p-ranav / merged_depth Goto Github PK
View Code? Open in Web Editor NEWMonocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
License: MIT License
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
License: MIT License
Success in setup and run (on Windows). Thank you for creating this package.
Hi, i am trying to use your code but it is impossible to download the pretrained weighs via download script. I guess the GDrive url is wrong.
Hii @p-ranav
thank so much for sharing your amazing work
i wanted to know what output image represents, is it representing absolute depth or anything proportional to absolute depth?
what are the values in average_depth
in infer.py represent?
if i want to get the absolute depth how can i get that
Thank you
In one of your response, related relative to absolute depth conversion, you mentioned : " I'm using some linear parameters to scale these to absolute depth". Could you please point to the particular code block where this transformation implemented.
Thank you.
Error received:
Traceback (most recent call last):
File "/Users/ashok/opt/anaconda3/envs/wsn/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/Users/ashok/opt/anaconda3/envs/wsn/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/Users/ashok/Desktop/wsnr/merged_depth/merged_depth/utils/download_models.py", line 65, in <module>
main()
File "/Users/ashok/Desktop/wsnr/merged_depth/merged_depth/utils/download_models.py", line 62, in main
extract_models(pretrained_models)
File "/Users/ashok/Desktop/wsnr/merged_depth/merged_depth/utils/download_models.py", line 56, in extract_models
with zipfile.ZipFile(file, 'r') as zip_ref:
File "/Users/ashok/opt/anaconda3/envs/wsn/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/Users/ashok/opt/anaconda3/envs/wsn/lib/python3.9/zipfile.py", line 1333, in _RealGetContents
raise BadZipFile("File is not a zip file")
zipfile.BadZipFile: File is not a zip file
It seems to me that the predicted values from SGDepth are inverted compared to other predictions.
(Also thank you for having this repository public! Really nice for comparing different depth networks!)
merged_depth >python utils\download_models.py
Traceback (most recent call last):
File "utils\download_models.py", line 65, in <module>
main()
File "utils\download_models.py", line 62, in main
extract_models(pretrained_models)
File "utils\download_models.py", line 56, in extract_models
with zipfile.ZipFile(file, 'r') as zip_ref:
File "c:\g\vr\lw\python\lib\zipfile.py", line 1258, in __init__
self._RealGetContents()
File "c:\g\vr\lw\python\lib\zipfile.py", line 1325, in _RealGetContents
raise BadZipFile("File is not a zip file")
zipfile.BadZipFile: File is not a zip file
When I try python3 -m merged_depth.utils.download_models
, following errors occurred
Traceback (most recent call last):
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/me/merged_depth/merged_depth/utils/download_models.py", line 65, in <module>
main()
File "/home/me/merged_depth/merged_depth/utils/download_models.py", line 62, in main
extract_models(pretrained_models)
File "/home/me/merged_depth/merged_depth/utils/download_models.py", line 56, in extract_models
with zipfile.ZipFile(file, 'r') as zip_ref:
File "/usr/lib/python3.8/zipfile.py", line 1269, in __init__
self._RealGetContents()
File "/usr/lib/python3.8/zipfile.py", line 1336, in _RealGetContents
raise BadZipFile("File is not a zip file")
zipfile.BadZipFile: File is not a zip file
The content of pretrained/pretrained.zip is
<HTML>
<HEAD>
<TITLE>Not Found</TITLE>
</HEAD>
<BODY BGCOLOR="#FFFFFF" TEXT="#000000">
<H1>Not Found</H1>
<H2>Error 404</H2>
</BODY>
</HTML>
How can I get the model?
Thanks!
Running on GTX 1060 6Gb. GPU utilization ` 0 -1%. Processed by CPU only that terribly slow.
"Standalone" Midas3 and monodepth2 utilize GPU just perfectly.
Solved by downgrading to torch from 1.9 to 1.8. This issue could be closed
It looks like you use Midas v.2.1. Any chance to upgrade to Midas v.3.0 with dpt_large-midas-2f21e586.pt model ?
I replaced the "core" Midas to Midas V.3 in the ...\merged_depth\nets and everything works just fine.
However attempt to change the model self.midas_model_path = "./pretrained/MiDaS_f6b98070.pt" to
self.midas_model_path = "./pretrained/dpt_large-midas-2f21e586.pt" throws multiple errors upon execution.
My great appreciation for your suggestion.
How to output non-stacked grayscale depth maps only?
When i run it (file version) with 19 images, RAM explotes (16 GB), how are you testing it?
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