,
|
264 |
+
step=256,
|
265 |
+
value=default_bas_size_longest_px,
|
266 |
+
)
|
267 |
+
bas_size_longest_cm = gr.Slider(
|
268 |
+
label="Longest side (cm)",
|
269 |
+
minimum=1,
|
270 |
+
maximum=100,
|
271 |
+
step=1,
|
272 |
+
value=default_bas_size_longest_cm,
|
273 |
+
)
|
274 |
+
bas_filter_size = gr.Slider(
|
275 |
+
label="Smooth radius",
|
276 |
+
minimum=1,
|
277 |
+
maximum=5,
|
278 |
+
step=2,
|
279 |
+
value=default_bas_filter_size,
|
280 |
+
)
|
281 |
+
bas_frame_thickness = gr.Slider(
|
282 |
+
label="Frame thickness",
|
283 |
+
minimum=0,
|
284 |
+
maximum=100,
|
285 |
+
step=1,
|
286 |
+
value=default_bas_frame_thickness,
|
287 |
+
)
|
288 |
+
bas_frame_near = gr.Slider(
|
289 |
+
label="Near offset",
|
290 |
+
minimum=-100,
|
291 |
+
maximum=100,
|
292 |
+
step=1,
|
293 |
+
value=default_bas_frame_near,
|
294 |
+
)
|
295 |
+
bas_frame_far = gr.Slider(
|
296 |
+
label="Far offset",
|
297 |
+
minimum=1,
|
298 |
+
maximum=10,
|
299 |
+
step=1,
|
300 |
+
value=default_bas_frame_far,
|
301 |
+
)
|
302 |
+
with gr.Column():
|
303 |
+
bas_output_viewer = gr.Model3D(
|
304 |
+
camera_position=(75.0, 90.0, 1.25),
|
305 |
+
elem_classes="viewport",
|
306 |
+
label="3D preview",
|
307 |
+
interactive=False,
|
308 |
+
)
|
309 |
+
bas_output_files = gr.Files(
|
310 |
+
label="3D models",
|
311 |
+
elem_id="download",
|
312 |
+
interactive=False,
|
313 |
+
)
|
314 |
+
Examples(
|
315 |
+
fn=process_bas,
|
316 |
+
examples=[
|
317 |
+
[
|
318 |
+
"files/einstein_depth_16bit.png", # input_depth
|
319 |
+
"files/einstein_rgb.jpg", # input_rgb
|
320 |
+
0.0, # plane_near
|
321 |
+
0.5, # plane_far
|
322 |
+
50, # embossing
|
323 |
+
512, # size_longest_px
|
324 |
+
10, # size_longest_cm
|
325 |
+
3, # filter_size
|
326 |
+
5, # frame_thickness
|
327 |
+
-25, # frame_near
|
328 |
+
1, # frame_far
|
329 |
+
],
|
330 |
+
],
|
331 |
+
inputs=[
|
332 |
+
bas_depth,
|
333 |
+
bas_rgb,
|
334 |
+
bas_plane_near,
|
335 |
+
bas_plane_far,
|
336 |
+
bas_embossing,
|
337 |
+
bas_size_longest_px,
|
338 |
+
bas_size_longest_cm,
|
339 |
+
bas_filter_size,
|
340 |
+
bas_frame_thickness,
|
341 |
+
bas_frame_near,
|
342 |
+
bas_frame_far,
|
343 |
+
],
|
344 |
+
outputs=[bas_output_viewer, bas_output_files],
|
345 |
+
cache_examples=True,
|
346 |
+
directory_name="outputs",
|
347 |
+
)
|
348 |
+
|
349 |
+
bas_submit_btn.click(
|
350 |
+
fn=process_bas,
|
351 |
+
inputs=[
|
352 |
+
bas_depth,
|
353 |
+
bas_rgb,
|
354 |
+
bas_plane_near,
|
355 |
+
bas_plane_far,
|
356 |
+
bas_embossing,
|
357 |
+
bas_size_longest_px,
|
358 |
+
bas_size_longest_cm,
|
359 |
+
bas_filter_size,
|
360 |
+
bas_frame_thickness,
|
361 |
+
bas_frame_near,
|
362 |
+
bas_frame_far,
|
363 |
+
],
|
364 |
+
outputs=[bas_output_viewer, bas_output_files],
|
365 |
+
)
|
366 |
+
|
367 |
+
bas_reset_btn.click(
|
368 |
+
fn=lambda: (
|
369 |
+
gr.Button(interactive=True),
|
370 |
+
None,
|
371 |
+
None,
|
372 |
+
None,
|
373 |
+
None,
|
374 |
+
default_bas_plane_near,
|
375 |
+
default_bas_plane_far,
|
376 |
+
default_bas_embossing,
|
377 |
+
default_bas_size_longest_px,
|
378 |
+
default_bas_size_longest_cm,
|
379 |
+
default_bas_filter_size,
|
380 |
+
default_bas_frame_thickness,
|
381 |
+
default_bas_frame_near,
|
382 |
+
default_bas_frame_far,
|
383 |
+
),
|
384 |
+
inputs=[],
|
385 |
+
outputs=[
|
386 |
+
bas_submit_btn,
|
387 |
+
bas_depth,
|
388 |
+
bas_rgb,
|
389 |
+
bas_output_viewer,
|
390 |
+
bas_output_files,
|
391 |
+
bas_plane_near,
|
392 |
+
bas_plane_far,
|
393 |
+
bas_embossing,
|
394 |
+
bas_size_longest_px,
|
395 |
+
bas_size_longest_cm,
|
396 |
+
bas_filter_size,
|
397 |
+
bas_frame_thickness,
|
398 |
+
bas_frame_near,
|
399 |
+
bas_frame_far,
|
400 |
+
],
|
401 |
+
)
|
402 |
+
|
403 |
+
|
404 |
+
if __name__ == "__main__":
|
405 |
+
demo.queue(
|
406 |
+
api_open=False,
|
407 |
+
).launch(
|
408 |
+
debug=True,
|
409 |
+
server_port=7860,
|
410 |
+
)
|
extrude.py
ADDED
@@ -0,0 +1,387 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Copyright 2023-2025 Marigold Team, ETH ZΓΌrich. All rights reserved.
|
2 |
+
#
|
3 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
4 |
+
# you may not use this file except in compliance with the License.
|
5 |
+
# You may obtain a copy of the License at
|
6 |
+
#
|
7 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
8 |
+
#
|
9 |
+
# Unless required by applicable law or agreed to in writing, software
|
10 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
11 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
12 |
+
# See the License for the specific language governing permissions and
|
13 |
+
# limitations under the License.
|
14 |
+
# --------------------------------------------------------------------------
|
15 |
+
# More information about Marigold:
|
16 |
+
# https://marigoldmonodepth.github.io
|
17 |
+
# https://marigoldcomputervision.github.io
|
18 |
+
# Efficient inference pipelines are now part of diffusers:
|
19 |
+
# https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage
|
20 |
+
# https://huggingface.co/docs/diffusers/api/pipelines/marigold
|
21 |
+
# Examples of trained models and live demos:
|
22 |
+
# https://huggingface.co/prs-eth
|
23 |
+
# Related projects:
|
24 |
+
# https://rollingdepth.github.io/
|
25 |
+
# https://marigolddepthcompletion.github.io/
|
26 |
+
# Citation (BibTeX):
|
27 |
+
# https://github.com/prs-eth/Marigold#-citation
|
28 |
+
# If you find Marigold useful, we kindly ask you to cite our papers.
|
29 |
+
# --------------------------------------------------------------------------
|
30 |
+
import math
|
31 |
+
import os
|
32 |
+
import zipfile
|
33 |
+
|
34 |
+
import numpy as np
|
35 |
+
import pygltflib
|
36 |
+
import trimesh
|
37 |
+
from PIL import Image
|
38 |
+
from scipy.ndimage import median_filter
|
39 |
+
|
40 |
+
|
41 |
+
def quaternion_multiply(q1, q2):
|
42 |
+
x1, y1, z1, w1 = q1
|
43 |
+
x2, y2, z2, w2 = q2
|
44 |
+
return [
|
45 |
+
w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2,
|
46 |
+
w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2,
|
47 |
+
w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2,
|
48 |
+
w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2,
|
49 |
+
]
|
50 |
+
|
51 |
+
|
52 |
+
def glb_add_lights(path_input, path_output):
|
53 |
+
"""
|
54 |
+
Adds directional lights in the horizontal plane to the glb file.
|
55 |
+
:param path_input: path to input glb
|
56 |
+
:param path_output: path to output glb
|
57 |
+
:return: None
|
58 |
+
"""
|
59 |
+
glb = pygltflib.GLTF2().load(path_input)
|
60 |
+
|
61 |
+
N = 3 # default max num lights in Babylon.js is 4
|
62 |
+
angle_step = 2 * math.pi / N
|
63 |
+
elevation_angle = math.radians(75)
|
64 |
+
|
65 |
+
light_colors = [
|
66 |
+
[1.0, 0.0, 0.0],
|
67 |
+
[0.0, 1.0, 0.0],
|
68 |
+
[0.0, 0.0, 1.0],
|
69 |
+
]
|
70 |
+
|
71 |
+
lights_extension = {
|
72 |
+
"lights": [
|
73 |
+
{"type": "directional", "color": light_colors[i], "intensity": 2.0}
|
74 |
+
for i in range(N)
|
75 |
+
]
|
76 |
+
}
|
77 |
+
|
78 |
+
if "KHR_lights_punctual" not in glb.extensionsUsed:
|
79 |
+
glb.extensionsUsed.append("KHR_lights_punctual")
|
80 |
+
glb.extensions["KHR_lights_punctual"] = lights_extension
|
81 |
+
|
82 |
+
light_nodes = []
|
83 |
+
for i in range(N):
|
84 |
+
angle = i * angle_step
|
85 |
+
|
86 |
+
pos_rot = [0.0, 0.0, math.sin(angle / 2), math.cos(angle / 2)]
|
87 |
+
elev_rot = [
|
88 |
+
math.sin(elevation_angle / 2),
|
89 |
+
0.0,
|
90 |
+
0.0,
|
91 |
+
math.cos(elevation_angle / 2),
|
92 |
+
]
|
93 |
+
rotation = quaternion_multiply(pos_rot, elev_rot)
|
94 |
+
|
95 |
+
node = {
|
96 |
+
"rotation": rotation,
|
97 |
+
"extensions": {"KHR_lights_punctual": {"light": i}},
|
98 |
+
}
|
99 |
+
light_nodes.append(node)
|
100 |
+
|
101 |
+
light_node_indices = list(range(len(glb.nodes), len(glb.nodes) + N))
|
102 |
+
glb.nodes.extend(light_nodes)
|
103 |
+
|
104 |
+
root_node_index = glb.scenes[glb.scene].nodes[0]
|
105 |
+
root_node = glb.nodes[root_node_index]
|
106 |
+
if hasattr(root_node, "children"):
|
107 |
+
root_node.children.extend(light_node_indices)
|
108 |
+
else:
|
109 |
+
root_node.children = light_node_indices
|
110 |
+
|
111 |
+
glb.save(path_output)
|
112 |
+
|
113 |
+
|
114 |
+
def extrude_depth_3d(
|
115 |
+
path_depth,
|
116 |
+
path_rgb=None,
|
117 |
+
path_out_base=None,
|
118 |
+
output_model_scale=100,
|
119 |
+
filter_size=3,
|
120 |
+
coef_near=0.0,
|
121 |
+
coef_far=1.0,
|
122 |
+
emboss=0.3,
|
123 |
+
f_thic=0.05,
|
124 |
+
f_near=-0.15,
|
125 |
+
f_back=0.01,
|
126 |
+
vertex_colors=True,
|
127 |
+
scene_lights=True,
|
128 |
+
prepare_for_3d_printing=False,
|
129 |
+
zip_outputs=False,
|
130 |
+
):
|
131 |
+
f_far_inner = -emboss
|
132 |
+
f_far_outer = f_far_inner - f_back
|
133 |
+
|
134 |
+
f_near = max(f_near, f_far_inner)
|
135 |
+
|
136 |
+
depth_image = Image.open(path_depth)
|
137 |
+
|
138 |
+
w, h = depth_image.size
|
139 |
+
d_max = max(w, h)
|
140 |
+
depth_image = np.array(depth_image).astype(np.double)
|
141 |
+
depth_image = median_filter(depth_image, size=filter_size)
|
142 |
+
z_min, z_max = np.min(depth_image), np.max(depth_image)
|
143 |
+
depth_image = (depth_image.astype(np.double) - z_min) / (z_max - z_min)
|
144 |
+
depth_image[depth_image < coef_near] = coef_near
|
145 |
+
depth_image[depth_image > coef_far] = coef_far
|
146 |
+
depth_image = emboss * (depth_image - coef_near) / (coef_far - coef_near)
|
147 |
+
rgb_image = None
|
148 |
+
if path_rgb is not None:
|
149 |
+
rgb_image = np.array(
|
150 |
+
Image.open(path_rgb).convert("RGB").resize((w, h), Image.Resampling.LANCZOS)
|
151 |
+
)
|
152 |
+
|
153 |
+
w_norm = w / float(d_max - 1)
|
154 |
+
h_norm = h / float(d_max - 1)
|
155 |
+
w_half = w_norm / 2
|
156 |
+
h_half = h_norm / 2
|
157 |
+
|
158 |
+
x, y = np.meshgrid(np.arange(w), np.arange(h))
|
159 |
+
x = x / float(d_max - 1) - w_half # [-w_half, w_half]
|
160 |
+
y = -y / float(d_max - 1) + h_half # [-h_half, h_half]
|
161 |
+
z = -depth_image # -depth_emboss (far) - 0 (near)
|
162 |
+
vertices_2d = np.stack((x, y, z), axis=-1)
|
163 |
+
vertices = vertices_2d.reshape(-1, 3)
|
164 |
+
if path_rgb is not None:
|
165 |
+
colors = rgb_image[:, :, :3].reshape(-1, 3) / 255.0
|
166 |
+
else:
|
167 |
+
colors = np.array([[0.5, 0.5, 0.5]] * (w * h))
|
168 |
+
|
169 |
+
faces = []
|
170 |
+
for y in range(h - 1):
|
171 |
+
for x in range(w - 1):
|
172 |
+
idx = y * w + x
|
173 |
+
faces.append([idx, idx + w, idx + 1])
|
174 |
+
faces.append([idx + 1, idx + w, idx + 1 + w])
|
175 |
+
|
176 |
+
# OUTER frame
|
177 |
+
|
178 |
+
nv = len(vertices)
|
179 |
+
vertices = np.append(
|
180 |
+
vertices,
|
181 |
+
[
|
182 |
+
[-w_half - f_thic, -h_half - f_thic, f_near], # 00
|
183 |
+
[-w_half - f_thic, -h_half - f_thic, f_far_outer], # 01
|
184 |
+
[w_half + f_thic, -h_half - f_thic, f_near], # 02
|
185 |
+
[w_half + f_thic, -h_half - f_thic, f_far_outer], # 03
|
186 |
+
[w_half + f_thic, h_half + f_thic, f_near], # 04
|
187 |
+
[w_half + f_thic, h_half + f_thic, f_far_outer], # 05
|
188 |
+
[-w_half - f_thic, h_half + f_thic, f_near], # 06
|
189 |
+
[-w_half - f_thic, h_half + f_thic, f_far_outer], # 07
|
190 |
+
],
|
191 |
+
axis=0,
|
192 |
+
)
|
193 |
+
faces.extend(
|
194 |
+
[
|
195 |
+
[nv + 0, nv + 1, nv + 2],
|
196 |
+
[nv + 2, nv + 1, nv + 3],
|
197 |
+
[nv + 2, nv + 3, nv + 4],
|
198 |
+
[nv + 4, nv + 3, nv + 5],
|
199 |
+
[nv + 4, nv + 5, nv + 6],
|
200 |
+
[nv + 6, nv + 5, nv + 7],
|
201 |
+
[nv + 6, nv + 7, nv + 0],
|
202 |
+
[nv + 0, nv + 7, nv + 1],
|
203 |
+
]
|
204 |
+
)
|
205 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * 8, axis=0)
|
206 |
+
|
207 |
+
# INNER frame
|
208 |
+
|
209 |
+
nv = len(vertices)
|
210 |
+
vertices_left_data = vertices_2d[:, 0] # H x 3
|
211 |
+
vertices_left_frame = vertices_2d[:, 0].copy() # H x 3
|
212 |
+
vertices_left_frame[:, 2] = f_near
|
213 |
+
vertices = np.append(vertices, vertices_left_data, axis=0)
|
214 |
+
vertices = np.append(vertices, vertices_left_frame, axis=0)
|
215 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * h), axis=0)
|
216 |
+
for i in range(h - 1):
|
217 |
+
nvi_d = nv + i
|
218 |
+
nvi_f = nvi_d + h
|
219 |
+
faces.append([nvi_d, nvi_f, nvi_d + 1])
|
220 |
+
faces.append([nvi_d + 1, nvi_f, nvi_f + 1])
|
221 |
+
|
222 |
+
nv = len(vertices)
|
223 |
+
vertices_right_data = vertices_2d[:, -1] # H x 3
|
224 |
+
vertices_right_frame = vertices_2d[:, -1].copy() # H x 3
|
225 |
+
vertices_right_frame[:, 2] = f_near
|
226 |
+
vertices = np.append(vertices, vertices_right_data, axis=0)
|
227 |
+
vertices = np.append(vertices, vertices_right_frame, axis=0)
|
228 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * h), axis=0)
|
229 |
+
for i in range(h - 1):
|
230 |
+
nvi_d = nv + i
|
231 |
+
nvi_f = nvi_d + h
|
232 |
+
faces.append([nvi_d, nvi_d + 1, nvi_f])
|
233 |
+
faces.append([nvi_d + 1, nvi_f + 1, nvi_f])
|
234 |
+
|
235 |
+
nv = len(vertices)
|
236 |
+
vertices_top_data = vertices_2d[0, :] # H x 3
|
237 |
+
vertices_top_frame = vertices_2d[0, :].copy() # H x 3
|
238 |
+
vertices_top_frame[:, 2] = f_near
|
239 |
+
vertices = np.append(vertices, vertices_top_data, axis=0)
|
240 |
+
vertices = np.append(vertices, vertices_top_frame, axis=0)
|
241 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * w), axis=0)
|
242 |
+
for i in range(w - 1):
|
243 |
+
nvi_d = nv + i
|
244 |
+
nvi_f = nvi_d + w
|
245 |
+
faces.append([nvi_d, nvi_d + 1, nvi_f])
|
246 |
+
faces.append([nvi_d + 1, nvi_f + 1, nvi_f])
|
247 |
+
|
248 |
+
nv = len(vertices)
|
249 |
+
vertices_bottom_data = vertices_2d[-1, :] # H x 3
|
250 |
+
vertices_bottom_frame = vertices_2d[-1, :].copy() # H x 3
|
251 |
+
vertices_bottom_frame[:, 2] = f_near
|
252 |
+
vertices = np.append(vertices, vertices_bottom_data, axis=0)
|
253 |
+
vertices = np.append(vertices, vertices_bottom_frame, axis=0)
|
254 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * w), axis=0)
|
255 |
+
for i in range(w - 1):
|
256 |
+
nvi_d = nv + i
|
257 |
+
nvi_f = nvi_d + w
|
258 |
+
faces.append([nvi_d, nvi_f, nvi_d + 1])
|
259 |
+
faces.append([nvi_d + 1, nvi_f, nvi_f + 1])
|
260 |
+
|
261 |
+
# FRONT frame
|
262 |
+
|
263 |
+
nv = len(vertices)
|
264 |
+
vertices = np.append(
|
265 |
+
vertices,
|
266 |
+
[
|
267 |
+
[-w_half - f_thic, -h_half - f_thic, f_near],
|
268 |
+
[-w_half - f_thic, h_half + f_thic, f_near],
|
269 |
+
],
|
270 |
+
axis=0,
|
271 |
+
)
|
272 |
+
vertices = np.append(vertices, vertices_left_frame, axis=0)
|
273 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + h), axis=0)
|
274 |
+
for i in range(h - 1):
|
275 |
+
faces.append([nv, nv + 2 + i + 1, nv + 2 + i])
|
276 |
+
faces.append([nv, nv + 2, nv + 1])
|
277 |
+
|
278 |
+
nv = len(vertices)
|
279 |
+
vertices = np.append(
|
280 |
+
vertices,
|
281 |
+
[
|
282 |
+
[w_half + f_thic, h_half + f_thic, f_near],
|
283 |
+
[w_half + f_thic, -h_half - f_thic, f_near],
|
284 |
+
],
|
285 |
+
axis=0,
|
286 |
+
)
|
287 |
+
vertices = np.append(vertices, vertices_right_frame, axis=0)
|
288 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + h), axis=0)
|
289 |
+
for i in range(h - 1):
|
290 |
+
faces.append([nv, nv + 2 + i, nv + 2 + i + 1])
|
291 |
+
faces.append([nv, nv + h + 1, nv + 1])
|
292 |
+
|
293 |
+
nv = len(vertices)
|
294 |
+
vertices = np.append(
|
295 |
+
vertices,
|
296 |
+
[
|
297 |
+
[w_half + f_thic, h_half + f_thic, f_near],
|
298 |
+
[-w_half - f_thic, h_half + f_thic, f_near],
|
299 |
+
],
|
300 |
+
axis=0,
|
301 |
+
)
|
302 |
+
vertices = np.append(vertices, vertices_top_frame, axis=0)
|
303 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + w), axis=0)
|
304 |
+
for i in range(w - 1):
|
305 |
+
faces.append([nv, nv + 2 + i, nv + 2 + i + 1])
|
306 |
+
faces.append([nv, nv + 1, nv + 2])
|
307 |
+
|
308 |
+
nv = len(vertices)
|
309 |
+
vertices = np.append(
|
310 |
+
vertices,
|
311 |
+
[
|
312 |
+
[-w_half - f_thic, -h_half - f_thic, f_near],
|
313 |
+
[w_half + f_thic, -h_half - f_thic, f_near],
|
314 |
+
],
|
315 |
+
axis=0,
|
316 |
+
)
|
317 |
+
vertices = np.append(vertices, vertices_bottom_frame, axis=0)
|
318 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + w), axis=0)
|
319 |
+
for i in range(w - 1):
|
320 |
+
faces.append([nv, nv + 2 + i + 1, nv + 2 + i])
|
321 |
+
faces.append([nv, nv + 1, nv + w + 1])
|
322 |
+
|
323 |
+
# BACK frame
|
324 |
+
|
325 |
+
nv = len(vertices)
|
326 |
+
vertices = np.append(
|
327 |
+
vertices,
|
328 |
+
[
|
329 |
+
[-w_half - f_thic, -h_half - f_thic, f_far_outer], # 00
|
330 |
+
[w_half + f_thic, -h_half - f_thic, f_far_outer], # 01
|
331 |
+
[w_half + f_thic, h_half + f_thic, f_far_outer], # 02
|
332 |
+
[-w_half - f_thic, h_half + f_thic, f_far_outer], # 03
|
333 |
+
],
|
334 |
+
axis=0,
|
335 |
+
)
|
336 |
+
faces.extend(
|
337 |
+
[
|
338 |
+
[nv + 0, nv + 2, nv + 1],
|
339 |
+
[nv + 2, nv + 0, nv + 3],
|
340 |
+
]
|
341 |
+
)
|
342 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * 4, axis=0)
|
343 |
+
|
344 |
+
trimesh_kwargs = {}
|
345 |
+
if vertex_colors:
|
346 |
+
trimesh_kwargs["vertex_colors"] = colors
|
347 |
+
mesh = trimesh.Trimesh(vertices=vertices, faces=faces, **trimesh_kwargs)
|
348 |
+
|
349 |
+
mesh.merge_vertices()
|
350 |
+
|
351 |
+
current_max_dimension = max(mesh.extents)
|
352 |
+
scaling_factor = output_model_scale / current_max_dimension
|
353 |
+
mesh.apply_scale(scaling_factor)
|
354 |
+
|
355 |
+
if prepare_for_3d_printing:
|
356 |
+
rotation_mat = trimesh.transformations.rotation_matrix(
|
357 |
+
np.radians(90), [-1, 0, 0]
|
358 |
+
)
|
359 |
+
mesh.apply_transform(rotation_mat)
|
360 |
+
|
361 |
+
if path_out_base is None:
|
362 |
+
path_out_base = os.path.splitext(path_depth)[0].replace("_16bit", "")
|
363 |
+
path_out_glb = path_out_base + ".glb"
|
364 |
+
path_out_stl = path_out_base + ".stl"
|
365 |
+
path_out_obj = path_out_base + ".obj"
|
366 |
+
|
367 |
+
mesh.export(path_out_glb, file_type="glb")
|
368 |
+
if scene_lights:
|
369 |
+
glb_add_lights(path_out_glb, path_out_glb)
|
370 |
+
mesh.export(path_out_stl, file_type="stl")
|
371 |
+
mesh.export(path_out_obj, file_type="obj")
|
372 |
+
|
373 |
+
if zip_outputs:
|
374 |
+
with zipfile.ZipFile(path_out_glb + ".zip", "w", zipfile.ZIP_DEFLATED) as zipf:
|
375 |
+
arcname = os.path.basename(os.path.splitext(path_out_glb)[0]) + ".glb"
|
376 |
+
zipf.write(path_out_glb, arcname=arcname)
|
377 |
+
path_out_glb = path_out_glb + ".zip"
|
378 |
+
with zipfile.ZipFile(path_out_stl + ".zip", "w", zipfile.ZIP_DEFLATED) as zipf:
|
379 |
+
arcname = os.path.basename(os.path.splitext(path_out_stl)[0]) + ".stl"
|
380 |
+
zipf.write(path_out_stl, arcname=arcname)
|
381 |
+
path_out_stl = path_out_stl + ".zip"
|
382 |
+
with zipfile.ZipFile(path_out_obj + ".zip", "w", zipfile.ZIP_DEFLATED) as zipf:
|
383 |
+
arcname = os.path.basename(os.path.splitext(path_out_obj)[0]) + ".obj"
|
384 |
+
zipf.write(path_out_obj, arcname=arcname)
|
385 |
+
path_out_obj = path_out_obj + ".zip"
|
386 |
+
|
387 |
+
return path_out_glb, path_out_stl, path_out_obj
|
files/einstein_depth_16bit.png
ADDED
![]() |
Git LFS Details
|
files/einstein_rgb.jpg
ADDED
![]() |
Git LFS Details
|
gradio_patches/examples.py
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from pathlib import Path
|
2 |
+
|
3 |
+
import gradio
|
4 |
+
from gradio.utils import get_cache_folder
|
5 |
+
|
6 |
+
|
7 |
+
class Examples(gradio.helpers.Examples):
|
8 |
+
def __init__(self, *args, directory_name=None, **kwargs):
|
9 |
+
super().__init__(*args, **kwargs, _initiated_directly=False)
|
10 |
+
if directory_name is not None:
|
11 |
+
self.cached_folder = get_cache_folder() / directory_name
|
12 |
+
self.cached_file = Path(self.cached_folder) / "log.csv"
|
13 |
+
self.cached_indices_file = Path(self.cached_folder) / "indices.csv"
|
14 |
+
self.create()
|
requirements.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
gradio==5.13.1
|
2 |
+
pygltflib==1.16.1
|
3 |
+
trimesh==4.0.5
|
4 |
+
imageio==2.34.1
|
5 |
+
imageio-ffmpeg==0.5.0
|
6 |
+
pillow==10.3.0
|
7 |
+
scipy==1.11.4
|