Comments (2)
dwofk
commented on August 24, 2024
We use scipy v1.0.0 and v1.1.0 on our systems.
All of the pretrained models outside of the tvm folder can be loaded in PyTorch and used on any system running PyTorch; they can be used without an embedded system. Only the compiled models inside the tvm folder are limited to usage on a TX2 CPU/GPU.
from fast-depth.
soldierofhell
commented on August 24, 2024
Hi @dwofk, it would be good to add requirements.txt for exact version or in this particular case replace scipy with PIL/skimage/opencv, because imresize is depreciated in scipy.
Regards,
from fast-depth.
Related Issues (20)
- module **scipy.misc** has no attribute *imresize* HOT 1
- Strange Depth Output Image HOT 3
- Why did you do the processing in this way?
- train transform
- can't decompression model
- nyuv2 data problem
- Distance Calculation
- GPU compilation error
- Why you saved the entire model instead of state_dict .. ? HOT 1
- How to train models? HOT 3
- Is there any way to solve the problem?
- Memory Error
- I have problem with using models, AssertionError: => no model found at
- Can I use Sparse-to-dense on Jetson TX2? HOT 1
- How to inference trained model on local environment(ex.window or ubuntu)
- Is NYUv2 rectified?
- Pretrained model link is broken HOT 1
- NYUv2 preprocessed data link doesn't work HOT 2
- Weights
- weird result after running "Evaluation" HOT 1
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from fast-depth.