initial commit

README.md

@@ -1,5 +1,5 @@
 ---
-title: Depth To 3d Print
+title: Depth To 3D Print
 emoji: 🏆
 colorFrom: blue
 colorTo: pink

app.py

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+# Copyright 2023-2025 Marigold Team, ETH Zürich. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+# More information about Marigold:
+#   https://marigoldmonodepth.github.io
+#   https://marigoldcomputervision.github.io
+# Efficient inference pipelines are now part of diffusers:
+#   https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage
+#   https://huggingface.co/docs/diffusers/api/pipelines/marigold
+# Examples of trained models and live demos:
+#   https://huggingface.co/prs-eth
+# Related projects:
+#   https://rollingdepth.github.io/
+#   https://marigolddepthcompletion.github.io/
+# Citation (BibTeX):
+#   https://github.com/prs-eth/Marigold#-citation
+# If you find Marigold useful, we kindly ask you to cite our papers.
+# --------------------------------------------------------------------------
+import os
+import tempfile
+
+import gradio as gr
+from PIL import Image
+
+from extrude import extrude_depth_3d
+from gradio_patches.examples import Examples
+
+default_seed = 2024
+default_batch_size = 4
+default_bas_plane_near = 0.0
+default_bas_plane_far = 1.0
+default_bas_embossing = 20
+default_bas_size_longest_px = 512
+default_bas_size_longest_cm = 10
+default_bas_filter_size = 3
+default_bas_frame_thickness = 5
+default_bas_frame_near = 1
+default_bas_frame_far = 1
+
+
+def process_bas(
+    path_input_depth,
+    path_input_rgb=None,
+    plane_near=default_bas_plane_near,
+    plane_far=default_bas_plane_far,
+    embossing=default_bas_embossing,
+    size_longest_px=default_bas_size_longest_px,
+    size_longest_cm=default_bas_size_longest_cm,
+    filter_size=default_bas_filter_size,
+    frame_thickness=default_bas_frame_thickness,
+    frame_near=default_bas_frame_near,
+    frame_far=default_bas_frame_far,
+):
+    if path_input_depth is None:
+        raise gr.Error(
+            "Missing image in the first pane: upload a file or use one from the gallery below."
+        )
+
+    input_depth = Image.open(path_input_depth)
+    if input_depth.mode not in ("I", "I;16"):
+        raise gr.Error(
+            f"Input depth must be a 16-bit PNG image of a depth map, found {input_depth.mode}"
+        )
+    depth_longest_px = max(input_depth.size)
+
+    input_rgb = None
+    if path_input_rgb is not None:
+        input_rgb = Image.open(path_input_rgb).convert("RGB")
+        if (
+            input_depth.size[0] * input_rgb.size[1]
+            != input_depth.size[0] * input_rgb.size[1]
+        ):
+            raise gr.Error(
+                f"Inputs have incompatible dimensions: {input_depth.size} and {input_rgb.size}"
+            )
+
+    if plane_near >= plane_far:
+        raise gr.Error("NEAR plane must have a value smaller than the FAR plane")
+
+    name_base, name_ext = os.path.splitext(os.path.basename(path_input_depth))
+    print(f"Processing bas-relief {name_base}{name_ext}")
+
+    path_output_dir = tempfile.mkdtemp()
+
+    def _process_3d(
+        size_longest_px,
+        filter_size,
+        vertex_colors,
+        scene_lights,
+        output_model_scale=None,
+        prepare_for_3d_printing=False,
+        zip_outputs=False,
+    ):
+        image_new_w = size_longest_px * input_depth.width // depth_longest_px
+        image_new_h = size_longest_px * input_depth.height // depth_longest_px
+        image_new_sz = (image_new_w, image_new_h)
+
+        path_depth_new = os.path.join(
+            path_output_dir, f"{name_base}_depth_{size_longest_px}.png"
+        )
+        (
+            input_depth.convert(mode="F")
+            .resize(image_new_sz, Image.BILINEAR)
+            .convert("I")
+            .save(path_depth_new)
+        )
+        path_rgb_new = None
+        if input_rgb is not None:
+            path_rgb_new = os.path.join(
+                path_output_dir, f"{name_base}_rgb_{size_longest_px}{name_ext}"
+            )
+            input_rgb.resize(image_new_sz, Image.LANCZOS).save(path_rgb_new)
+
+        path_glb, path_stl, path_obj = extrude_depth_3d(
+            path_depth_new,
+            path_rgb_new,
+            output_model_scale=(
+                size_longest_cm * 10
+                if output_model_scale is None
+                else output_model_scale
+            ),
+            filter_size=filter_size,
+            coef_near=plane_near,
+            coef_far=plane_far,
+            emboss=embossing / 100,
+            f_thic=frame_thickness / 100,
+            f_near=frame_near / 100,
+            f_back=frame_far / 100,
+            vertex_colors=vertex_colors,
+            scene_lights=scene_lights,
+            prepare_for_3d_printing=prepare_for_3d_printing,
+            zip_outputs=zip_outputs,
+        )
+
+        return path_glb, path_stl, path_obj
+
+    path_viewer_glb, _, _ = _process_3d(
+        256, filter_size, vertex_colors=False, scene_lights=True, output_model_scale=1
+    )
+    path_files_glb, path_files_stl, path_files_obj = _process_3d(
+        size_longest_px,
+        filter_size,
+        vertex_colors=True,
+        scene_lights=False,
+        prepare_for_3d_printing=True,
+        zip_outputs=True,
+    )
+
+    return path_viewer_glb, [path_files_glb, path_files_stl, path_files_obj]
+
+
+with gr.Blocks(
+    title="Depth To 3D Print",
+    css="""
+        #download {
+            height: 118px;
+        }
+        .viewport {
+            aspect-ratio: 4/3;
+        }
+        h1 {
+            text-align: center;
+            display: block;
+        }
+        h2 {
+            text-align: center;
+            display: block;
+        }
+        h3 {
+            text-align: center;
+            display: block;
+        }
+        .md_feedback li {
+            margin-bottom: 0px !important;
+        }
+    """,
+    head="""
+        <script async src="https://www.googletagmanager.com/gtag/js?id=G-1FWSVCGZTG"></script>
+        <script>
+            window.dataLayer = window.dataLayer || [];
+            function gtag() {dataLayer.push(arguments);}
+            gtag('js', new Date());
+            gtag('config', 'G-1FWSVCGZTG');
+        </script>
+    """,
+) as demo:
+    gr.Markdown(
+        """
+        # Depth To 3D Print
+        <p align="center">
+        <a title="Get Depth" href="https://huggingface.co/spaces/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+            <img src="https://img.shields.io/badge/🤗%20Create%20Your%20-Depth%20from%20Image-blue" alt="Get Depth">
+        </a>
+        <a title="Website" href="https://marigoldmonodepth.github.io/" target="_blank" rel="noopener noreferrer" 
+                style="display: inline-block;">
+            <img src="https://img.shields.io/badge/%F0%9F%A4%8D%20Project%20-Website-af2928" alt="Website Badge">
+        </a>
+        <a title="Social" href="https://twitter.com/antonobukhov1" target="_blank" rel="noopener noreferrer" 
+                style="display: inline-block;">
+            <img src="https://www.obukhov.ai/img/badges/badge-social.svg" alt="social">
+        </a><br>
+            Start exploring the interactive bas-relief examples at the bottom of the page! 
+            The models are watertight and exported in a variety of formats, which makes them 3D-printable.
+        </p>
+    """
+    )
+    with gr.Row():
+        with gr.Column():
+            bas_depth = gr.Image(
+                label="Depth",
+                type="filepath",
+                format="png",
+                image_mode=None,
+                sources=["upload", "clipboard"],
+                show_fullscreen_button=False,
+            )
+            bas_rgb = gr.Image(
+                label="Image (optional)",
+                type="filepath",
+                sources=["upload", "clipboard"],
+                show_fullscreen_button=False,
+            )
+            with gr.Row():
+                bas_submit_btn = gr.Button(value="Create 3D", variant="primary")
+                bas_reset_btn = gr.Button(value="Reset")
+            with gr.Accordion("3D printing demo: Main options", open=True):
+                bas_plane_near = gr.Slider(
+                    label="Near plane",
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.001,
+                    value=default_bas_plane_near,
+                )
+                bas_plane_far = gr.Slider(
+                    label="Far plane",
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.001,
+                    value=default_bas_plane_far,
+                )
+                bas_embossing = gr.Slider(
+                    label="Embossing level",
+                    minimum=0,
+                    maximum=100,
+                    step=1,
+                    value=default_bas_embossing,
+                )
+            with gr.Accordion("3D printing demo: Advanced options", open=False):
+                bas_size_longest_px = gr.Slider(
+                    label="Longest side (px)",
+                    minimum=256,
+                    maximum=1024,
+                    step=256,
+                    value=default_bas_size_longest_px,
+                )
+                bas_size_longest_cm = gr.Slider(
+                    label="Longest side (cm)",
+                    minimum=1,
+                    maximum=100,
+                    step=1,
+                    value=default_bas_size_longest_cm,
+                )
+                bas_filter_size = gr.Slider(
+                    label="Smooth radius",
+                    minimum=1,
+                    maximum=5,
+                    step=2,
+                    value=default_bas_filter_size,
+                )
+                bas_frame_thickness = gr.Slider(
+                    label="Frame thickness",
+                    minimum=0,
+                    maximum=100,
+                    step=1,
+                    value=default_bas_frame_thickness,
+                )
+                bas_frame_near = gr.Slider(
+                    label="Near offset",
+                    minimum=-100,
+                    maximum=100,
+                    step=1,
+                    value=default_bas_frame_near,
+                )
+                bas_frame_far = gr.Slider(
+                    label="Far offset",
+                    minimum=1,
+                    maximum=10,
+                    step=1,
+                    value=default_bas_frame_far,
+                )
+        with gr.Column():
+            bas_output_viewer = gr.Model3D(
+                camera_position=(75.0, 90.0, 1.25),
+                elem_classes="viewport",
+                label="3D preview",
+                interactive=False,
+            )
+            bas_output_files = gr.Files(
+                label="3D models",
+                elem_id="download",
+                interactive=False,
+            )
+    Examples(
+        fn=process_bas,
+        examples=[
+            [
+                "files/einstein_depth_16bit.png",  # input_depth
+                "files/einstein_rgb.jpg",  # input_rgb
+                0.0,  # plane_near
+                0.5,  # plane_far
+                50,  # embossing
+                512,  # size_longest_px
+                10,  # size_longest_cm
+                3,  # filter_size
+                5,  # frame_thickness
+                -25,  # frame_near
+                1,  # frame_far
+            ],
+        ],
+        inputs=[
+            bas_depth,
+            bas_rgb,
+            bas_plane_near,
+            bas_plane_far,
+            bas_embossing,
+            bas_size_longest_px,
+            bas_size_longest_cm,
+            bas_filter_size,
+            bas_frame_thickness,
+            bas_frame_near,
+            bas_frame_far,
+        ],
+        outputs=[bas_output_viewer, bas_output_files],
+        cache_examples=True,
+        directory_name="outputs",
+    )
+
+    bas_submit_btn.click(
+        fn=process_bas,
+        inputs=[
+            bas_depth,
+            bas_rgb,
+            bas_plane_near,
+            bas_plane_far,
+            bas_embossing,
+            bas_size_longest_px,
+            bas_size_longest_cm,
+            bas_filter_size,
+            bas_frame_thickness,
+            bas_frame_near,
+            bas_frame_far,
+        ],
+        outputs=[bas_output_viewer, bas_output_files],
+    )
+
+    bas_reset_btn.click(
+        fn=lambda: (
+            gr.Button(interactive=True),
+            None,
+            None,
+            None,
+            None,
+            default_bas_plane_near,
+            default_bas_plane_far,
+            default_bas_embossing,
+            default_bas_size_longest_px,
+            default_bas_size_longest_cm,
+            default_bas_filter_size,
+            default_bas_frame_thickness,
+            default_bas_frame_near,
+            default_bas_frame_far,
+        ),
+        inputs=[],
+        outputs=[
+            bas_submit_btn,
+            bas_depth,
+            bas_rgb,
+            bas_output_viewer,
+            bas_output_files,
+            bas_plane_near,
+            bas_plane_far,
+            bas_embossing,
+            bas_size_longest_px,
+            bas_size_longest_cm,
+            bas_filter_size,
+            bas_frame_thickness,
+            bas_frame_near,
+            bas_frame_far,
+        ],
+    )
+
+
+if __name__ == "__main__":
+    demo.queue(
+        api_open=False,
+    ).launch(
+        debug=True,
+        server_port=7860,
+    )

extrude.py

@@ -0,0 +1,387 @@
+# Copyright 2023-2025 Marigold Team, ETH Zürich. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# --------------------------------------------------------------------------
+# More information about Marigold:
+#   https://marigoldmonodepth.github.io
+#   https://marigoldcomputervision.github.io
+# Efficient inference pipelines are now part of diffusers:
+#   https://huggingface.co/docs/diffusers/using-diffusers/marigold_usage
+#   https://huggingface.co/docs/diffusers/api/pipelines/marigold
+# Examples of trained models and live demos:
+#   https://huggingface.co/prs-eth
+# Related projects:
+#   https://rollingdepth.github.io/
+#   https://marigolddepthcompletion.github.io/
+# Citation (BibTeX):
+#   https://github.com/prs-eth/Marigold#-citation
+# If you find Marigold useful, we kindly ask you to cite our papers.
+# --------------------------------------------------------------------------
+import math
+import os
+import zipfile
+
+import numpy as np
+import pygltflib
+import trimesh
+from PIL import Image
+from scipy.ndimage import median_filter
+
+
+def quaternion_multiply(q1, q2):
+    x1, y1, z1, w1 = q1
+    x2, y2, z2, w2 = q2
+    return [
+        w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2,
+        w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2,
+        w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2,
+        w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2,
+    ]
+
+
+def glb_add_lights(path_input, path_output):
+    """
+    Adds directional lights in the horizontal plane to the glb file.
+    :param path_input: path to input glb
+    :param path_output: path to output glb
+    :return: None
+    """
+    glb = pygltflib.GLTF2().load(path_input)
+
+    N = 3  # default max num lights in Babylon.js is 4
+    angle_step = 2 * math.pi / N
+    elevation_angle = math.radians(75)
+
+    light_colors = [
+        [1.0, 0.0, 0.0],
+        [0.0, 1.0, 0.0],
+        [0.0, 0.0, 1.0],
+    ]
+
+    lights_extension = {
+        "lights": [
+            {"type": "directional", "color": light_colors[i], "intensity": 2.0}
+            for i in range(N)
+        ]
+    }
+
+    if "KHR_lights_punctual" not in glb.extensionsUsed:
+        glb.extensionsUsed.append("KHR_lights_punctual")
+    glb.extensions["KHR_lights_punctual"] = lights_extension
+
+    light_nodes = []
+    for i in range(N):
+        angle = i * angle_step
+
+        pos_rot = [0.0, 0.0, math.sin(angle / 2), math.cos(angle / 2)]
+        elev_rot = [
+            math.sin(elevation_angle / 2),
+            0.0,
+            0.0,
+            math.cos(elevation_angle / 2),
+        ]
+        rotation = quaternion_multiply(pos_rot, elev_rot)
+
+        node = {
+            "rotation": rotation,
+            "extensions": {"KHR_lights_punctual": {"light": i}},
+        }
+        light_nodes.append(node)
+
+    light_node_indices = list(range(len(glb.nodes), len(glb.nodes) + N))
+    glb.nodes.extend(light_nodes)
+
+    root_node_index = glb.scenes[glb.scene].nodes[0]
+    root_node = glb.nodes[root_node_index]
+    if hasattr(root_node, "children"):
+        root_node.children.extend(light_node_indices)
+    else:
+        root_node.children = light_node_indices
+
+    glb.save(path_output)
+
+
+def extrude_depth_3d(
+    path_depth,
+    path_rgb=None,
+    path_out_base=None,
+    output_model_scale=100,
+    filter_size=3,
+    coef_near=0.0,
+    coef_far=1.0,
+    emboss=0.3,
+    f_thic=0.05,
+    f_near=-0.15,
+    f_back=0.01,
+    vertex_colors=True,
+    scene_lights=True,
+    prepare_for_3d_printing=False,
+    zip_outputs=False,
+):
+    f_far_inner = -emboss
+    f_far_outer = f_far_inner - f_back
+
+    f_near = max(f_near, f_far_inner)
+
+    depth_image = Image.open(path_depth)
+
+    w, h = depth_image.size
+    d_max = max(w, h)
+    depth_image = np.array(depth_image).astype(np.double)
+    depth_image = median_filter(depth_image, size=filter_size)
+    z_min, z_max = np.min(depth_image), np.max(depth_image)
+    depth_image = (depth_image.astype(np.double) - z_min) / (z_max - z_min)
+    depth_image[depth_image < coef_near] = coef_near
+    depth_image[depth_image > coef_far] = coef_far
+    depth_image = emboss * (depth_image - coef_near) / (coef_far - coef_near)
+    rgb_image = None
+    if path_rgb is not None:
+        rgb_image = np.array(
+            Image.open(path_rgb).convert("RGB").resize((w, h), Image.Resampling.LANCZOS)
+        )
+
+    w_norm = w / float(d_max - 1)
+    h_norm = h / float(d_max - 1)
+    w_half = w_norm / 2
+    h_half = h_norm / 2
+
+    x, y = np.meshgrid(np.arange(w), np.arange(h))
+    x = x / float(d_max - 1) - w_half  # [-w_half, w_half]
+    y = -y / float(d_max - 1) + h_half  # [-h_half, h_half]
+    z = -depth_image  # -depth_emboss (far) - 0 (near)
+    vertices_2d = np.stack((x, y, z), axis=-1)
+    vertices = vertices_2d.reshape(-1, 3)
+    if path_rgb is not None:
+        colors = rgb_image[:, :, :3].reshape(-1, 3) / 255.0
+    else:
+        colors = np.array([[0.5, 0.5, 0.5]] * (w * h))
+
+    faces = []
+    for y in range(h - 1):
+        for x in range(w - 1):
+            idx = y * w + x
+            faces.append([idx, idx + w, idx + 1])
+            faces.append([idx + 1, idx + w, idx + 1 + w])
+
+    # OUTER frame
+
+    nv = len(vertices)
+    vertices = np.append(
+        vertices,
+        [
+            [-w_half - f_thic, -h_half - f_thic, f_near],  # 00
+            [-w_half - f_thic, -h_half - f_thic, f_far_outer],  # 01
+            [w_half + f_thic, -h_half - f_thic, f_near],  # 02
+            [w_half + f_thic, -h_half - f_thic, f_far_outer],  # 03
+            [w_half + f_thic, h_half + f_thic, f_near],  # 04
+            [w_half + f_thic, h_half + f_thic, f_far_outer],  # 05
+            [-w_half - f_thic, h_half + f_thic, f_near],  # 06
+            [-w_half - f_thic, h_half + f_thic, f_far_outer],  # 07
+        ],
+        axis=0,
+    )
+    faces.extend(
+        [
+            [nv + 0, nv + 1, nv + 2],
+            [nv + 2, nv + 1, nv + 3],
+            [nv + 2, nv + 3, nv + 4],
+            [nv + 4, nv + 3, nv + 5],
+            [nv + 4, nv + 5, nv + 6],
+            [nv + 6, nv + 5, nv + 7],
+            [nv + 6, nv + 7, nv + 0],
+            [nv + 0, nv + 7, nv + 1],
+        ]
+    )
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * 8, axis=0)
+
+    # INNER frame
+
+    nv = len(vertices)
+    vertices_left_data = vertices_2d[:, 0]  # H x 3
+    vertices_left_frame = vertices_2d[:, 0].copy()  # H x 3
+    vertices_left_frame[:, 2] = f_near
+    vertices = np.append(vertices, vertices_left_data, axis=0)
+    vertices = np.append(vertices, vertices_left_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * h), axis=0)
+    for i in range(h - 1):
+        nvi_d = nv + i
+        nvi_f = nvi_d + h
+        faces.append([nvi_d, nvi_f, nvi_d + 1])
+        faces.append([nvi_d + 1, nvi_f, nvi_f + 1])
+
+    nv = len(vertices)
+    vertices_right_data = vertices_2d[:, -1]  # H x 3
+    vertices_right_frame = vertices_2d[:, -1].copy()  # H x 3
+    vertices_right_frame[:, 2] = f_near
+    vertices = np.append(vertices, vertices_right_data, axis=0)
+    vertices = np.append(vertices, vertices_right_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * h), axis=0)
+    for i in range(h - 1):
+        nvi_d = nv + i
+        nvi_f = nvi_d + h
+        faces.append([nvi_d, nvi_d + 1, nvi_f])
+        faces.append([nvi_d + 1, nvi_f + 1, nvi_f])
+
+    nv = len(vertices)
+    vertices_top_data = vertices_2d[0, :]  # H x 3
+    vertices_top_frame = vertices_2d[0, :].copy()  # H x 3
+    vertices_top_frame[:, 2] = f_near
+    vertices = np.append(vertices, vertices_top_data, axis=0)
+    vertices = np.append(vertices, vertices_top_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * w), axis=0)
+    for i in range(w - 1):
+        nvi_d = nv + i
+        nvi_f = nvi_d + w
+        faces.append([nvi_d, nvi_d + 1, nvi_f])
+        faces.append([nvi_d + 1, nvi_f + 1, nvi_f])
+
+    nv = len(vertices)
+    vertices_bottom_data = vertices_2d[-1, :]  # H x 3
+    vertices_bottom_frame = vertices_2d[-1, :].copy()  # H x 3
+    vertices_bottom_frame[:, 2] = f_near
+    vertices = np.append(vertices, vertices_bottom_data, axis=0)
+    vertices = np.append(vertices, vertices_bottom_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * w), axis=0)
+    for i in range(w - 1):
+        nvi_d = nv + i
+        nvi_f = nvi_d + w
+        faces.append([nvi_d, nvi_f, nvi_d + 1])
+        faces.append([nvi_d + 1, nvi_f, nvi_f + 1])
+
+    # FRONT frame
+
+    nv = len(vertices)
+    vertices = np.append(
+        vertices,
+        [
+            [-w_half - f_thic, -h_half - f_thic, f_near],
+            [-w_half - f_thic, h_half + f_thic, f_near],
+        ],
+        axis=0,
+    )
+    vertices = np.append(vertices, vertices_left_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + h), axis=0)
+    for i in range(h - 1):
+        faces.append([nv, nv + 2 + i + 1, nv + 2 + i])
+    faces.append([nv, nv + 2, nv + 1])
+
+    nv = len(vertices)
+    vertices = np.append(
+        vertices,
+        [
+            [w_half + f_thic, h_half + f_thic, f_near],
+            [w_half + f_thic, -h_half - f_thic, f_near],
+        ],
+        axis=0,
+    )
+    vertices = np.append(vertices, vertices_right_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + h), axis=0)
+    for i in range(h - 1):
+        faces.append([nv, nv + 2 + i, nv + 2 + i + 1])
+    faces.append([nv, nv + h + 1, nv + 1])
+
+    nv = len(vertices)
+    vertices = np.append(
+        vertices,
+        [
+            [w_half + f_thic, h_half + f_thic, f_near],
+            [-w_half - f_thic, h_half + f_thic, f_near],
+        ],
+        axis=0,
+    )
+    vertices = np.append(vertices, vertices_top_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + w), axis=0)
+    for i in range(w - 1):
+        faces.append([nv, nv + 2 + i, nv + 2 + i + 1])
+    faces.append([nv, nv + 1, nv + 2])
+
+    nv = len(vertices)
+    vertices = np.append(
+        vertices,
+        [
+            [-w_half - f_thic, -h_half - f_thic, f_near],
+            [w_half + f_thic, -h_half - f_thic, f_near],
+        ],
+        axis=0,
+    )
+    vertices = np.append(vertices, vertices_bottom_frame, axis=0)
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + w), axis=0)
+    for i in range(w - 1):
+        faces.append([nv, nv + 2 + i + 1, nv + 2 + i])
+    faces.append([nv, nv + 1, nv + w + 1])
+
+    # BACK frame
+
+    nv = len(vertices)
+    vertices = np.append(
+        vertices,
+        [
+            [-w_half - f_thic, -h_half - f_thic, f_far_outer],  # 00
+            [w_half + f_thic, -h_half - f_thic, f_far_outer],  # 01
+            [w_half + f_thic, h_half + f_thic, f_far_outer],  # 02
+            [-w_half - f_thic, h_half + f_thic, f_far_outer],  # 03
+        ],
+        axis=0,
+    )
+    faces.extend(
+        [
+            [nv + 0, nv + 2, nv + 1],
+            [nv + 2, nv + 0, nv + 3],
+        ]
+    )
+    colors = np.append(colors, [[0.5, 0.5, 0.5]] * 4, axis=0)
+
+    trimesh_kwargs = {}
+    if vertex_colors:
+        trimesh_kwargs["vertex_colors"] = colors
+    mesh = trimesh.Trimesh(vertices=vertices, faces=faces, **trimesh_kwargs)
+
+    mesh.merge_vertices()
+
+    current_max_dimension = max(mesh.extents)
+    scaling_factor = output_model_scale / current_max_dimension
+    mesh.apply_scale(scaling_factor)
+
+    if prepare_for_3d_printing:
+        rotation_mat = trimesh.transformations.rotation_matrix(
+            np.radians(90), [-1, 0, 0]
+        )
+        mesh.apply_transform(rotation_mat)
+
+    if path_out_base is None:
+        path_out_base = os.path.splitext(path_depth)[0].replace("_16bit", "")
+    path_out_glb = path_out_base + ".glb"
+    path_out_stl = path_out_base + ".stl"
+    path_out_obj = path_out_base + ".obj"
+
+    mesh.export(path_out_glb, file_type="glb")
+    if scene_lights:
+        glb_add_lights(path_out_glb, path_out_glb)
+    mesh.export(path_out_stl, file_type="stl")
+    mesh.export(path_out_obj, file_type="obj")
+
+    if zip_outputs:
+        with zipfile.ZipFile(path_out_glb + ".zip", "w", zipfile.ZIP_DEFLATED) as zipf:
+            arcname = os.path.basename(os.path.splitext(path_out_glb)[0]) + ".glb"
+            zipf.write(path_out_glb, arcname=arcname)
+            path_out_glb = path_out_glb + ".zip"
+        with zipfile.ZipFile(path_out_stl + ".zip", "w", zipfile.ZIP_DEFLATED) as zipf:
+            arcname = os.path.basename(os.path.splitext(path_out_stl)[0]) + ".stl"
+            zipf.write(path_out_stl, arcname=arcname)
+            path_out_stl = path_out_stl + ".zip"
+        with zipfile.ZipFile(path_out_obj + ".zip", "w", zipfile.ZIP_DEFLATED) as zipf:
+            arcname = os.path.basename(os.path.splitext(path_out_obj)[0]) + ".obj"
+            zipf.write(path_out_obj, arcname=arcname)
+            path_out_obj = path_out_obj + ".zip"
+
+    return path_out_glb, path_out_stl, path_out_obj

gradio_patches/examples.py

@@ -0,0 +1,14 @@
+from pathlib import Path
+
+import gradio
+from gradio.utils import get_cache_folder
+
+
+class Examples(gradio.helpers.Examples):
+    def __init__(self, *args, directory_name=None, **kwargs):
+        super().__init__(*args, **kwargs, _initiated_directly=False)
+        if directory_name is not None:
+            self.cached_folder = get_cache_folder() / directory_name
+            self.cached_file = Path(self.cached_folder) / "log.csv"
+            self.cached_indices_file = Path(self.cached_folder) / "indices.csv"
+        self.create()

requirements.txt

@@ -0,0 +1,7 @@
+gradio==5.13.1
+pygltflib==1.16.1
+trimesh==4.0.5
+imageio==2.34.1
+imageio-ffmpeg==0.5.0
+pillow==10.3.0
+scipy==1.11.4