Doors Image Dataset | Indoor Object Detection

Indoor scene object detection, Augmented Reality, Scene detection

About Dataset

**This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai **

This dataset is an extremely challenging set of over 3,000+ images of excavator vehicles from multiple construction site. These images captured and crowdsourced from over 2000+ different locations, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs. It contains a wide variety of indoor door images. This dataset can be used scene classification and domestic object detection.

Dataset Features

1. Dataset size : 3000+ images
2. Captured by : Over 2000+ crowdsource contributors
3. Resolution : HD and above (1920x1080 and above)
4. Location : Captured with 2000+ locations
5. Diversity : Various lighting conditions like day, night, varied distances, view points etc.
6. Device used : Captured using mobile phones in 2020-2022
7. Usage : Image classification, domestic object detection, objects relationship understanding etc.

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

                        @misc{
                            doors-image-dataset_dataset,
                            title = { Doors Image Dataset  Dataset },
                            type = { Open Source Dataset },
                            author = { DataCluster Labs },
                            howpublished = { \url{ https://universe.roboflow.com/datacluster-labs-agryi/doors-image-dataset } },
                            url = { https://universe.roboflow.com/datacluster-labs-agryi/doors-image-dataset },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-12-22 },
                            }