Add more badges (#391)

* Update README

* Update color

* Add badges in deployment

* Update badges

* Fix badges

* Add libtorch

README.md

@@ -15,11 +15,11 @@ ______________________________________________________________________
 ______________________________________________________________________
 
 [![Python Version](https://img.shields.io/badge/Python-3.6--3.10-FFD43B?logo=python)](https://pypi.org/project/yolort/)
-[![PyPI version](https://img.shields.io/pypi/v/yolort?color=3775A9&logo=PyPI&logoColor=white)](https://badge.fury.io/py/yolort)
+[![PyPI version](https://img.shields.io/pypi/v/yolort?color=4D97FF&logo=PyPI)](https://badge.fury.io/py/yolort)
 [![PyPI downloads](https://static.pepy.tech/personalized-badge/yolort?period=total&units=international_system&left_color=grey&right_color=violet&left_text=pypi%20downloads)](https://pepy.tech/project/yolort)
 [![Github downloads](https://img.shields.io/github/downloads/zhiqwang/yolov5-rt-stack/total?label=Model%20downloads&logo=PyTorch&color=FF6F00&logoColor=EE4C2C)](https://github.com/zhiqwang/yolov5-rt-stack/releases)
 [![Slack](https://img.shields.io/badge/Slack%20chat-4A154B?logo=slack&logoColor=white)](https://join.slack.com/t/yolort/shared_invite/zt-mqwc7235-940aAh8IaKYeWclrJx10SA)
-[![PRs Welcome](https://img.shields.io/badge/PRs%20welcome-4D97FF?logo=GitHub-Sponsors&logoColor=#white)](.github/CONTRIBUTING.md)
+[![PRs Welcome](https://img.shields.io/badge/PRs%20welcome-792EE5?logo=GitHub-Sponsors&logoColor=#white)](.github/CONTRIBUTING.md)
 
 [![CI testing](https://github.com/zhiqwang/yolov5-rt-stack/actions/workflows/ci-test.yml/badge.svg)](https://github.com/zhiqwang/yolov5-rt-stack/actions/workflows/ci-test.yml)
 [![Build & deploy docs](https://github.com/zhiqwang/yolov5-rt-stack/actions/workflows/gh-pages.yml/badge.svg)](https://github.com/zhiqwang/yolov5-rt-stack/tree/gh-pages)
@@ -177,7 +177,7 @@ Now, `yolort` can draw the model graph directly, checkout our [tutorial](https:/
 
 We love your input! Please see our [Contributing Guide](.github/CONTRIBUTING.md) to get started and for how to help out. Thank you to all our contributors! If you like this project please consider ⭐ this repo, as it is the simplest way to support us.
 
-[![Contributors](https://opencollective.com/yolort/contributors.svg?width=950)](https://github.com/zhiqwang/yolov5-rt-stack/graphs/contributors)
+[![Contributors](https://opencollective.com/yolort/contributors.svg?width=890&button=false)](https://opencollective.com/yolort/contributors.svg?width=890&button=true)
 
 ## 📖 Citing yolort
 

deployment/libtorch/README.md

@@ -1,13 +1,14 @@
 # LibTorch Inference
 
+![OpenCV](https://img.shields.io/badge/OpenCV-27338e?style=for-the-badge&logo=OpenCV&logoColor=white) ![LibTorch](https://img.shields.io/badge/LibTorch-EE4C2C?style=for-the-badge&logo=PyTorch&logoColor=white) ![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black) ![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white) ![macOS](https://img.shields.io/badge/macOS-000000?style=for-the-badge&logo=apple&logoColor=white)
+
 The LibTorch inference for `yolort`, both GPU and CPU are supported.
 
 ## Dependencies
 
-- Ubuntu / Windows / macOS
 - LibTorch 1.8.0+ together with corresponding TorchVision 0.9.0+
-- OpenCV 3.4+
-- CUDA 10.2 \[Optional\]
+- OpenCV
+- CUDA 10.2+ \[Optional\]
 
 *We didn't impose too strong restrictions on the version of CUDA.*
 

deployment/ncnn/README.md

@@ -1,12 +1,13 @@
 # Ncnn Inference
 
+![OpenCV](https://img.shields.io/badge/OpenCV-27338e?style=for-the-badge&logo=OpenCV&logoColor=white) ![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black) ![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white) ![macOS](https://img.shields.io/badge/macOS-000000?style=for-the-badge&logo=apple&logoColor=white)
+
 The ncnn inference for `yolort`, both GPU and CPU are supported.
 
 ## Dependencies
 
-- Ubuntu 18.04
 - ncnn
-- OpenCV 3.4+
+- OpenCV
 
 ## Usage
 

deployment/onnxruntime/README.md

@@ -1,12 +1,13 @@
 # ONNX Runtime Inference
 
+![OpenCV](https://img.shields.io/badge/OpenCV-27338e?style=for-the-badge&logo=OpenCV&logoColor=white) ![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black) ![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white) ![macOS](https://img.shields.io/badge/macOS-000000?style=for-the-badge&logo=apple&logoColor=white)
+
 The ONNX Runtime inference for `yolort`, both CPU and GPU are supported.
 
 ## Dependencies
 
-- Ubuntu 20.04 / Windows 10 / macOS
-- ONNX Runtime 1.7 +
-- OpenCV 4.5 +
+- ONNX Runtime 1.7+
+- OpenCV
 - CUDA \[Optional\]
 
 *We didn't impose too strong restrictions on the versions of dependencies.*

deployment/tensorrt/README.md

@@ -1,6 +1,6 @@
 # TensorRT Inference Example
 
-![Nvidia](https://img.shields.io/badge/NVIDIA-76B900?style=for-the-badge&logo=nvidia&logoColor=white) ![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black) ![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white)
+![OpenCV](https://img.shields.io/badge/OpenCV-27338e?style=for-the-badge&logo=OpenCV&logoColor=white) ![Nvidia](https://img.shields.io/badge/NVIDIA-76B900?style=for-the-badge&logo=nvidia&logoColor=white) ![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black) ![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white)
 
 The TensorRT inference example of `yolort`.