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# Introduction | ||
# CVPM Introduction | ||
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# Welcome | ||
[![Go Report Card](https://goreportcard.com/badge/github.com/unarxiv/cvpm)](https://goreportcard.com/report/github.com/unarxiv/cvpm) | ||
[![Build Status](https://travis-ci.org/unarxiv/CVPM.svg?branch=master)](https://travis-ci.org/unarxiv/CVPM) | ||
[![GitHub issues](https://img.shields.io/github/issues/unarxiv/cvpm.svg?style=flat-square)](https://github.com/unarxiv/cvpm/issues) | ||
[![GitHub license](https://img.shields.io/github/license/unarxiv/cvpm.svg?style=flat-square)](https://github.com/unarxiv/CVPM/blob/master/LICENSE) | ||
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## Introduction | ||
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CVPM is a package manager for computer vision. It helps you to download, install and run a computer vision service. | ||
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[![asciicast](https://asciinema.org/a/YRgOSy1a7WwdPyK77PEgE12Kl.png)](https://asciinema.org/a/YRgOSy1a7WwdPyK77PEgE12Kl) | ||
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## Contributing | ||
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If you found a security bugs, please do not post it in issues or any other public forum. You can send me [email](mailto:xiaozhe.yaoi@qq.com) directly. | ||
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## Affiliated Project | ||
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This project is inspired from [CVTron](https://docs.cvtron.org). | ||
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## FAQs | ||
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Q: Where can I find useful models? | ||
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A: There are three places. The first one, which is we recommend most, is our [model hub](https://hub.autoai.org), where you can download, purchase, search models. The second one is GitHub, in GiHub, you can search for CVPM_Available in readme file, which indicates that repository is compatible with CVPM. The third one is our [forum](https://forum.cvtron.xyz), where you can discuss performance of models, and ask for others models. |
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# Contribute |
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# Credit | ||
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We would like to extend our sincere appreciate for the following organizations and individuals for their kind help during the development and production of CVPM. | ||
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* [Shenzhen University](https://www.szu.edu.cn) for providing lots of general help. | ||
* [Oregon State University Open Source Lab](https://www.google.com.hk/search?q=osuosl&oq=osusl&aqs=chrome.1.69i57j0l5.2563j1j4&sourceid=chrome&ie=UTF-8) for hosting open source and public models. | ||
* [Netlify](https://www.netlify.com/) for providing CI/CD for documentation. | ||
* [Clarifai](https://clarifai.com/) for providing image recognition models. | ||
* [Amazon Web Services](https://aws.amazon.com) for providing general web services. | ||
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During the development, we are standing on the shoulders of many open source software listed below but not limited to. |
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# Install a Package | ||
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# Write a Package | ||
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## Prepare Your Model Locally | ||
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### Project Structure | ||
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Your package is firstly a Python Package. Therefore, it will look like: | ||
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``` | ||
- example_package | ||
- example_package | ||
- solver.py | ||
- bundle.py | ||
- pretrained | ||
- pretrained.toml | ||
- tests // optional | ||
- examples // optional | ||
- cvpm.toml | ||
- requirements.txt | ||
- README.md | ||
``` | ||
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### Solvers | ||
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Solver is a ```class``` extended from ```cvpm.Solver``` class. In this class, you need to implement 2 functions: ```__init__``` and ```infer```. As their literal meanings, in the ```init``` function, parameters that your infer functions use should be initiate, and in the ```infer``` function, a image file path will be passed in the parameter, and the ```infer``` function is supposed to return your result in a dict or list. | ||
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For example, a simple solver frame will look like | ||
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``` python | ||
from cvpm.solver import Solver | ||
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class SampleSolver(Solver): | ||
def __init__(self, toml_file=None): | ||
super().__init__(toml_file) | ||
# Do you Init Work here | ||
self.classifer = get_classifier() | ||
self.set_ready() | ||
def infer(self, image_file, config): | ||
# Use your own load_image method, or from cvpm.utility import load_image_file | ||
image = load_image(image_file) | ||
result = self.classifier(image) | ||
return result | ||
``` | ||
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### Bundle | ||
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::: tip | ||
This chapter and its related function may have broken changes recently. ([#64](https://github.com/unarxiv/CVPM/issues/64)) | ||
::: | ||
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### cvpm.toml | ||
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### Pre-trained models | ||
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## Publish to Model Hub | ||
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## Publish to GitHub | ||
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When publishing to GitHub, mention "CVPM Available" at the top of your README file, only if you want you model to be searchable by the Model Hub. | ||
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Your README file should be look like | ||
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``` | ||
## PROJECT NAME | ||
[CVPM-Available](https://hub.autoai.org) | ||
``` | ||
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You can look at [Face Utility](https://github.com/cvmodel/Face_Utility) for reference that we provided as an official repository. | ||
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## Best Practice |
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# Introduction | ||
# CVPM Introduction | ||
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# Welcome | ||
[![Go Report Card](https://goreportcard.com/badge/github.com/unarxiv/cvpm)](https://goreportcard.com/report/github.com/unarxiv/cvpm) | ||
[![Build Status](https://travis-ci.org/unarxiv/CVPM.svg?branch=master)](https://travis-ci.org/unarxiv/CVPM) | ||
[![GitHub issues](https://img.shields.io/github/issues/unarxiv/cvpm.svg?style=flat-square)](https://github.com/unarxiv/cvpm/issues) | ||
[![GitHub license](https://img.shields.io/github/license/unarxiv/cvpm.svg?style=flat-square)](https://github.com/unarxiv/CVPM/blob/master/LICENSE) | ||
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## Introduction | ||
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CVPM is a package manager for computer vision. It helps you to download, install and run a computer vision service. | ||
|
||
[![asciicast](https://asciinema.org/a/YRgOSy1a7WwdPyK77PEgE12Kl.png)](https://asciinema.org/a/YRgOSy1a7WwdPyK77PEgE12Kl) | ||
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## Contributing | ||
|
||
If you found a security bugs, please do not post it in issues or any other public forum. You can send me [email](mailto:xiaozhe.yaoi@qq.com) directly. | ||
|
||
## Affiliated Project | ||
|
||
This project is inspired from [CVTron](https://docs.cvtron.org). | ||
|
||
## FAQs | ||
|
||
Q: Where can I find useful models? | ||
|
||
A: There are three places. The first one, which is we recommend most, is our [model hub](https://hub.autoai.org), where you can download, purchase, search models. The second one is GitHub, in GiHub, you can search for CVPM_Available in readme file, which indicates that repository is compatible with CVPM. The third one is our [forum](https://forum.cvtron.xyz), where you can discuss performance of models, and ask for others models. |
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# 参与 |
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# 致谢 |
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# 安装及运行 |
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# 创建新的包 |
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