ListView例子
这是一个关于Android中实现listview 像html 中树形菜单一样,可以展开和折叠的例子
In-shop Clothes Retrieval Benchmark evaluates the performance of in-shop Clothes Retrievel. This is a large subset of DeepFashion, containing large pose and scale variations. It also has large diversities, large quantities, and rich annotations, including 7,982 number of clothing items; 52,712 number of in-shop clothes images, and ~200,000 cross-pose/scale pairs; Each image is annotated by bounding box, clothing type and pose type.
Fashion Synthesis Benchmark facilitates the studies of generating new clothing images. It includes 78,979 images selected from the In-shop Clothes Benchmark. Each image is associated with several sentences as captions and a segmentation map. If you use the images, captions, and segmentations, please appropriately cite the papers of DeepFashion and FashionGAN. The 78,979 images can be downloaded from Google Drive or Baidu Drive. The captions and segmentations for these images can be downloaded from FashionGAN. Images with high resolutions are released upon request.
Fashion Landmark Detection Benchmark evaluates the performance of fashion landmark detection. This is a large subset of DeepFashion, with diverse and large pose/zoom-in variations. It contains 123,016 number of clothes images; 8 fashion landmarks (both location and visibility) for each image; Each image is also annotated by bounding box, clothing type and variation type. More details can be found in "Fashion Landmark Detection in the Wild, ECCV 2016".
Consumer-to-shop Clothes Retrieval Benchmark evaluates the performance of consumer-to-shop Clothes Retrievel. This is a large subset of DeepFashion, containing cross-domain correspondences and variations in the wild. It contains 33,881 number of clothing items; 239,557 number of consumer/shop clothes images, and 195,540 cross-domain pairs; Each image is annotated by bounding box, clothing type and source type.
2016-08-08 The data and labels of the attribute prediction benchmark are released without encription (password). If Dropbox are not accessable, please download the dataset using Google Drive or Baidu Drive
Dataset 1: Over 4.1 million continuous ratings (-10.00 to +10.00) of 100 jokes from 73,421 users: collected between April 1999 - May 2003. Dataset 2: Over 1.7 million continuous ratings (-10.00 to +10.00) of 150 jokes from 59,132 users: collected between November 2006 - May 2009. Dataset 2+: An updated version of Dataset 2 with over 500,000 new ratings from 79,681 total users: data collected from November 2006 - Nov 2012 下载链接:http://eigentaste.berkeley.edu/dataset/