kiui kit
A toolkit for personal use.
Install
# released
pip install kiui # install the minimal package
pip install kiui[full] # install optional dependencies
# latest
pip install git+https://github.com/ashawkey/kiuikit.git # only the minimal package
Usage
import kiui
### auto import
kiui.env() # os, glob, math, time, random, argparse
kiui.env('data') # above + np, plt, cv2, Image, ...
kiui.env('torch') # above + torch, nn, F, ...
### quick inspection of array-like object
x = torch.tensor(...)
y = np.array(...)
kiui.lo(x)
kiui.lo(x, y) # support multiple objects
kiui.lo(kiui) # or any other object (just print with name)
### io utils
# read image as-is in RGB order
img = kiui.read_image('image.png', mode='float') # mode: float (default), pil, uint8, tensor
# write image
kiui.write_image('image.png', img)
### visualization tools
img_tensor = torch.rand(3, 256, 256)
# tensor of [3, H, W], [1, H, W], [H, W] / array of [H, W ,3], [H, W, 1], [H, W] in [0, 1]
kiui.vis.plot_image(img)
kiui.vis.plot_image(img_tensor)
### mesh utils
from kiui.mesh import Mesh
mesh = Mesh.load('model.obj')
kiui.lo(mesh.v, mesh.f) # CUDA torch.Tensor suitable for nvdiffrast
mesh.write('new.obj')
mesh.write('new.glb') # support exporting to GLB/GLTF too (texture embedded).
# perceptual loss (from https://github.com/richzhang/PerceptualSimilarity)
from kiui.lpips import LPIPS
lpips = LPIPS(net='vgg').cuda()
loss = lpips(input, target) # [B, 3, H, W] image in [-1, 1]
CLI tools:
# background removal utils
python -m kiui.cli.bg --help
python -m kiui.cli.bg input.png output.png
python -m kiui.cli.bg input_folder output_folder
# openpose detector
python -m kiui.cli.pose --help
# hed edge detector
python -m kiui.cli.hed --help
# open a GUI to render a mesh (extra dependency: nvdiffrast)
python -m kiui.render --help
python -m kiui.render mesh.obj
python -m kiui.render mesh.obj --save_video out.mp4 --wogui # save 360 degree rotating video
# sr (Real-ESRGAN from https://github.com/ai-forever/Real-ESRGAN/tree/main)
python -m kiui.sr --help
python -m kiui.sr image.jpg --scale 2 # save to image_2x.jpg
1 maintainer
Release files for kiui 0.1.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kiui-0.1.8.tar.gz | 29.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kiui-0.1.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 60.8 kB
Release files / kiui-0.1.8.tar.gz
| Download URL | kiui-0.1.8.tar.gz |
|---|---|
| Size | 29.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1b05382dd25e436d450720050e4d247d6b323f70bf1d57157a242fcf9aa5f07b
|
|
BLAKE2b-256 checksum How to use checksums |
0e860be5added71bc45fd1ac46ba4bced61462ef123291cf2a28c0f8b566300b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
Release files / kiui-0.1.8-py3-none-any.whl
| Download URL | kiui-0.1.8-py3-none-any.whl |
|---|---|
| Size | 31.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2ffde8ddf362d9f16e4f28c5182620e7d83ea83369fe4b4284710b20de2c2ea8
|
|
BLAKE2b-256 checksum How to use checksums |
14774cb89c9b5955bbd0ae1019fbdf4422efe6134a67fb905b4af92126b7b632
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.4
|
