WOOD Object Detection Dataset and Pre-Trained Model by srm

Images

818 images

Explore Dataset

Here are a few use cases for this project:

Lumber Quality Control: Industries involved in the production of wooden materials can utilize the "WOOD" model to assist in identifying defects in lumber before it reaches the consumer. This aids in maintaining high standards of quality control.
Furniture Manufacturing: Furniture manufacturers can leverage "WOOD" for inspecting the quality and condition of wood used for production, leading to higher-quality products and less wastage due to defected wood.
Forestry Management: Forestry departments and organizations can employ the "WOOD" model for assessing the health of trees within their jurisdiction. Detecting damages, shakes, or stains on trees can be paramount for early pest detection or disease prevention.
Home Inspection Services: Home inspectors can utilize the "WOOD" model to identify any potential wood defects during their inspections. This could be particularly beneficial for assessing the condition of wooden structures, foundations or pieces such as floors, walls, and furniture.
Wood Artwork Authentication: Art historians or auction houses might use the "WOOD" model to analyze wooden art pieces. Identifying specific defects could help to verify the authenticity of a piece or understand its age and preservation state.

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{
                            wood-gihub_dataset,
                            title = { WOOD Dataset },
                            type = { Open Source Dataset },
                            author = { srm },
                            howpublished = { \url{ https://universe.roboflow.com/srm-kcu7c/wood-gihub } },
                            url = { https://universe.roboflow.com/srm-kcu7c/wood-gihub },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-28 },
                            }