https://github.com/image-py/planer-zoo

toolbox of planer
https://github.com/image-py/planer-zoo

Last synced: 6 months ago
JSON representation

toolbox of planer

• Host: GitHub
• URL: https://github.com/image-py/planer-zoo
• Owner: Image-Py
• License: bsd-3-clause
• Created: 2021-04-29T08:41:26.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2022-03-06T17:05:31.000Z (over 3 years ago)
• Last Synced: 2024-09-17T09:54:33.790Z (about 1 year ago)
• Language: Python
• Size: 56.6 KB
• Stars: 4
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# planer-store

[Planer](https://github.com/Image-Py/planer) is a light-weight CNN framework implemented in pure Numpy-like interface. It can run only with Numpy. Or change different backends. (Cupy accelerated with CUDA, ClPy accelerated with OpenCL).

planer-store is a toolbox based on planer. Supportting many models, we can use them easily:

```python

import planer_store as plas

model = plas.load_model('xxx')

model.xxx ...

```

## crnn-ocr

```python

import planer_store as plas

model = plas.load_model('crnn_ocr')

img = imread('planer.jpg')

text = model.recognize(img)

# show img and result

```

![crnn-ocr](https://user-images.githubusercontent.com/24822467/116868860-25630f00-ac42-11eb-92ce-a645eb7d5a8a.png)

## face-68-key

```python

import planer_store as plas

model = plas.load_model('face_68_key')

face = imread('face.jpg')

rc = model.get_face_key(face)

thin = model.face_adjust(face, fac=-10)

fat = model.face_adjust(face, fac=10)

# show face, thin, fat

```

![face-69key](https://user-images.githubusercontent.com/24822467/116868863-25fba580-ac42-11eb-82fb-4896162b70af.png)

## hed-edge

```python

import planer_store as plas

model = plas.load_model('hed_edge')

face = imread('edge.jpg')

edge = model.hed_edge(img)

# show face, edge

```

![hed-edge](https://user-images.githubusercontent.com/24822467/116868866-26943c00-ac42-11eb-9b6e-b06776a67659.png)

## object-recognize

```python

import planer_store as plas

model = plas.load_model('resnet18')

img = imread('bus.jpg')

obj = model.recognize(img)

# show img and result

```

![object-recognize](https://user-images.githubusercontent.com/24822467/116868854-23994b80-ac42-11eb-81ce-31b945a09ccc.png)

## high-resolution

```python

import planer_store as plas

model = plas.load_model('ESRGAN')

img = imread('girl.jpg')

high = model.super_resolution(img)

# show img and high resolution result

```

![high-resolution](https://user-images.githubusercontent.com/24822467/116868867-26943c00-ac42-11eb-96b8-844f44aa63ac.png)

## cellpose

```python

import planer_store as plas

model = plas.load_model('cellpose')

img = 255 - imread('cell.png')[:,:,0]

flow = count_flow(img)

lab = flow2msk(flow, level=0.2)

edge = draw_edge(img, lab)

rgb = rgb_mask(img, lab)

# show img, flow, edge, rgbmsk

```

![cellpose](https://user-images.githubusercontent.com/24822467/116868857-24ca7880-ac42-11eb-8799-37f65a1e2421.png)

## Contribution

welcom to contribute new models.

1. use torch to train, and export as onnx

2. planer.onnx2planer('xxx.onnx')