JPG images with annotation text files

The Extended Moulouya Bird Detection Dataset (E-Moulouya BDD) is a comprehensive collection of annotated images proposed for bird detection. The dataset is a combination of three datasets, namely the XMBA dataset, the Rest Birds Dataset, and the D-Birds Dataset, which were merged and cleaned up to provide a consistent and unified labeling format. The E-Moulouya BDD comprises 13,000 annotated images, labeled with a standardized format to ensure consistency across the dataset. The dataset is publicly available on IEEE DATAPORT, making it an ideal resource for use by the scientific community.

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Ear biting is a welfare challenge in commercial pig farming. Pigs sustain injuries at the site of bite paving the way for bacterial infections. Early detection and management of this behaviour is important to enhance animal health and welfare, increase productivity whilst minimising inputs from medication. Pig management using physical observation is not practical due to the scale of modern pig production systems. The same applies to the manual analysis of captured videos from pig houses. Therefore, a method of automated detection is desirable.

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This is the collection of Indian Traffic Sign Detection Dataset. This can be used maily on Traffic Sign detection projects using YOLO. Dataset is in YOLO format. There are 1264 total images in this dataset fully annotated using Labelimg tool. Some augmented datas using techniques like blurring, mosaic etc.. are also present. The dataset has images in 3 different types of traffic signs in India. Dataset is annotated only as one class-Traffic Sign.

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This is the collection of Indian Traffic Sign Detection Dataset. This can be used maily on Traffic Sign detection projects using YOLO. Dataset is in YOLO format. There are 1264 total images in this dataset fully annotated using Labelimg tool. Some augmented datas using techniques like blurring, mosaic etc.. are also present. The dataset has images in 3 different types of traffic signs in India. Dataset is annotated only as one class-Traffic Sign.

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