val-iisc/sketch-parse
Code, demos and data for SketchParse (a neural network for sketch segmentation). Paper:
This project helps graphic designers, illustrators, or educators automatically understand the meaning of shapes and lines within freehand sketches. It takes your freehand drawing as input and outputs a detailed breakdown of its semantic parts, like segmenting a drawing of a cup into 'handle', 'body', and 'base'. This is ideal for anyone working with digital sketches who needs to automatically categorize or process components of their drawings.
No commits in the last 6 months.
Use this if you need to automatically identify and label different semantic parts within your freehand digital sketches.
Not ideal if you are looking for a tool to enhance the aesthetic quality of your sketches or if you require fine-grained segmentation for highly complex, photorealistic drawings.
Stars
82
Forks
13
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 15, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/val-iisc/sketch-parse"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
tonybeltramelli/pix2code
pix2code: Generating Code from a Graphical User Interface Screenshot
bobbens/sketch_simplification
Models and code related to sketch simplification of rough sketches.
emilwallner/Screenshot-to-code
A neural network that transforms a design mock-up into a static website.
MiteshPuthran/Image-Caption-Generator
The LSTM model generates captions for the input images after extracting features from...
jchenghu/ExpansionNet_v2
Implementation code of the work "Exploiting Multiple Sequence Lengths in Fast End to End...