Birds dataset. eBird Basic Dataset (EBD) The EBD is the core dataset for accessing all raw eBird observations and associated metadata. The total number of categories of birds is 200 and there are 6033 images in the 2010 dataset and 11,788 images in the 2011 dataset. Refresh. 4 GB . BIRD contains over 12,751 unique question-SQL pairs, 95 big databases with a total size of 33. BIRD (BIg Bench for LaRge-scale Database Grounded Text-to-SQL Evaluation) represents a pioneering, cross-domain dataset that examines the impact of extensive database contents on text-to-SQL parsing. The Caltech-UCSD Birds-200-2011 (CUB-200-2011) dataset is the most widely-used dataset for fine-grained visual categorization task. 525 species, 84635 train, 2625 test, 2625 validation images 224X224X3 jpg. Aug 8, 2024 ยท Caltech-UCSD Birds 200 (CUB-200) is an image dataset with photos of 200 bird species (mostly North American). The dataset comprises 84,635 training images, 2,625 test images, and 2,625 validation images, with each image having dimensions of 224 x 224 x 3. This project is designed to classify 525 different bird species using deep learning techniques and a comprehensive dataset of bird images. The aim is to leverage TensorFlow and EfficientNetB7 for efficient and accurate image classification. . This repository contains a deep learning project focused on classifying 525 bird species using convolutional neural networks (CNNs). The Caltech-UCSD Birds-200-2011 (CUB-200-2011) dataset is the most widely-used dataset for fine-grained visual categorization task. The EBD is updated monthly (15th of each month), and is available by direct download through eBird to any logged-in user after completion of a data request form. It contains 11,788 images of 200 subcategories belonging to birds, 5,994 for training and 5,794 for testing. scstf malgbli bvbyc bnolxz kqxdowp jkgjl elbjml pexdr tcjjr lybx