Image to SVG 2024-06-20
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By unverified author. Claim this AI
Trace pixels to vectors automatically with AI.
Generated by ChatGPT

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.


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Jun 20, 2024
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Vectorizer was manually vetted by our editorial team and was first featured on July 16th 2023.
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1 alternative to Vectorizer for Image to SVG

Pros and Cons


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
Image Types compatibility
Fully automatic operation
High Performance


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


What is Vectorizer.AI?
How does Vectorizer.AI convert JPEG and PNG bitmaps into SVG vectors?
What technology does Vectorizer.AI use to process images?
How does Vectorizer.AI assures image clarity at any resolution?
What are the output formats supported by Vectorizer.AI?
What distinguishes Vectorizer.AI from other vectorizers?
How are the AI models of Vectorizer.AI trained?
Can Vectorizer.AI clean corners and match tangents?
What input formats are supported by Vectorizer.AI?
Are any exciting new features for Vectorizer.AI expected in the future?
How does Vectorizer.AI make use of Deep Learning and Vector Conversion?
What is the role of Geometric Shapes and Image Transformation in Vectorizer.AI's functionality?
Why does Vectorizer.AI fit whole geometric shapes?
How does Vectorizer.AI execute high performance conversions?
How does Vectorizer.AI handle features less than a pixel wide?
Is Vectorizer.AI fully automatic or does it require user inputs?
Can Vectorizer.AI operate effectively on scanner images, photos of sketches, drawn artwork, and photographs?
What types of curves does Vectorizer.AI support?
What output control does Vectorizer.AI offer to its users?
Is there an option in Vectorizer.AI to pre-crop images for optimized resolution?

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