Datasets
A versatile collection of high-quality datasets designed to support a wide range of machine learning development tasks, from training and validation to benchmarking across various domains and methods.
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Subject area: Manufacturing
Description: This dataset is collected to train a YOLO model to detect and count different types of packages such as plastic bottles, glass bottles, cans, tubes, jars and cartons in a production line.
Dataset: Link
Purpose: Detect and count packages in a production line.
Resolution: Multi resolutions
No. Classes: 6(plastic bottles, glass bottles, cans, tubes, jars, cartons)
Samples: Train: 9086 samples (801 images), Validation: 445 samples (118 images)
Subject area: Food Industry
Description: This dataset contains high resolution images of white and brown eggs. Egg labels and their locations in each image is provided in text files. The images and their labels are provided in YOLO format that can be used easily for training segmentation and classification models.
Dataset: Link
Purpose: Can be used for developing egg segmentation, classification, and detection models. Moreover, sizes of eggs can be estimated properly which can be used in sorting lines.
Resolution: 3024x4032
No. Classes: 2(white/brown eggs)
Samples: Train:393 egg samples (50 images), Validation: 30 egg samples (2 images)
Subject area: Food Industry
Description: This dataset contains high resolution images of white and brown eggs. Egg labels and their locations in each image is provided in text files. The images and their labels are provided in YOLO format that can be easily used for training detection and classification models.
Dataset: Link
Purpose: Can be used for developing egg detector, classification, and counter models.
Resolution: 3024x4032
No. Classes: 2(white/brown eggs)
Samples: Train:393 egg samples (50 images), Validation: 30 egg samples (2 images)
