readme: introduce ci badges

README.md

@@ -2,16 +2,39 @@
     <img src="assets/banner.png" width="75%" alt="Torqueo logo" align="center" />
 </div>
 
+<div align="center">
+    <a href="#">
+        <img src="https://img.shields.io/badge/Python-3.7, 3.8, 3.9, 3.10-efefef">
+    </a>
+    <a href="https://github.com/serre-lab/Warped/actions/workflows/lint.yml/badge.svg">
+        <img alt="PyLint" src="https://github.com/serre-lab/Warped/actions/workflows/lint.yml/badge.svg">
+    </a>
+    <a href="https://github.com/serre-lab/Warped/actions/workflows/tox.yml/badge.svg">
+        <img alt="Tox" src="https://github.com/serre-lab/Warped/actions/workflows/tox.yml/badge.svg">
+    </a>
+    <a href="https://github.com/serre-lab/Warped/actions/workflows/publish.yml/badge.svg">
+        <img alt="Pypi" src="https://github.com/serre-lab/Warped/actions/workflows/publish.yml/badge.svg">
+    </a>
+    <a href="https://pepy.tech/project/torqueo">
+        <img alt="Pepy" src="https://static.pepy.tech/badge/torqueo">
+    </a>
+    <a href="#">
+        <img src="https://img.shields.io/badge/License-MIT-efefef">
+    </a>
+</div>
+
+**Torqueo** is a simple and hackable library for experimentation with image warping in **PyTorch**. It is designed to facilitate easy manipulation and transformation of images using various warping techniques.
+
 
 # 🚀 Getting Started with Torqueo
 
-Torqueo requires Python 3.6 or newer and several dependencies, including Numpy. Installation is straightforward with Pypi:
+**Torqueo** requires **Python 3.7** or newer and several dependencies, including **Numpy**. Installation is straightforward with **Pypi**:
 
 ```bash
 pip install torqueo
 ```
 
-With Torqueo installed, you can dive into image warping. The API is designed to be intuitive, requiring only a few hyperparameters to get started.
+With **Torqueo** installed, you can dive into image warping. The API is designed to be **intuitive**, requiring only a few hyperparameters to get started.
 
 Example usage:
 
@@ -20,23 +43,21 @@ import torch
 import timm
 from torqueo import Fisheye
 
-@tfel todo
+transformed_images = Fisheye()(images)
 ```
 
 # Examples of transformations
 
-Below are some examples of image transformations using Torqueo.
-
-|  |  ||
-|----------------|----------------|----------------|
-| ![Original Image](./assets/rabbit.jpg)<br> Original Image | ![Barrel](./assets/transformations/barrel.jpg)<br> Barrel | ![Fisheye](./assets/transformations/fisheye.jpg)<br> Fisheye  |
-| ![Perspective](./assets/transformations/perspective.jpg)<br> Perspective  | ![Pinch](./assets/transformations/pinch.jpg)<br> Pinch  | ![Spherize](./assets/transformations/spherize.jpg)<br> Spherize  |
-| ![Stretch](./assets/transformations/stretch.jpg)<br> Stretch  | ![Swirl](./assets/transformations/swirl.jpg)<br> Swirl  | ![Twirl](./assets/transformations/twirl.jpg)<br> Twirl  |
-| ![Wave](./assets/transformations/wave.jpg)<br> Wave  |   |   |
-
+Below are some examples of image transformations using **Torqueo**.
 
+|  |  |  |
+|-|-|-|
+| <img src="./assets/rabbit.jpg" width="30%" alt="Original Image"><br> **Original Image** | <img src="./assets/transformations/barrel.jpg" width="30%" alt="Barrel"><br> **Barrel** | <img src="./assets/transformations/fisheye.jpg" width="30%" alt="Fisheye"><br> **Fisheye**|
+| <img src="./assets/transformations/perspective.jpg" width="30%" alt="Perspective"><br> **Perspective** | <img src="./assets/transformations/pinch.jpg" width="30%" alt="Pinch"><br> **Pinch** | <img src="./assets/transformations/spherize.jpg" width="30%" alt="Spherize"><br> **Spherize**|
+| <img src="./assets/transformations/stretch.jpg" width="30%" alt="Stretch"><br> **Stretch** | <img src="./assets/transformations/swirl.jpg" width="30%" alt="Swirl"><br> **Swirl** | <img src="./assets/transformations/twirl.jpg" width="30%" alt="Twirl"><br> **Twirl**|
+| <img src="./assets/transformations/wave.jpg" width="30%" alt="Wave"><br> **Wave** | | |
 
 # Authors of the code
 
-- [Vipul Sharma]() - [email protected], Brown University
-- [Thomas Fel](https://thomasfel.fr) - [email protected], PhD Student DEEL (ANITI), Brown University
+- [**Vipul Sharma**]() - [email protected], Brown University
+- [**Thomas Fel**](https://thomasfel.fr) - [email protected], PhD Student DEEL (ANITI), Brown University