Agile SVG maker for python

Related tags

Deep LearningASVG
Overview

Agile SVG Maker

Need to draw hundreds of frames for a GIF? Need to change the style of all pictures in a PPT? Need to draw similar images with different parameters? Try ASVG!

Under construction, not so agile yet...

Basically aimed at academic illustrations.

Simple Example

from ASVG import *

# A 500x300 canvas
a = Axis((500, 300)) 

# Draw a rectangle on a, at level 1, from (0,0) to (200,100)
# With (5,5) round corner, fill with red color.
rect(a, 1, 0, 0, 200, 100, 5, 5, fill='red')

# Draw a circle on a, at level 3
# Centered (50,50) with 50 radius, fill with blue color.
circle(a, 3, 50, 50, 50, fill='blue')

# Draw this picture to example.svg
draw(a, "example.svg")

Parameterized Sub-image

def labeledRect(
        level: int,
        width: float,
        height: float,
        s: Union[str, TextRepresent],
        font_size: float,
        textShift: Tuple[float, float] = (0, 0),
        font: str = "Arial",
        rx: float = 0,
        ry: float = 0,
        margin: float = 5,
        attrib: Attrib = Attrib(),
        rectAttrib: Attrib = Attrib(),
        textAttrib: Attrib = Attrib(),
        **kwargs):
    e = ComposedElement((width + 2 * margin, height + 2 * margin),
                        level, attrib + kwargs)
    rect(e, 0, margin, margin, width, height, rx, ry, attrib=rectAttrib)

    textX = width / 2 + textShift[0] + margin
    textY = height / 2 + textShift[1] + (font_size / 2) + margin
    text(e, 1, s, textX, textY, font_size, font, attrib=textAttrib)
    return e

a = Axis((300,200))
a.addElement(labeledRect(...))

Nested Canvas

Canvas and Axis

Create a canvas axis with Axis(size, viewport) size=(width, height) is the physical size of the canvas in pixels. viewport=(x, y) is the logical size of the axis, by default its the same of the physical size.

# A 1600x900 canvas, axis range [0,1600)x[0,900)
a = Axis((1600, 900))

# A 1600x900 canva, with normalized axis range[0,1),[0,1)
b = Axis((1600, 900), (1.0, 1.0))

ComposedElement

A composed element is a sub-image.

ComposedElement(size, level, attrib) size=(width, height): the size of the axis of this element. level: the higher the level is, the fronter the composed element is. attrib: the common attributes of this element

Add a composed element into the big canvas:axis.addElement(element, shift) shift=(x,y) is the displacement of the element in the outer axis.

A composed element can have other composed elements as sub-pictures: element.addElement(subElement, shift)

Basic Elements

The basic element comes from SVG. Basicly, every element needs a axis and a level argument. axis can be a Axis or ComposedElement. The bigger the level is, the fronter the element is. level is only comparable when two elements are under the same axis.

# Rectangle
rect(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    x: float, # top left
    y: float,
    width: float,
    height: float,
    rx: float = 0.0, # round corner radius
    ry: float = 0.0,
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)
# Circle
circle(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    cx: float, # center
    cy: float,
    r: float, # radius
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)
# Ellipse
ellipse(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    cx: float, # center
    cy: float,
    rx: float, # radius
    ry: float,
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)
# Straight line
line(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    x1: float, # Start
    y1: float,
    x2: float, # End
    y2: float,
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)
# Polyline
polyline(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    points: List[Tuple[float, float]],
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)
# Polygon
polygon(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    points: List[Tuple[float, float]],
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)
# Path
path(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    d: PathD,
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)

PathD is a sequence of path descriptions, the actions is like SVG's path element. View Path tutorial We use ?To() for captial letters and ?For() for lower-case letters. close() and open() is for closing or opening the path. Example:

d = PathD()
d.moveTo(100,100)
d.hlineFor(90)
d.close()
# Equivilent: d = PathD(["M 80 80", "h 90",  "Z"])

path(a, 0, d)

Text

text(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    s: Union[str, TextRepresent],
    x: float,
    y: float,
    fontSize: int,
    font: str = "Arial",
    anchor: str = "middle",
    attrib: core.Attrib = core.Attrib(),
    **kwargs
)

anchor is where (x,y) is in the text. Can be either start, middle or end.

TextRepresent means formatted text. Normal string with \n in it will be converted into multilines. You can use TextSpan to add some attributes to a span of text.

Examples:

text(
    a, 10,
    "Hello\n???" + \
    TextSpan("!!!\n", fill='#00ffff', font_size=25) +\
    "???\nabcdef",
    30, 30, 20, anchor="start")

Arrow

# Straight arrow
arrow(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    x: float, # Position of the tip
    y: float,
    fromX: float, # Position of the other end
    fromY: float,
    tipSize: float = 10.0,
    tipAngle: float = 60.0,
    tipFilled: bool = True,
    **kwargs
)
# Polyline arrow
polyArrow(
    axis: Union[core.Axis, core.ComposedElement],
    level: int,
    points: List[Tuple[float, float]],
    tipSize: float = 10.0,
    tipAngle: float = 60.0,
    tipFilled: bool = True,
    **kwargs
)

Attributes

Attributes is for customizing the style of the elements.

myStyle = Attrib(
    fill = "#1bcd20",
    stroke = "black",
    stroke_width = "1pt"
)

alertStype = myStyle.copy()
alertStype.fill = "#ff0000"

rect(..., attrib=myStyle)
circle(..., attrib=alertStyle)

The name of the attribute are the same as in SVG elements, except use underline _ instead of dash -

Attributs of ComposedElement applies on <group> element.

For convinent, you can directly write some attributes in **kwargs.

rect(..., fill="red")

# Equivilient
rect(..., attrib=Attrib(fill="red))
Owner
SemiWaker
A student in Peking University Department of Electronic Engineering and Computer Science, Major in Artificial Intelligence.
SemiWaker
Codes to calculate solar-sensor zenith and azimuth angles directly from hyperspectral images collected by UAV. Works only for UAVs that have high resolution GNSS/IMU unit.

UAV Solar-Sensor Angle Calculation Table of Contents About The Project Built With Getting Started Prerequisites Installation Datasets Contributing Lic

Sourav Bhadra 1 Jan 15, 2022
End-To-End Optimization of LiDAR Beam Configuration

End-To-End Optimization of LiDAR Beam Configuration arXiv | IEEE Xplore This repository is the official implementation of the paper: End-To-End Optimi

Niclas 30 Nov 28, 2022
Pyeventbus: a publish/subscribe event bus

pyeventbus pyeventbus is a publish/subscribe event bus for Python 2.7. simplifies the communication between python classes decouples event senders and

15 Apr 21, 2022
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade

Sanghyun Son 2.1k Dec 27, 2022
Awesome Remote Sensing Toolkit based on PaddlePaddle.

基于飞桨框架开发的高性能遥感图像处理开发套件,端到端地完成从训练到部署的全流程遥感深度学习应用。 最新动态 PaddleRS 即将发布alpha版本!欢迎大家试用 简介 PaddleRS是遥感科研院所、相关高校共同基于飞桨开发的遥感处理平台,支持遥感图像分类,目标检测,图像分割,以及变化检测等常用遥

146 Dec 11, 2022
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

Vikash Sehwag 65 Dec 19, 2022
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling Transformer-based models are widely used in natural language processi

Zhanpeng Zeng 12 Jan 01, 2023
The Deep Learning with Julia book, using Flux.jl.

Deep Learning with Julia DL with Julia is a book about how to do various deep learning tasks using the Julia programming language and specifically the

Logan Kilpatrick 67 Dec 25, 2022
The MATH Dataset

Measuring Mathematical Problem Solving With the MATH Dataset This is the repository for Measuring Mathematical Problem Solving With the MATH Dataset b

Dan Hendrycks 267 Dec 26, 2022
“英特尔创新大师杯”深度学习挑战赛 赛道3:CCKS2021中文NLP地址相关性任务

基于 bert4keras 的一个baseline 不作任何 数据trick 单模 线上 最高可到 0.7891 # 基础 版 train.py 0.7769 # transformer 各层 cls concat 明神的trick https://xv44586.git

孙永松 7 Dec 28, 2021
Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"

DMT: Dynamic Mutual Training for Semi-Supervised Learning This repository contains the code for our paper DMT: Dynamic Mutual Training for Semi-Superv

Zhengyang Feng 120 Dec 30, 2022
Text2Art is an AI art generator powered with VQGAN + CLIP and CLIPDrawer models

Text2Art is an AI art generator powered with VQGAN + CLIP and CLIPDrawer models. You can easily generate all kind of art from drawing, painting, sketch, or even a specific artist style just using a t

Muhammad Fathy Rashad 643 Dec 30, 2022
This repository is for our paper Exploiting Scene Graphs for Human-Object Interaction Detection accepted by ICCV 2021.

SG2HOI This repository is for our paper Exploiting Scene Graphs for Human-Object Interaction Detection accepted by ICCV 2021. Installation Pytorch 1.7

HT 10 Dec 20, 2022
A project to build an AI voice assistant using Python . The Voice assistant interacts with the humans to perform basic tasks.

AI_Personal_Voice_Assistant_Using_Python A project to build an AI voice assistant using Python . The Voice assistant interacts with the humans to perf

Chumui Tripura 1 Oct 30, 2021
Rendering color and depth images for ShapeNet models.

Color & Depth Renderer for ShapeNet This library includes the tools for rendering multi-view color and depth images of ShapeNet models. Physically bas

Yinyu Nie 41 Dec 19, 2022
Exploring Cross-Image Pixel Contrast for Semantic Segmentation

Exploring Cross-Image Pixel Contrast for Semantic Segmentation Exploring Cross-Image Pixel Contrast for Semantic Segmentation, Wenguan Wang, Tianfei Z

Tianfei Zhou 510 Jan 02, 2023
How to train a CNN to 99% accuracy on MNIST in less than a second on a laptop

Training a NN to 99% accuracy on MNIST in 0.76 seconds A quick study on how fast you can reach 99% accuracy on MNIST with a single laptop. Our answer

Tuomas Oikarinen 42 Dec 10, 2022
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

MNE-Python MNE-Python software is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, E

MNE tools for MEG and EEG data analysis 2.1k Dec 28, 2022
The code for the CVPR 2021 paper Neural Deformation Graphs, a novel approach for globally-consistent deformation tracking and 3D reconstruction of non-rigid objects.

Neural Deformation Graphs Project Page | Paper | Video Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction Aljaž Božič, Pablo P

Aljaz Bozic 134 Dec 16, 2022
PyTorch Implementation of Vector Quantized Variational AutoEncoders.

Pytorch implementation of VQVAE. This paper combines 2 tricks: Vector Quantization (check out this amazing blog for better understanding.) Straight-Th

Vrushank Changawala 2 Oct 06, 2021