MiDaS function for VapourSynth
Project description
MiDaS
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer, based on https://github.com/isl-org/MiDaS.
Dependencies
- PyTorch 2.1.0 or later
- timm 0.6.13. Not compatible with 0.9.x
- VapourSynth R62 or later
Installation
pip install -U vsmidas
python -m vsmidas
Usage
from vsmidas import midas
ret = midas(clip)
See __init__.py
for the description of the parameters.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
vsmidas-1.1.0-py3-none-any.whl
(19.8 kB
view details)
File details
Details for the file vsmidas-1.1.0-py3-none-any.whl
.
File metadata
- Download URL: vsmidas-1.1.0-py3-none-any.whl
- Upload date:
- Size: 19.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 46601e3662ce97303e414c0019363f44adc9f1680ac7cfe51f28a9838a2d8dc2 |
|
MD5 | d9abd0f57d83c846d8c72f0e98c4a69e |
|
BLAKE2b-256 | 3a8318c73446ed6df0b3d68f6a03a751633d84a8e0bb9a7129d979c7eb7fe09b |