Siddharth_Dataset Object Detection Dataset and Pre-Trained Model by siddharthWorkspace

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Explore Dataset

Here are a few use cases for this project:

Brand Identification: The "Siddharth_Dataset" can be utilized in a commercial setting for identifying specific brand logos or products present in a scene. For instance, it can identify whether a person is wearing Nike, Puma, or Adidas shoes, or if there's a Standard Chartered sign or HSBC ATM in the background. This can allow companies to conduct market research and measure brand visibility and dominance in various locations.
Sports Equipment Recognition: In sports games, the model can distinguish between different brand's equipment, such as Nike or Adidas soccer balls, Puma jerseys etc. This can be useful in sponsorship analysis and sports market research.
Advertising Monitoring: This computer vision model can help monitor or audit advertising places. For instance, ensuring if a Lavazza advertisement intended for a specific billboard was indeed put up, or if a web page contains the correct AXA banner advertisement.
Environmental Impact Studies: By analyzing images of areas suffering from pollution, the model can identify discarded products from these brands. Such data can provide important insights for environmental impact reports related to specific companies or product categories.
Content Curation Moderation: With the ability to identify various brands, the model can be used to moderate user-generated content in social media platforms. For instance, it could automatically flag content that contains inappropriate use or misrepresentation of brands such as Canon or Hewlett Packard.

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{
                            siddharth_dataset_dataset,
                            title = { Siddharth_Dataset Dataset },
                            type = { Open Source Dataset },
                            author = { siddharthWorkspace },
                            howpublished = { \url{ https://universe.roboflow.com/siddharthworkspace/siddharth_dataset } },
                            url = { https://universe.roboflow.com/siddharthworkspace/siddharth_dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-19 },
                            }