Pictures classification Object Detection Dataset and Pre-Trained Model by Project

Images

1927 images

Explore Dataset

Here are a few use cases for this project:

Photo Sorting Application: An application that can utilize the model to sort users' vast photo galleries into different classes such as professional pictures, indoor or outdoor pictures, pictures with faces or without, etc.
Social Media Content Moderation: This model can be used to automate moderation and content categorization on social media platforms, identifying professional or non-professional pictures, or photos containing faces with or without glasses, smiles, etc.
Digital Advertising: Advertisers can use the model to classify and understand the content of images on web pages or social media to better tailor and position their ads. For example, identifying if the picture is professional or not, if it includes faces or smiles might help in highly targeted advertising.
Augmented Reality Applications: AR applications can benefit from this model by better understanding the type of the surroundings (indoor, outdoor), presence of individuals, and specifics like glasses or scarfs for more precise digital information placement or object interaction.
Vision Assistance for Visually Impaired: Visual aids can use this model to describe the surroundings to visually impaired people. By identifying faces, smiles, glasses, whether they are indoors or outdoors, it can provide a more detailed and descriptive picture of their environment.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            pictures-classification_dataset,
                            title = { Pictures classification Dataset },
                            type = { Open Source Dataset },
                            author = { Project },
                            howpublished = { \url{ https://universe.roboflow.com/project-vkjtv/pictures-classification } },
                            url = { https://universe.roboflow.com/project-vkjtv/pictures-classification },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { may },
                            note = { visited on 2024-05-04 },
                            }