Vectorizer.AI is a tool designed to facilitate the smooth conversion of pixel-based (raster) PNG and JPG images into scalable vector graphics (SVGs) fully automatically. Built on a foundation of deep learning and classical algorithms, this tool analyzes, processes, and transforms your image from a grid of pixels to geometrical shapes. These resulting vector images can be expanded to any resolution without losing quality, allowing for a wider range of applications, including printing, cutting, embroidering and more.A core feature of Vectorizer.AI is its deep vector engine that employs artificial intelligence networks to create thorough and precise vector conversions. It also utilizes a unique computational geometry framework, the Vector Graph, which enables automated edits and localized optimizations that are challenging to achieve with conventional vector image representations. Rather than limiting its functioning to simple Bezier curves, it fits complex geometric shapes where applicable to provide an ideal fit and unmatched consistency. It supports various types of curves and uses them as needed, providing results that are more natural than those from other vectorizers. High performance is ensured through the full utilization of state-of-the-art GPUs for deep learning, and efficient, parallel classical algorithms conducted on multi-core CPUs.Vectorizer.AI takes care of features that are less than a pixel wide and places boundaries according to the anti-aliasing pixel values. Fully automatic, it doesnt require user input to produce results, working effectively on scanner images, photos of sketches, drawn artwork, and photographs. It also supports full 32-bit color, including the alpha channel, and allows for a wide range of export options, including SVG, PDF, EPS, DXF, and PNG formats.
Pros And Cons Of Vectorizer
Pros
Converts JPEG
PNG to SVG
Uses multi-core CPUs
Uses powerful GPUs
Analyzed images retain clarity
Images can be upscaled
Good for printing
cutting
embroidering
Preview before download
Multiple download formats: SVG
PDF
EPS
DXF
PNG
Accurate detail capture
Handles ambiguous pixel data
Possible to fit geometric shapes
Clean corner output
Tangent matching
Curve fairing
Supports numerous input formats: JPEG
PNG
WEBP
BMP
GIF
Continual tool development
Pixel to vector automatic conversion
Deep learning based
Classical algorithms integration
Sub-pixel precision
Handles different curve types
Less than pixel wide features
Works on scanner images
drawn artwork
photos
Full 32-bit color supported
Full Color & Transparency
Supports ARGB input
Various export choices
Maximum image pixel size of 3 megapixels
Maximum image file size of 30 megabytes
Image cropping supported
Resolution maximization
Pre-cropping
Image Types compatibility
Fully automatic operation
High Performance
Cons
Limited to 3 megapixels
Only works on images
Limited file size
Use for machine learning prohibited
Data retention only 24 hours
Not always fully automatic
Pre-cropping needed for large images
Possible compatibility issues
Pricing Of Vectorizer
from $9.99/mo
FQA From Vectorizer
What is Vectorizer.AI?
Vectorizer.AI is an AI-driven tool purposed for converting JPEG and PNG bitmaps into scalable vector graphics (SVGs). The tool uses high-end GPUs and multi-core CPUs to analyze and process images, transforming them from pixel-based to geometric shapes. The resultant vector images maintain perfect clarity, even when scaled to any resolution, making the tool perfect for uses such as printing, cutting and embroidering. Also, Vectorizer.AI enables users to preview results and download vectorized images in numerous formats—including SVG, PDF, EPS, DXF, and PNG.
How does Vectorizer.AI convert JPEG and PNG bitmaps into SVG vectors?
Vectorizer.AI deploys deep learning and classical algorithms to convert JPEG and PNG bitmaps into SVG vectors. During the conversion process, the tool thoroughly analyzes, processes, and transforms the bitmap image from a grid of pixels to geometrical shapes. The deep vector engine of Vectorizer.AI uses specific AI networks to create precise and thorough vector conversions. Thus converting even the pixel details of an image into precise geometric shapes.
What technology does Vectorizer.AI use to process images?
Vectorizer.AI utilizes several powerful technologies in processing images. Primarily, it uses an artificial intelligence network for precise vector conversions, known as the deep vector engine. Additionally, Vectorizer.AI employs a unique computational geometry framework, the Vector Graph, that allows for automated edits and localized optimizations. The tool maximizes the power of high-end GPUs for deep learning and applies efficient, parallel classical algorithms run on multi-core CPUs ensuring high performance.
How does Vectorizer.AI assures image clarity at any resolution?
Vectorizer.AI ensures image clarity at any resolution by converting pixel-based images into geometric shapes. Since geometric shapes can be mathematically scaled without losing any detail, the resultant vector images can be enlarged or minimized to any resolution without loss of quality. This distinctive image representation means that vectorized graphics can provide a high level of detail irrespective of the scale.
What are the output formats supported by Vectorizer.AI?
Vectorizer.AI supports a wide variety of output formats. Users can download their vectorized images in formats such as SVG, PDF, EPS, DXF, and PNG. Having multiple output formats provides users with the flexibility to choose the format that best suits their requirements.
What distinguishes Vectorizer.AI from other vectorizers?
Vectorizer.AI distinguishes itself from other vectorizers through its AI technology. The AI element helps in accurately capturing minute details and producing sensible interpretations when pixel data is ambiguous. Additionally, unlike other tools that limit their function to simple Bezier curves, Vectorizer.AI fits complex geometric shapes, providing an ideal fit and unparalleled consistency. The tool also supports different curve types, resulting in more natural results compared to other vectorizers.
How are the AI models of Vectorizer.AI trained?
Vectorizer.AI's AI models have been developed in-house and have been trained using a proprietary dataset. This training tends to be recurrent, allowing the model to learn and improve its accuracy in capturing details and making intelligent interpretations when faced with ambiguous pixel data.
Can Vectorizer.AI clean corners and match tangents?
Vectorizer.AI does indeed house the functionality for cleaning up corners and matching tangents. This process is part of Vectorizer.AI’s raster-to-vector conversion methodology, leading to cleaner outputs and improved image consistency compared to conventional vectorizers.
What input formats are supported by Vectorizer.AI?
Vectorizer.AI supports a variety of input formats. Presently, users can input files in formats including JPEG, PNG, WEBP, BMP, and GIF. This multiplicity of format accommodations helps in broadening the reach of the tool, making it usable to a large pool of users regardless of their required format.
Are any exciting new features for Vectorizer.AI expected in the future?
Vectorizer.AI is under active development with plans to introduce more exciting features in the future. However, detailed specifics about what these future features could be are not provided on their website.
How does Vectorizer.AI make use of Deep Learning and Vector Conversion?
Vectorizer.AI intensely leverages Deep Learning and Vector Conversion in its process. Deep Learning techniques are used to train artificial intelligence networks, effectively allowing the tool to identify and convert distinct pixelated details into vector shapes. A unique feature, the Vector Graph, allows automated edits and localized optimization, which brings about high-quality vector conversions (Vector Conversion).
What is the role of Geometric Shapes and Image Transformation in Vectorizer.AI's functionality?
Geometric Shapes and Image Transformation are core elements in Vectorizer.AI’s functionality. In the conversion process, the tool transforms a bitmap image from a grid of pixels to geometrical shapes. These serve as the building blocks of the resultant vectorized image. The transformation from pixel representations to geometric shapes means that the quality of the image won't degrade, even when the resolution changes.
Why does Vectorizer.AI fit whole geometric shapes?
Vectorizer.AI makes a decision to fit whole geometric shapes as a part of the process towards producing high-quality vector conversion results. Unlike other vectorizers that only utilize simple Bezier curves, Vectorizer.AI fits complex geometric shapes to provide an ideal fit and unmatched consistency. This full shape fitting leads to more accurate, naturally flowing vector images.
How does Vectorizer.AI execute high performance conversions?
Vectorizer.AI ensures high-performance conversions by leveraging the power of cutting-edge GPUs for deep learning and running efficient, parallel classical algorithms on multi-core CPUs. This approach allows Vectorizer.AI to deliver high-quality vector conversions at a much faster pace than traditional methods.
How does Vectorizer.AI handle features less than a pixel wide?
Vectorizer.AI employs Sub-Pixel Precision technology in handling features less than a pixel wide. This means it can trace out details that are less than a pixel wide and place boundaries according to the anti-aliasing pixel values, ensuring that even the tiniest details are not lost in the conversion process.
Is Vectorizer.AI fully automatic or does it require user inputs?
Vectorizer.AI is fully automated and doesn't require any user input to deliver its results. It is designed to be capable of effectively processing various types of images, including scanner images, photos of sketches, drawn artwork, and photographs, without requiring user intervention.
Can Vectorizer.AI operate effectively on scanner images, photos of sketches, drawn artwork, and photographs?
Vectorizer.AI can indeed operate effectively on scanner images, photos of sketches, drawn artwork, and photographs. It is designed to work well on a variety of image types, not limited to logos and other rasterized vector art. Its algorithm manages to convert these different types of images into precise vector representations, all without requiring user input.
What types of curves does Vectorizer.AI support?
Vectorizer.AI supports a wide range of curve types as part of the vectorization process. Apart from simple straight lines, it accommodates circular arcs, elliptical arcs, and quadratic and cubic Bezier curves. Most other vector graphic software applications try to simplify things to contain only cubic Bezier curves, which is a limited approximation. But Vectorizer.AI employs a comprehensive range of curve types to provide more natural and accurate results.
What output control does Vectorizer.AI offer to its users?
Vectorizer.AI offers a range of export options to its users. Users can download their vectorized images in formats including SVG, PDF, EPS, DXF, and PNG. Plus, users have the ability to control how shapes are drawn, how they are grouped, and a number of other format-specific options. This offers users more control over the output of the vectorized images.
Is there an option in Vectorizer.AI to pre-crop images for optimized resolution?
Vectorizer.AI does offer an option to pre-crop images. Pre-cropping is used to maximize the quality of the resultant vectorized image by allowing you to crop the portion of your photo that you wish to convert to a vector. By cutting out the portion of the bitmap to vectorize, only the cropped area counts against the resolution limit imposed by the tool.
