Shape_detect_on Computer Vision Project

Shapecolorlive

Updated 2 years ago

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Classes (38)
Blue_Arrow
Blue_Circle
Blue_Cross
Blue_Hexagon
Blue_Moon
Blue_Octagon
Blue_Square
Blue_Star
Blue_Triangle
Green_Arrow
Green_Circle
Green_Cross
Green_Hexagon
Green_Moon
Green_Octagon
Green_Square
Green_Star
Green_Triangle
Red_Arrow
Red_Circle
Red_Cross
Red_Hexagon
Red_Moon
Red_Octagon
Red_Square
Red_Star
Red_Triangle
Rwd_Square
White_Arrow
White_Box
White_Circle
White_Cross
White_Hexagon
White_Moon
White_Octagon
White_Square
White_Star
White_Triangle
Description

Here are a few use cases for this project:

  1. Traffic Sign Recognition: Utilize the Shape_detect_on model to identify and classify various traffic signs used in road safety and traffic control, such as different types of arrows, crosses, and shapes with colored backgrounds.

  2. Educational Tools: Develop interactive games and learning applications for children, where they can correctly identify and match shapes and colors to improve their cognitive and motor skills.

  3. Industrial Quality Control: Implement the Shape_detect_on model in a manufacturing line to identify and sort parts and products based on their shape and color, ensuring that only the correct items move forward in the production process.

  4. Art and Design Applications: Use the model to assist graphic designers and artists in distinguishing and categorizing various geometrical shapes and colors in design elements, streamlining their creative process.

  5. Environmental Monitoring: Apply the Shape_detect_on model to monitor and analyze aerial or satellite imagery for features and patterns of interest (e.g., identifying colored shapes on rooftops, signs, or landmarks) for urban planning, disaster response, or environmental research.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            shape_detect_on_dataset,
                            title = { Shape_detect_on Dataset },
                            type = { Open Source Dataset },
                            author = { Shapecolorlive },
                            howpublished = { \url{ https://universe.roboflow.com/shapecolorlive/shape_detect_on } },
                            url = { https://universe.roboflow.com/shapecolorlive/shape_detect_on },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-11-29 },
                            }
                        
                    

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336 images 2 models