Spaces:
Running
on
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Running
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Zero
batching_and_3d_printing (#4)
Browse files- add fine control (7e6bc52ce03b857bb9117339e936f295b840be37)
- .gitattributes +2 -0
- .gitignore +4 -1
- CONTRIBUTING.md +15 -0
- LICENSE.txt +177 -0
- README.md +1 -1
- app.py +551 -114
- extrude.py +322 -0
- files/bee_depth_16bit.png +0 -0
- files/bee_depth_colored.png +0 -0
- files/bee_depth_fp32.npy +3 -0
- files/bee_pred.jpg +0 -0
- files/bee_vis.jpg +0 -0
- files/cat_depth_16bit.png +0 -0
- files/cat_depth_colored.png +0 -0
- files/cat_depth_fp32.npy +3 -0
- files/cat_pred.jpg +0 -0
- files/cat_vis.jpg +0 -0
- files/einstein.jpg +0 -0
- files/einstein_depth_16bit.png +3 -0
- files/einstein_depth_colored.png +0 -0
- files/einstein_depth_fp32.npy +3 -0
- files/swings_depth_16bit.png +0 -0
- files/swings_depth_colored.png +0 -0
- files/swings_depth_fp32.npy +3 -0
- files/swings_pred.jpg +0 -0
- files/swings_vis.jpg +0 -0
- requirements.txt +11 -22
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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files/einstein_depth_fp32.npy filter=lfs diff=lfs merge=lfs -text
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files/einstein_depth_16bit.png filter=lfs diff=lfs merge=lfs -text
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.gitignore
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__pycache__
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gradio_cached_examples
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Marigold
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CONTRIBUTING.md
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## Contributing instructions
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We appreciate your interest in contributing. Please follow these guidelines:
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1. **Discuss Changes:** Start a GitHub issue to talk about your proposed change before proceeding.
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2. **Pull Requests:** Avoid unsolicited PRs. Discussion helps align with project goals.
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3. **License Agreement:** By submitting a PR, you accept our LICENSE terms.
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4. **Legal Compatibility:** Ensure your change complies with our project's objectives and licensing.
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5. **Attribution:** Credit third-party code in your PR if used.
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Please, feel free to reach out for questions or assistance. Your contributions are valued, and we're excited to work together to enhance this project!
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LICENSE.txt
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README.md
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colorFrom: blue
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sdk: gradio
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app_file: app.py
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pinned: true
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sdk: gradio
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app_file: app.py
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pinned: true
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license: cc-by-sa-4.0
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app.py
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|
123 |
|
124 |
|
125 |
if __name__ == "__main__":
|
126 |
-
|
127 |
-
iface.queue().launch(server_name="0.0.0.0", server_port=7860)
|
|
|
1 |
+
import functools
|
2 |
import os
|
3 |
import shutil
|
4 |
+
import sys
|
5 |
|
6 |
+
import git
|
7 |
import gradio as gr
|
8 |
+
import numpy as np
|
9 |
+
import torch as torch
|
10 |
+
from PIL import Image
|
11 |
|
12 |
+
from gradio_imageslider import ImageSlider
|
13 |
|
14 |
+
from extrude import extrude_depth_3d
|
15 |
+
|
16 |
+
|
17 |
+
def process(
|
18 |
+
pipe,
|
19 |
+
path_input,
|
20 |
+
ensemble_size,
|
21 |
+
denoise_steps,
|
22 |
+
processing_res,
|
23 |
+
path_out_16bit=None,
|
24 |
+
path_out_fp32=None,
|
25 |
+
path_out_vis=None,
|
26 |
+
_input_3d_plane_near=None,
|
27 |
+
_input_3d_plane_far=None,
|
28 |
+
_input_3d_embossing=None,
|
29 |
+
_input_3d_filter_size=None,
|
30 |
+
_input_3d_frame_near=None,
|
31 |
+
):
|
32 |
+
if path_out_vis is not None:
|
33 |
+
return (
|
34 |
+
[path_out_16bit, path_out_vis],
|
35 |
+
[path_out_16bit, path_out_fp32, path_out_vis],
|
36 |
+
)
|
37 |
+
|
38 |
+
input_image = Image.open(path_input)
|
39 |
+
|
40 |
+
pipe_out = pipe(
|
41 |
+
input_image,
|
42 |
+
ensemble_size=ensemble_size,
|
43 |
+
denoising_steps=denoise_steps,
|
44 |
+
processing_res=processing_res,
|
45 |
+
show_progress_bar=True,
|
46 |
+
)
|
47 |
+
|
48 |
+
depth_pred = pipe_out.depth_np
|
49 |
+
depth_colored = pipe_out.depth_colored
|
50 |
+
depth_16bit = (depth_pred * 65535.0).astype(np.uint16)
|
51 |
+
|
52 |
+
path_output_dir = os.path.splitext(path_input)[0] + "_output"
|
53 |
os.makedirs(path_output_dir, exist_ok=True)
|
|
|
54 |
|
55 |
+
name_base = os.path.splitext(os.path.basename(path_input))[0]
|
56 |
+
path_out_fp32 = os.path.join(path_output_dir, f"{name_base}_depth_fp32.npy")
|
57 |
+
path_out_16bit = os.path.join(path_output_dir, f"{name_base}_depth_16bit.png")
|
58 |
+
path_out_vis = os.path.join(path_output_dir, f"{name_base}_depth_colored.png")
|
59 |
+
|
60 |
+
np.save(path_out_fp32, depth_pred)
|
61 |
+
Image.fromarray(depth_16bit).save(path_out_16bit, mode="I;16")
|
62 |
+
depth_colored.save(path_out_vis)
|
63 |
+
|
64 |
+
return (
|
65 |
+
[path_out_16bit, path_out_vis],
|
66 |
+
[path_out_16bit, path_out_fp32, path_out_vis],
|
67 |
)
|
68 |
|
69 |
+
|
70 |
+
def process_3d(
|
71 |
+
input_image,
|
72 |
+
files,
|
73 |
+
size_longest_px,
|
74 |
+
size_longest_cm,
|
75 |
+
filter_size,
|
76 |
+
plane_near,
|
77 |
+
plane_far,
|
78 |
+
embossing,
|
79 |
+
frame_thickness,
|
80 |
+
frame_near,
|
81 |
+
frame_far,
|
82 |
+
):
|
83 |
+
if input_image is None or len(files) < 1:
|
84 |
+
raise gr.Error("Please upload an image (or use examples) and compute depth first")
|
85 |
+
|
86 |
+
if plane_near >= plane_far:
|
87 |
+
raise gr.Error("NEAR plane must have a value smaller than the FAR plane")
|
88 |
+
|
89 |
+
def _process_3d(size_longest_px, filter_size, vertex_colors, scene_lights, output_model_scale=None):
|
90 |
+
image_rgb = input_image
|
91 |
+
image_depth = files[0]
|
92 |
+
|
93 |
+
image_rgb_basename, image_rgb_ext = os.path.splitext(image_rgb)
|
94 |
+
image_depth_basename, image_depth_ext = os.path.splitext(image_depth)
|
95 |
+
|
96 |
+
image_rgb_content = Image.open(image_rgb)
|
97 |
+
image_rgb_w, image_rgb_h = image_rgb_content.width, image_rgb_content.height
|
98 |
+
image_rgb_d = max(image_rgb_w, image_rgb_h)
|
99 |
+
image_new_w = size_longest_px * image_rgb_w // image_rgb_d
|
100 |
+
image_new_h = size_longest_px * image_rgb_h // image_rgb_d
|
101 |
+
|
102 |
+
image_rgb_new = image_rgb_basename + f"_{size_longest_px}" + image_rgb_ext
|
103 |
+
image_depth_new = image_depth_basename + f"_{size_longest_px}" + image_depth_ext
|
104 |
+
image_rgb_content.resize((image_new_w, image_new_h), Image.LANCZOS).save(
|
105 |
+
image_rgb_new
|
106 |
+
)
|
107 |
+
Image.open(image_depth).resize((image_new_w, image_new_h), Image.LANCZOS).save(
|
108 |
+
image_depth_new
|
109 |
+
)
|
110 |
+
|
111 |
+
path_glb, path_stl = extrude_depth_3d(
|
112 |
+
image_rgb_new,
|
113 |
+
image_depth_new,
|
114 |
+
output_model_scale=size_longest_cm * 10 if output_model_scale is None else output_model_scale,
|
115 |
+
filter_size=filter_size,
|
116 |
+
coef_near=plane_near,
|
117 |
+
coef_far=plane_far,
|
118 |
+
emboss=embossing / 100,
|
119 |
+
f_thic=frame_thickness / 100,
|
120 |
+
f_near=frame_near / 100,
|
121 |
+
f_back=frame_far / 100,
|
122 |
+
vertex_colors=vertex_colors,
|
123 |
+
scene_lights=scene_lights,
|
124 |
+
)
|
125 |
+
|
126 |
+
return path_glb, path_stl
|
127 |
+
|
128 |
+
path_viewer_glb, _ = _process_3d(256, filter_size, vertex_colors=False, scene_lights=True, output_model_scale=1)
|
129 |
+
path_files_glb, path_files_stl = _process_3d(size_longest_px, filter_size, vertex_colors=True, scene_lights=False)
|
130 |
+
|
131 |
+
# sanitize 3d viewer glb path to keep babylon.js happy
|
132 |
+
path_viewer_glb_sanitized = os.path.join(os.path.dirname(path_viewer_glb), "preview.glb")
|
133 |
+
if path_viewer_glb_sanitized != path_viewer_glb:
|
134 |
+
os.rename(path_viewer_glb, path_viewer_glb_sanitized)
|
135 |
+
path_viewer_glb = path_viewer_glb_sanitized
|
136 |
+
|
137 |
+
return path_viewer_glb, [path_files_glb, path_files_stl]
|
138 |
+
|
139 |
+
|
140 |
+
def run_demo_server(pipe):
|
141 |
+
process_pipe = functools.partial(process, pipe)
|
142 |
+
os.environ["GRADIO_ALLOW_FLAGGING"] = "never"
|
143 |
+
|
144 |
+
with gr.Blocks(
|
145 |
+
analytics_enabled=False,
|
146 |
+
title="Marigold Depth Estimation",
|
147 |
+
css="""
|
148 |
+
#download {
|
149 |
+
height: 118px;
|
150 |
+
}
|
151 |
+
.slider .inner {
|
152 |
+
width: 5px;
|
153 |
+
background: #FFF;
|
154 |
+
}
|
155 |
+
.viewport {
|
156 |
+
aspect-ratio: 4/3;
|
157 |
+
}
|
158 |
+
""",
|
159 |
+
) as demo:
|
160 |
+
gr.Markdown(
|
161 |
+
"""
|
162 |
+
<h1 align="center">Marigold Depth Estimation</h1>
|
163 |
+
<p align="center">
|
164 |
+
<a title="Website" href="https://marigoldmonodepth.github.io/" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
|
165 |
+
<img src="https://www.obukhov.ai/img/badges/badge-website.svg">
|
166 |
+
</a>
|
167 |
+
<a title="arXiv" href="https://arxiv.org/abs/2312.02145" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
|
168 |
+
<img src="https://www.obukhov.ai/img/badges/badge-pdf.svg">
|
169 |
+
</a>
|
170 |
+
<a title="Github" href="https://github.com/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
|
171 |
+
<img src="https://img.shields.io/github/stars/prs-eth/marigold?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="badge-github-stars">
|
172 |
+
</a>
|
173 |
+
<a title="Social" href="https://twitter.com/antonobukhov1" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
|
174 |
+
<img src="https://www.obukhov.ai/img/badges/badge-social.svg" alt="social">
|
175 |
+
</a>
|
176 |
+
</p>
|
177 |
+
<p align="justify">
|
178 |
+
Marigold is the new state-of-the-art depth estimator for images in the wild.
|
179 |
+
Upload your image into the <b>left</b> side, or click any of the <b>examples</b> below.
|
180 |
+
The result will be computed and appear on the <b>right</b> in the output comparison window.
|
181 |
+
<b style="color: red;">NEW</b>: Scroll down to the new 3D printing part of the demo!
|
182 |
+
</p>
|
183 |
+
"""
|
184 |
+
)
|
185 |
+
|
186 |
+
with gr.Row():
|
187 |
+
with gr.Column():
|
188 |
+
input_image = gr.Image(
|
189 |
+
label="Input Image",
|
190 |
+
type="filepath",
|
191 |
+
)
|
192 |
+
with gr.Accordion("Advanced options", open=False):
|
193 |
+
ensemble_size = gr.Slider(
|
194 |
+
label="Ensemble size",
|
195 |
+
minimum=1,
|
196 |
+
maximum=20,
|
197 |
+
step=1,
|
198 |
+
value=10,
|
199 |
+
)
|
200 |
+
denoise_steps = gr.Slider(
|
201 |
+
label="Number of denoising steps",
|
202 |
+
minimum=1,
|
203 |
+
maximum=20,
|
204 |
+
step=1,
|
205 |
+
value=10,
|
206 |
+
)
|
207 |
+
processing_res = gr.Radio(
|
208 |
+
[
|
209 |
+
("Native", 0),
|
210 |
+
("Recommended", 768),
|
211 |
+
],
|
212 |
+
label="Processing resolution",
|
213 |
+
value=768,
|
214 |
+
)
|
215 |
+
input_output_16bit = gr.File(
|
216 |
+
label="Predicted depth (16-bit)",
|
217 |
+
visible=False,
|
218 |
+
)
|
219 |
+
input_output_fp32 = gr.File(
|
220 |
+
label="Predicted depth (32-bit)",
|
221 |
+
visible=False,
|
222 |
+
)
|
223 |
+
input_output_vis = gr.File(
|
224 |
+
label="Predicted depth (red-near, blue-far)",
|
225 |
+
visible=False,
|
226 |
+
)
|
227 |
+
with gr.Row():
|
228 |
+
submit_btn = gr.Button(value="Compute Depth", variant="primary")
|
229 |
+
clear_btn = gr.Button(value="Clear")
|
230 |
+
with gr.Column():
|
231 |
+
output_slider = ImageSlider(
|
232 |
+
label="Predicted depth (red-near, blue-far)",
|
233 |
+
type="filepath",
|
234 |
+
show_download_button=True,
|
235 |
+
show_share_button=True,
|
236 |
+
interactive=False,
|
237 |
+
elem_classes="slider",
|
238 |
+
position=0.25,
|
239 |
+
)
|
240 |
+
files = gr.Files(
|
241 |
+
label="Depth outputs",
|
242 |
+
elem_id="download",
|
243 |
+
interactive=False,
|
244 |
+
)
|
245 |
+
|
246 |
+
demo_3d_header = gr.Markdown(
|
247 |
+
"""
|
248 |
+
<h3 align="center">3D Printing Depth Maps</h3>
|
249 |
+
<p align="justify">
|
250 |
+
This part of the demo uses Marigold depth maps estimated in the previous step to create a
|
251 |
+
3D-printable model. The models are watertight, with correct normals, and exported in the STL format.
|
252 |
+
We recommended creating the first model with the default parameters and iterating on it until the best
|
253 |
+
result (see Pro Tips below).
|
254 |
+
</p>
|
255 |
+
""",
|
256 |
+
render=False,
|
257 |
+
)
|
258 |
+
|
259 |
+
demo_3d = gr.Row(render=False)
|
260 |
+
with demo_3d:
|
261 |
+
with gr.Column():
|
262 |
+
with gr.Accordion("3D printing demo: Main options", open=True):
|
263 |
+
plane_near = gr.Slider(
|
264 |
+
label="Relative position of the near plane (between 0 and 1)",
|
265 |
+
minimum=0.0,
|
266 |
+
maximum=1.0,
|
267 |
+
step=0.001,
|
268 |
+
value=0.0,
|
269 |
+
)
|
270 |
+
plane_far = gr.Slider(
|
271 |
+
label="Relative position of the far plane (between near and 1)",
|
272 |
+
minimum=0.0,
|
273 |
+
maximum=1.0,
|
274 |
+
step=0.001,
|
275 |
+
value=1.0,
|
276 |
+
)
|
277 |
+
embossing = gr.Slider(
|
278 |
+
label="Embossing level",
|
279 |
+
minimum=0,
|
280 |
+
maximum=100,
|
281 |
+
step=1,
|
282 |
+
value=20,
|
283 |
+
)
|
284 |
+
with gr.Accordion("3D printing demo: Advanced options", open=False):
|
285 |
+
size_longest_px = gr.Slider(
|
286 |
+
label="Size (px) of the longest side",
|
287 |
+
minimum=256,
|
288 |
+
maximum=1024,
|
289 |
+
step=256,
|
290 |
+
value=512,
|
291 |
+
)
|
292 |
+
size_longest_cm = gr.Slider(
|
293 |
+
label="Size (cm) of the longest side",
|
294 |
+
minimum=1,
|
295 |
+
maximum=100,
|
296 |
+
step=1,
|
297 |
+
value=10,
|
298 |
+
)
|
299 |
+
filter_size = gr.Slider(
|
300 |
+
label="Size (px) of the smoothing filter",
|
301 |
+
minimum=1,
|
302 |
+
maximum=5,
|
303 |
+
step=2,
|
304 |
+
value=3,
|
305 |
+
)
|
306 |
+
frame_thickness = gr.Slider(
|
307 |
+
label="Frame thickness",
|
308 |
+
minimum=0,
|
309 |
+
maximum=100,
|
310 |
+
step=1,
|
311 |
+
value=5,
|
312 |
+
)
|
313 |
+
frame_near = gr.Slider(
|
314 |
+
label="Frame's near plane offset",
|
315 |
+
minimum=-100,
|
316 |
+
maximum=100,
|
317 |
+
step=1,
|
318 |
+
value=1,
|
319 |
+
)
|
320 |
+
frame_far = gr.Slider(
|
321 |
+
label="Frame's far plane offset",
|
322 |
+
minimum=1,
|
323 |
+
maximum=10,
|
324 |
+
step=1,
|
325 |
+
value=1,
|
326 |
+
)
|
327 |
+
with gr.Row():
|
328 |
+
submit_3d = gr.Button(value="Create 3D", variant="primary")
|
329 |
+
clear_3d = gr.Button(value="Clear 3D")
|
330 |
+
gr.Markdown(
|
331 |
+
"""
|
332 |
+
<h5 align="center">Pro Tips</h5>
|
333 |
+
<ol>
|
334 |
+
<li><b>Re-render with new parameters</b>: Click "Clear 3D" and then "Create 3D".</li>
|
335 |
+
<li><b>Adjust 3D scale and cut-off focus</b>: Set the frame's near plane offset to the
|
336 |
+
minimum and use 3D preview to evaluate depth scaling. Repeat until the scale is correct and
|
337 |
+
everything important is in the focus. Set the optimal value for frame's near
|
338 |
+
plane offset as a last step.</li>
|
339 |
+
<li><b>Increase details</b>: Decrease size of the smoothing filter (also increases noise).</li>
|
340 |
+
</ol>
|
341 |
+
"""
|
342 |
+
)
|
343 |
+
|
344 |
+
with gr.Column():
|
345 |
+
viewer_3d = gr.Model3D(
|
346 |
+
camera_position=(75.0, 90.0, 1.25),
|
347 |
+
elem_classes="viewport",
|
348 |
+
label="3D preview (low-res, relief highlight)",
|
349 |
+
interactive=False,
|
350 |
+
)
|
351 |
+
files_3d = gr.Files(
|
352 |
+
label="3D model outputs (high-res)",
|
353 |
+
elem_id="download",
|
354 |
+
interactive=False,
|
355 |
+
)
|
356 |
+
|
357 |
+
blocks_settings_depth = [ensemble_size, denoise_steps, processing_res]
|
358 |
+
blocks_settings_3d = [plane_near, plane_far, embossing, size_longest_px, size_longest_cm, filter_size,
|
359 |
+
frame_thickness, frame_near, frame_far]
|
360 |
+
blocks_settings = blocks_settings_depth + blocks_settings_3d
|
361 |
+
map_id_to_default = {b._id: b.value for b in blocks_settings}
|
362 |
+
|
363 |
+
inputs = [
|
364 |
+
input_image,
|
365 |
+
ensemble_size,
|
366 |
+
denoise_steps,
|
367 |
+
processing_res,
|
368 |
+
input_output_16bit,
|
369 |
+
input_output_fp32,
|
370 |
+
input_output_vis,
|
371 |
+
plane_near,
|
372 |
+
plane_far,
|
373 |
+
embossing,
|
374 |
+
filter_size,
|
375 |
+
frame_near,
|
376 |
+
]
|
377 |
+
outputs = [
|
378 |
+
submit_btn,
|
379 |
+
input_image,
|
380 |
+
output_slider,
|
381 |
+
files,
|
382 |
+
]
|
383 |
+
|
384 |
+
def submit_depth_fn(*args):
|
385 |
+
out = list(process_pipe(*args))
|
386 |
+
out = [gr.Button(interactive=False), gr.Image(interactive=False)] + out
|
387 |
+
return out
|
388 |
+
|
389 |
+
submit_btn.click(
|
390 |
+
fn=submit_depth_fn,
|
391 |
+
inputs=inputs,
|
392 |
+
outputs=outputs,
|
393 |
+
concurrency_limit=1,
|
394 |
+
)
|
395 |
+
|
396 |
+
gr.Examples(
|
397 |
+
fn=submit_depth_fn,
|
398 |
+
examples=[
|
399 |
+
[
|
400 |
+
"files/bee.jpg",
|
401 |
+
10, # ensemble_size
|
402 |
+
10, # denoise_steps
|
403 |
+
768, # processing_res
|
404 |
+
"files/bee_depth_16bit.png",
|
405 |
+
"files/bee_depth_fp32.npy",
|
406 |
+
"files/bee_depth_colored.png",
|
407 |
+
0.0, # plane_near
|
408 |
+
0.5, # plane_far
|
409 |
+
20, # embossing
|
410 |
+
3, # filter_size
|
411 |
+
0, # frame_near
|
412 |
+
],
|
413 |
+
[
|
414 |
+
"files/cat.jpg",
|
415 |
+
10, # ensemble_size
|
416 |
+
10, # denoise_steps
|
417 |
+
768, # processing_res
|
418 |
+
"files/cat_depth_16bit.png",
|
419 |
+
"files/cat_depth_fp32.npy",
|
420 |
+
"files/cat_depth_colored.png",
|
421 |
+
0.0, # plane_near
|
422 |
+
0.3, # plane_far
|
423 |
+
20, # embossing
|
424 |
+
3, # filter_size
|
425 |
+
0, # frame_near
|
426 |
+
],
|
427 |
+
[
|
428 |
+
"files/swings.jpg",
|
429 |
+
10, # ensemble_size
|
430 |
+
10, # denoise_steps
|
431 |
+
768, # processing_res
|
432 |
+
"files/swings_depth_16bit.png",
|
433 |
+
"files/swings_depth_fp32.npy",
|
434 |
+
"files/swings_depth_colored.png",
|
435 |
+
0.05, # plane_near
|
436 |
+
0.25, # plane_far
|
437 |
+
10, # embossing
|
438 |
+
1, # filter_size
|
439 |
+
0, # frame_near
|
440 |
+
],
|
441 |
+
[
|
442 |
+
"files/einstein.jpg",
|
443 |
+
10, # ensemble_size
|
444 |
+
10, # denoise_steps
|
445 |
+
768, # processing_res
|
446 |
+
"files/einstein_depth_16bit.png",
|
447 |
+
"files/einstein_depth_fp32.npy",
|
448 |
+
"files/einstein_depth_colored.png",
|
449 |
+
0.0, # plane_near
|
450 |
+
0.5, # plane_far
|
451 |
+
50, # embossing
|
452 |
+
3, # filter_size
|
453 |
+
-15, # frame_near
|
454 |
+
],
|
455 |
+
],
|
456 |
+
inputs=inputs,
|
457 |
+
outputs=outputs,
|
458 |
+
cache_examples=True,
|
459 |
+
)
|
460 |
+
|
461 |
+
demo_3d_header.render()
|
462 |
+
demo_3d.render()
|
463 |
+
|
464 |
+
def clear_fn():
|
465 |
+
out = []
|
466 |
+
for b in blocks_settings:
|
467 |
+
out.append(map_id_to_default[b._id])
|
468 |
+
out += [
|
469 |
+
gr.Button(interactive=True),
|
470 |
+
gr.Button(interactive=True),
|
471 |
+
gr.Image(value=None, interactive=True),
|
472 |
+
None, None, None, None, None, None, None,
|
473 |
+
]
|
474 |
+
return out
|
475 |
+
|
476 |
+
clear_btn.click(
|
477 |
+
fn=clear_fn,
|
478 |
+
inputs=[],
|
479 |
+
outputs=blocks_settings + [
|
480 |
+
submit_btn,
|
481 |
+
submit_3d,
|
482 |
+
input_image,
|
483 |
+
input_output_16bit,
|
484 |
+
input_output_fp32,
|
485 |
+
input_output_vis,
|
486 |
+
output_slider,
|
487 |
+
files,
|
488 |
+
viewer_3d,
|
489 |
+
files_3d,
|
490 |
+
],
|
491 |
+
)
|
492 |
+
|
493 |
+
def submit_3d_fn(*args):
|
494 |
+
out = list(process_3d(*args))
|
495 |
+
out = [gr.Button(interactive=False)] + out
|
496 |
+
return out
|
497 |
+
|
498 |
+
submit_3d.click(
|
499 |
+
fn=submit_3d_fn,
|
500 |
+
inputs=[
|
501 |
+
input_image,
|
502 |
+
files,
|
503 |
+
size_longest_px,
|
504 |
+
size_longest_cm,
|
505 |
+
filter_size,
|
506 |
+
plane_near,
|
507 |
+
plane_far,
|
508 |
+
embossing,
|
509 |
+
frame_thickness,
|
510 |
+
frame_near,
|
511 |
+
frame_far,
|
512 |
+
],
|
513 |
+
outputs=[submit_3d, viewer_3d, files_3d],
|
514 |
+
concurrency_limit=1,
|
515 |
+
)
|
516 |
+
|
517 |
+
def clear_3d_fn():
|
518 |
+
return [gr.Button(interactive=True), None, None]
|
519 |
+
|
520 |
+
clear_3d.click(
|
521 |
+
fn=clear_3d_fn,
|
522 |
+
inputs=[],
|
523 |
+
outputs=[submit_3d, viewer_3d, files_3d],
|
524 |
+
)
|
525 |
+
|
526 |
+
demo.queue().launch(server_name="0.0.0.0", server_port=7860)
|
527 |
+
|
528 |
+
|
529 |
+
def prefetch_hf_cache(pipe):
|
530 |
+
process(pipe, "files/bee.jpg", 1, 1, 64)
|
531 |
+
shutil.rmtree("files/bee_output")
|
532 |
+
|
533 |
+
|
534 |
+
def main():
|
535 |
+
REPO_URL = "https://github.com/prs-eth/Marigold.git"
|
536 |
+
REPO_HASH = "22437a9d"
|
537 |
+
REPO_DIR = "Marigold"
|
538 |
+
CHECKPOINT = "Bingxin/Marigold"
|
539 |
+
|
540 |
+
if os.path.isdir(REPO_DIR):
|
541 |
+
shutil.rmtree(REPO_DIR)
|
542 |
+
repo = git.Repo.clone_from(REPO_URL, REPO_DIR)
|
543 |
+
repo.git.checkout(REPO_HASH)
|
544 |
+
|
545 |
+
sys.path.append(os.path.join(os.getcwd(), REPO_DIR))
|
546 |
+
|
547 |
+
from marigold import MarigoldPipeline
|
548 |
+
|
549 |
+
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
|
550 |
+
|
551 |
+
pipe = MarigoldPipeline.from_pretrained(CHECKPOINT)
|
552 |
+
try:
|
553 |
+
import xformers
|
554 |
+
pipe.enable_xformers_memory_efficient_attention()
|
555 |
+
except:
|
556 |
+
pass # run without xformers
|
557 |
+
|
558 |
+
pipe = pipe.to(device)
|
559 |
+
prefetch_hf_cache(pipe)
|
560 |
+
run_demo_server(pipe)
|
561 |
|
562 |
|
563 |
if __name__ == "__main__":
|
564 |
+
main()
|
|
extrude.py
ADDED
@@ -0,0 +1,322 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
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|
|
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|
|
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|
|
|
|
|
|
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|
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|
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|
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|
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|
|
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|
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|
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|
|
|
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|
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|
|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import math
|
2 |
+
import os
|
3 |
+
|
4 |
+
import numpy as np
|
5 |
+
import pygltflib
|
6 |
+
import trimesh
|
7 |
+
from PIL import Image, ImageFilter
|
8 |
+
|
9 |
+
|
10 |
+
def quaternion_multiply(q1, q2):
|
11 |
+
x1, y1, z1, w1 = q1
|
12 |
+
x2, y2, z2, w2 = q2
|
13 |
+
return [
|
14 |
+
w1 * x2 + x1 * w2 + y1 * z2 - z1 * y2,
|
15 |
+
w1 * y2 - x1 * z2 + y1 * w2 + z1 * x2,
|
16 |
+
w1 * z2 + x1 * y2 - y1 * x2 + z1 * w2,
|
17 |
+
w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2,
|
18 |
+
]
|
19 |
+
|
20 |
+
|
21 |
+
def glb_add_lights(path_input, path_output):
|
22 |
+
"""
|
23 |
+
Adds directional lights in the horizontal plane to the glb file.
|
24 |
+
:param path_input: path to input glb
|
25 |
+
:param path_output: path to output glb
|
26 |
+
:return: None
|
27 |
+
"""
|
28 |
+
glb = pygltflib.GLTF2().load(path_input)
|
29 |
+
|
30 |
+
N = 3 # default max num lights in Babylon.js is 4
|
31 |
+
angle_step = 2 * math.pi / N
|
32 |
+
elevation_angle = math.radians(75)
|
33 |
+
|
34 |
+
light_colors = [
|
35 |
+
[1.0, 0.0, 0.0],
|
36 |
+
[0.0, 1.0, 0.0],
|
37 |
+
[0.0, 0.0, 1.0],
|
38 |
+
]
|
39 |
+
|
40 |
+
lights_extension = {
|
41 |
+
"lights": [
|
42 |
+
{"type": "directional", "color": light_colors[i], "intensity": 2.0}
|
43 |
+
for i in range(N)
|
44 |
+
]
|
45 |
+
}
|
46 |
+
|
47 |
+
if "KHR_lights_punctual" not in glb.extensionsUsed:
|
48 |
+
glb.extensionsUsed.append("KHR_lights_punctual")
|
49 |
+
glb.extensions["KHR_lights_punctual"] = lights_extension
|
50 |
+
|
51 |
+
light_nodes = []
|
52 |
+
for i in range(N):
|
53 |
+
angle = i * angle_step
|
54 |
+
|
55 |
+
pos_rot = [0.0, 0.0, math.sin(angle / 2), math.cos(angle / 2)]
|
56 |
+
elev_rot = [math.sin(elevation_angle / 2), 0.0, 0.0, math.cos(elevation_angle / 2)]
|
57 |
+
rotation = quaternion_multiply(pos_rot, elev_rot)
|
58 |
+
|
59 |
+
node = {
|
60 |
+
"rotation": rotation,
|
61 |
+
"extensions": {"KHR_lights_punctual": {"light": i}},
|
62 |
+
}
|
63 |
+
light_nodes.append(node)
|
64 |
+
|
65 |
+
light_node_indices = list(range(len(glb.nodes), len(glb.nodes) + N))
|
66 |
+
glb.nodes.extend(light_nodes)
|
67 |
+
|
68 |
+
root_node_index = glb.scenes[glb.scene].nodes[0]
|
69 |
+
root_node = glb.nodes[root_node_index]
|
70 |
+
if hasattr(root_node, "children"):
|
71 |
+
root_node.children.extend(light_node_indices)
|
72 |
+
else:
|
73 |
+
root_node.children = light_node_indices
|
74 |
+
|
75 |
+
glb.save(path_output)
|
76 |
+
|
77 |
+
|
78 |
+
def extrude_depth_3d(
|
79 |
+
path_rgb,
|
80 |
+
path_depth,
|
81 |
+
output_model_scale=100,
|
82 |
+
filter_size=3,
|
83 |
+
coef_near=0.0,
|
84 |
+
coef_far=1.0,
|
85 |
+
emboss=0.3,
|
86 |
+
f_thic=0.05,
|
87 |
+
f_near=-0.15,
|
88 |
+
f_back=0.01,
|
89 |
+
vertex_colors=True,
|
90 |
+
scene_lights=True,
|
91 |
+
):
|
92 |
+
f_far_inner = -emboss
|
93 |
+
f_far_outer = f_far_inner - f_back
|
94 |
+
|
95 |
+
f_near = max(f_near, f_far_inner)
|
96 |
+
|
97 |
+
depth_image = Image.open(path_depth)
|
98 |
+
assert depth_image.mode == "I", depth_image.mode
|
99 |
+
depth_image = depth_image.filter(ImageFilter.MedianFilter(size=filter_size))
|
100 |
+
|
101 |
+
w, h = depth_image.size
|
102 |
+
d_max = max(w, h)
|
103 |
+
depth_image = np.array(depth_image).astype(np.double)
|
104 |
+
z_min, z_max = np.min(depth_image), np.max(depth_image)
|
105 |
+
depth_image = (depth_image.astype(np.double) - z_min) / (z_max - z_min)
|
106 |
+
depth_image[depth_image < coef_near] = coef_near
|
107 |
+
depth_image[depth_image > coef_far] = coef_far
|
108 |
+
depth_image = emboss * (depth_image - coef_near) / (coef_far - coef_near)
|
109 |
+
rgb_image = np.array(
|
110 |
+
Image.open(path_rgb).convert("RGB").resize((w, h), Image.Resampling.LANCZOS)
|
111 |
+
)
|
112 |
+
|
113 |
+
w_norm = w / float(d_max - 1)
|
114 |
+
h_norm = h / float(d_max - 1)
|
115 |
+
w_half = w_norm / 2
|
116 |
+
h_half = h_norm / 2
|
117 |
+
|
118 |
+
x, y = np.meshgrid(np.arange(w), np.arange(h))
|
119 |
+
x = x / float(d_max - 1) - w_half # [-w_half, w_half]
|
120 |
+
y = -y / float(d_max - 1) + h_half # [-h_half, h_half]
|
121 |
+
z = -depth_image # -depth_emboss (far) - 0 (near)
|
122 |
+
vertices_2d = np.stack((x, y, z), axis=-1)
|
123 |
+
vertices = vertices_2d.reshape(-1, 3)
|
124 |
+
colors = rgb_image[:, :, :3].reshape(-1, 3) / 255.0
|
125 |
+
|
126 |
+
faces = []
|
127 |
+
for y in range(h - 1):
|
128 |
+
for x in range(w - 1):
|
129 |
+
idx = y * w + x
|
130 |
+
faces.append([idx, idx + w, idx + 1])
|
131 |
+
faces.append([idx + 1, idx + w, idx + 1 + w])
|
132 |
+
|
133 |
+
# OUTER frame
|
134 |
+
|
135 |
+
nv = len(vertices)
|
136 |
+
vertices = np.append(
|
137 |
+
vertices,
|
138 |
+
[
|
139 |
+
[-w_half - f_thic, -h_half - f_thic, f_near], # 00
|
140 |
+
[-w_half - f_thic, -h_half - f_thic, f_far_outer], # 01
|
141 |
+
[w_half + f_thic, -h_half - f_thic, f_near], # 02
|
142 |
+
[w_half + f_thic, -h_half - f_thic, f_far_outer], # 03
|
143 |
+
[w_half + f_thic, h_half + f_thic, f_near], # 04
|
144 |
+
[w_half + f_thic, h_half + f_thic, f_far_outer], # 05
|
145 |
+
[-w_half - f_thic, h_half + f_thic, f_near], # 06
|
146 |
+
[-w_half - f_thic, h_half + f_thic, f_far_outer], # 07
|
147 |
+
],
|
148 |
+
axis=0,
|
149 |
+
)
|
150 |
+
faces.extend(
|
151 |
+
[
|
152 |
+
[nv + 0, nv + 1, nv + 2],
|
153 |
+
[nv + 2, nv + 1, nv + 3],
|
154 |
+
[nv + 2, nv + 3, nv + 4],
|
155 |
+
[nv + 4, nv + 3, nv + 5],
|
156 |
+
[nv + 4, nv + 5, nv + 6],
|
157 |
+
[nv + 6, nv + 5, nv + 7],
|
158 |
+
[nv + 6, nv + 7, nv + 0],
|
159 |
+
[nv + 0, nv + 7, nv + 1],
|
160 |
+
]
|
161 |
+
)
|
162 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * 8, axis=0)
|
163 |
+
|
164 |
+
# INNER frame
|
165 |
+
|
166 |
+
nv = len(vertices)
|
167 |
+
vertices_left_data = vertices_2d[:, 0] # H x 3
|
168 |
+
vertices_left_frame = vertices_2d[:, 0].copy() # H x 3
|
169 |
+
vertices_left_frame[:, 2] = f_near
|
170 |
+
vertices = np.append(vertices, vertices_left_data, axis=0)
|
171 |
+
vertices = np.append(vertices, vertices_left_frame, axis=0)
|
172 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * h), axis=0)
|
173 |
+
for i in range(h - 1):
|
174 |
+
nvi_d = nv + i
|
175 |
+
nvi_f = nvi_d + h
|
176 |
+
faces.append([nvi_d, nvi_f, nvi_d + 1])
|
177 |
+
faces.append([nvi_d + 1, nvi_f, nvi_f + 1])
|
178 |
+
|
179 |
+
nv = len(vertices)
|
180 |
+
vertices_right_data = vertices_2d[:, -1] # H x 3
|
181 |
+
vertices_right_frame = vertices_2d[:, -1].copy() # H x 3
|
182 |
+
vertices_right_frame[:, 2] = f_near
|
183 |
+
vertices = np.append(vertices, vertices_right_data, axis=0)
|
184 |
+
vertices = np.append(vertices, vertices_right_frame, axis=0)
|
185 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * h), axis=0)
|
186 |
+
for i in range(h - 1):
|
187 |
+
nvi_d = nv + i
|
188 |
+
nvi_f = nvi_d + h
|
189 |
+
faces.append([nvi_d, nvi_d + 1, nvi_f])
|
190 |
+
faces.append([nvi_d + 1, nvi_f + 1, nvi_f])
|
191 |
+
|
192 |
+
nv = len(vertices)
|
193 |
+
vertices_top_data = vertices_2d[0, :] # H x 3
|
194 |
+
vertices_top_frame = vertices_2d[0, :].copy() # H x 3
|
195 |
+
vertices_top_frame[:, 2] = f_near
|
196 |
+
vertices = np.append(vertices, vertices_top_data, axis=0)
|
197 |
+
vertices = np.append(vertices, vertices_top_frame, axis=0)
|
198 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * w), axis=0)
|
199 |
+
for i in range(w - 1):
|
200 |
+
nvi_d = nv + i
|
201 |
+
nvi_f = nvi_d + w
|
202 |
+
faces.append([nvi_d, nvi_d + 1, nvi_f])
|
203 |
+
faces.append([nvi_d + 1, nvi_f + 1, nvi_f])
|
204 |
+
|
205 |
+
nv = len(vertices)
|
206 |
+
vertices_bottom_data = vertices_2d[-1, :] # H x 3
|
207 |
+
vertices_bottom_frame = vertices_2d[-1, :].copy() # H x 3
|
208 |
+
vertices_bottom_frame[:, 2] = f_near
|
209 |
+
vertices = np.append(vertices, vertices_bottom_data, axis=0)
|
210 |
+
vertices = np.append(vertices, vertices_bottom_frame, axis=0)
|
211 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 * w), axis=0)
|
212 |
+
for i in range(w - 1):
|
213 |
+
nvi_d = nv + i
|
214 |
+
nvi_f = nvi_d + w
|
215 |
+
faces.append([nvi_d, nvi_f, nvi_d + 1])
|
216 |
+
faces.append([nvi_d + 1, nvi_f, nvi_f + 1])
|
217 |
+
|
218 |
+
# FRONT frame
|
219 |
+
|
220 |
+
nv = len(vertices)
|
221 |
+
vertices = np.append(
|
222 |
+
vertices,
|
223 |
+
[
|
224 |
+
[-w_half - f_thic, -h_half - f_thic, f_near],
|
225 |
+
[-w_half - f_thic, h_half + f_thic, f_near],
|
226 |
+
],
|
227 |
+
axis=0,
|
228 |
+
)
|
229 |
+
vertices = np.append(vertices, vertices_left_frame, axis=0)
|
230 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + h), axis=0)
|
231 |
+
for i in range(h - 1):
|
232 |
+
faces.append([nv, nv + 2 + i + 1, nv + 2 + i])
|
233 |
+
faces.append([nv, nv + 2, nv + 1])
|
234 |
+
|
235 |
+
nv = len(vertices)
|
236 |
+
vertices = np.append(
|
237 |
+
vertices,
|
238 |
+
[
|
239 |
+
[w_half + f_thic, h_half + f_thic, f_near],
|
240 |
+
[w_half + f_thic, -h_half - f_thic, f_near],
|
241 |
+
],
|
242 |
+
axis=0,
|
243 |
+
)
|
244 |
+
vertices = np.append(vertices, vertices_right_frame, axis=0)
|
245 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + h), axis=0)
|
246 |
+
for i in range(h - 1):
|
247 |
+
faces.append([nv, nv + 2 + i, nv + 2 + i + 1])
|
248 |
+
faces.append([nv, nv + h + 1, nv + 1])
|
249 |
+
|
250 |
+
nv = len(vertices)
|
251 |
+
vertices = np.append(
|
252 |
+
vertices,
|
253 |
+
[
|
254 |
+
[w_half + f_thic, h_half + f_thic, f_near],
|
255 |
+
[-w_half - f_thic, h_half + f_thic, f_near],
|
256 |
+
],
|
257 |
+
axis=0,
|
258 |
+
)
|
259 |
+
vertices = np.append(vertices, vertices_top_frame, axis=0)
|
260 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + w), axis=0)
|
261 |
+
for i in range(w - 1):
|
262 |
+
faces.append([nv, nv + 2 + i, nv + 2 + i + 1])
|
263 |
+
faces.append([nv, nv + 1, nv + 2])
|
264 |
+
|
265 |
+
nv = len(vertices)
|
266 |
+
vertices = np.append(
|
267 |
+
vertices,
|
268 |
+
[
|
269 |
+
[-w_half - f_thic, -h_half - f_thic, f_near],
|
270 |
+
[w_half + f_thic, -h_half - f_thic, f_near],
|
271 |
+
],
|
272 |
+
axis=0,
|
273 |
+
)
|
274 |
+
vertices = np.append(vertices, vertices_bottom_frame, axis=0)
|
275 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * (2 + w), axis=0)
|
276 |
+
for i in range(w - 1):
|
277 |
+
faces.append([nv, nv + 2 + i + 1, nv + 2 + i])
|
278 |
+
faces.append([nv, nv + 1, nv + w + 1])
|
279 |
+
|
280 |
+
# BACK frame
|
281 |
+
|
282 |
+
nv = len(vertices)
|
283 |
+
vertices = np.append(
|
284 |
+
vertices,
|
285 |
+
[
|
286 |
+
[-w_half - f_thic, -h_half - f_thic, f_far_outer], # 00
|
287 |
+
[w_half + f_thic, -h_half - f_thic, f_far_outer], # 01
|
288 |
+
[w_half + f_thic, h_half + f_thic, f_far_outer], # 02
|
289 |
+
[-w_half - f_thic, h_half + f_thic, f_far_outer], # 03
|
290 |
+
],
|
291 |
+
axis=0,
|
292 |
+
)
|
293 |
+
faces.extend(
|
294 |
+
[
|
295 |
+
[nv + 0, nv + 2, nv + 1],
|
296 |
+
[nv + 2, nv + 0, nv + 3],
|
297 |
+
]
|
298 |
+
)
|
299 |
+
colors = np.append(colors, [[0.5, 0.5, 0.5]] * 4, axis=0)
|
300 |
+
|
301 |
+
trimesh_kwargs = {}
|
302 |
+
if vertex_colors:
|
303 |
+
trimesh_kwargs["vertex_colors"] = colors
|
304 |
+
mesh = trimesh.Trimesh(vertices=vertices, faces=faces, **trimesh_kwargs)
|
305 |
+
|
306 |
+
mesh.merge_vertices()
|
307 |
+
|
308 |
+
current_max_dimension = max(mesh.extents)
|
309 |
+
scaling_factor = output_model_scale / current_max_dimension
|
310 |
+
mesh.apply_scale(scaling_factor)
|
311 |
+
|
312 |
+
path_out_base = os.path.splitext(path_depth)[0].replace("_16bit", "")
|
313 |
+
path_out_glb = path_out_base + ".glb"
|
314 |
+
path_out_stl = path_out_base + ".stl"
|
315 |
+
|
316 |
+
mesh.export(path_out_glb, file_type="glb")
|
317 |
+
if scene_lights:
|
318 |
+
glb_add_lights(path_out_glb, path_out_glb)
|
319 |
+
|
320 |
+
mesh.export(path_out_stl, file_type="stl")
|
321 |
+
|
322 |
+
return path_out_glb, path_out_stl
|
files/bee_depth_16bit.png
ADDED
files/bee_depth_colored.png
ADDED
files/bee_depth_fp32.npy
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:82bfba1b08942eea990bcda9f120bc75274f432de56d221fadbf428f85c6f22c
|
3 |
+
size 1398912
|
files/bee_pred.jpg
DELETED
Binary file (48.3 kB)
|
|
files/bee_vis.jpg
DELETED
Binary file (66.2 kB)
|
|
files/cat_depth_16bit.png
ADDED
files/cat_depth_colored.png
ADDED
files/cat_depth_fp32.npy
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b44fba3ec47bc4591d47ee2ddf8594934a89728fb8fc8d50bc9596dfe2cee831
|
3 |
+
size 1550292
|
files/cat_pred.jpg
DELETED
Binary file (40.2 kB)
|
|
files/cat_vis.jpg
DELETED
Binary file (56.5 kB)
|
|
files/einstein.jpg
ADDED
files/einstein_depth_16bit.png
ADDED
Git LFS Details
|
files/einstein_depth_colored.png
ADDED
files/einstein_depth_fp32.npy
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6306511f81c545ef9997176e067ed44d0ee6c4277788f19ffc109586be88a2f7
|
3 |
+
size 4194432
|
files/swings_depth_16bit.png
ADDED
files/swings_depth_colored.png
ADDED
files/swings_depth_fp32.npy
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b5728d846cd554d4a5e1d0e5f71d622135bca36164026b8e49668acdfa20e070
|
3 |
+
size 1398912
|
files/swings_pred.jpg
DELETED
Binary file (79.2 kB)
|
|
files/swings_vis.jpg
DELETED
Binary file (115 kB)
|
|
requirements.txt
CHANGED
@@ -1,24 +1,13 @@
|
|
1 |
-
gradio==
|
2 |
-
|
3 |
-
|
|
|
|
|
4 |
|
5 |
-
accelerate
|
6 |
-
diffusers
|
7 |
-
|
8 |
-
|
9 |
-
numpy==1.26.1
|
10 |
-
omegaconf
|
11 |
-
opencv-python
|
12 |
-
pandas
|
13 |
-
scipy==1.11.3
|
14 |
-
tabulate
|
15 |
-
tensorboard
|
16 |
torch==2.0.1
|
17 |
-
|
18 |
-
|
19 |
-
torchshow
|
20 |
-
tqdm
|
21 |
-
transformers
|
22 |
-
triton
|
23 |
-
wandb==0.14.0
|
24 |
-
xformers
|
|
|
1 |
+
gradio==4.9.1
|
2 |
+
gradio-imageslider==0.0.16
|
3 |
+
GitPython==3.1.40
|
4 |
+
pygltflib==1.16.1
|
5 |
+
trimesh==4.0.5
|
6 |
|
7 |
+
accelerate>=0.22.0
|
8 |
+
diffusers>=0.20.1
|
9 |
+
matplotlib==3.8.2
|
10 |
+
scipy==1.11.4
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
torch==2.0.1
|
12 |
+
transformers>=4.32.1
|
13 |
+
xformers==0.0.21
|
|
|
|
|
|
|
|
|
|
|
|