ImageNet1k

ImageNet1k is a subset of the larger ImageNet dataset, specifically curated for use in image classification benchmarks. It contains approximately 1.28 million training images, 50,000 validation images, and 100,000 test images. These images are divided into 1,000 distinct object categories. The development of ImageNet1k was a significant event in the field of computer vision, largely due to its role in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a competition that spurred rapid advancements in deep learning models for image recognition. The dataset's scale and diversity have made it a de facto standard for evaluating and comparing the performance of various image classification algorithms, particularly convolutional neural networks (CNNs). Researchers worldwide have used ImageNet1k to train and test models, leading to breakthroughs in areas such as object detection and image segmentation. The availability of such a large, labeled dataset was crucial for the success of deep learning in computer vision.