Docker install opendronemap/nodeodm run error

The steps I performed were simple

1、install docker
2、run ”docker pull opendronemap/nodeodm"
3、run command in console “docker run -p 3000:3000 opendronemap/nodeodm"
4、Open URL in chrome “http://localhost:3000
6、in chrome upload
[INFO] use_3dmesh: False
[INFO] use_exif: False
[INFO] use_fixed_camera_params: False
[INFO] use_hybrid_bundle_adjustment: False
[INFO] verbose: False
[INFO] ==============
[INFO] Running dataset stage
[INFO] Loading dataset from: /var/www/data/552fda05-b488-4661-83d0-05733bdf343b/images
[ERROR] Not enough supported images in /var/www/data/552fda05-b488-4661-83d0-05733bdf343b/images

8、I run this on macos and contes7
9、please help me

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I checked that there is no /var/www/data/552fda05-b488-4661-83d0-05733bdf343b/images directory, is there a problem with uploading。

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I am Chinese, my English is not good, I use google translation, please forgive me if there is any inconsistency. Looking forward to your reply, thank you

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I got it, the upload should be a picture, not a zip package, the problem is solved, haha



Sorry for the trouble, but glad you got it sorted out!

Happy processing!



In the process of using, I found that the downloaded opendronemap/nodeodm is wrong, I should download opendronemap/nodeodm:gpu. Ha ha

However, when I used opendronemap/nodeodm:gpu, I found that when the cpu is fully loaded, the utilization of the gpu is extremely low, and it is only 4% at most.

My computer configuration is:
CPU: AMD Ryzen 9 5950X 16-Core Processor 3.40 GHz
RAM: 128 GB
Graphics Card: nvidia GeForce RTX 3060

I want to squeeze the hardware as much as possible to increase the processing speed, how can I do it.

Looking forward to your reply, thanks!

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I uploaded 334 images in order to generate orthophotos.
The last task 77 sheets (odm_data_aukerman-master) only ran 00:07:44.
This time the 334 images have been run at 00:32:37 and only 6% completed, I want to improve the running speed of this task


You will need to get GPU compute/passthrough working in Docker and WSL2.

You can search the forum here for some tips, or check out the official Docker and Microsoft WSL2 documentation for this.

It will require a very recent version of Windows 10 and Windows 11, as well as a proper CUDA Compute enabled NVIDIA driver.

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