COCO data set of Dataset: Introduction and download of COCO data set
Introduction to the COCO dataset
The full name of MS COCO is Microsoft Common Objects in Context. It originated from the Microsoft COCO dataset that Microsoft funded and annotated in 2014. Like the ImageNet competition, it is regarded as one of the most watched and authoritative competitions in the computer vision field.
The COCO data set is a large and rich object detection, segmentation and captioning data set. This data set aims at scene understanding, which is mainly intercepted from complex daily scenes. The target in the image is calibrated through precise segmentation. The image includes 91 types of targets, 328,000 images and 2,500,000 labels. So far, there is the largest dataset of semantic segmentation. There are 80 categories and more than 330,000 images, of which 200,000 are labeled. The number of individuals in the entire dataset exceeds 1.5 million.
Official website address : http://cocodataset.org
0. 80 categories of COCO data set-data set used by YoloV3 algorithm
person
bicycle (bicycle) car (car) motorbike (motorcycle) aeroplane (airplane) bus (bus) train (train) truck (truck) boat (boat)
traffic light (signal light) fire hydrant (fire hydrant) stop sign (parking sign) parking meter (parking meter) bench (bench)
bird (bird) cat (cat) dog (dog) horse (horse) sheep (sheep) cow (ox) elephant (elephant) bear (熊) ) zebra(zebra) giraffe(giraffe)
backpack(backpack) umbrella(umbrella) handbag(handbag) tie(tie) suitcase(suitcase)
frisbee(frisbee) skis(snowboard feet) snowboard(snowboard) sports ball(sports ball) ) kite(kite) baseball bat(baseball bat) baseball glove(baseball glove) skateboard(skateboard) surfboard(surfboard) tennis racket(tennis racket)
bottle(bottle) wine glass(goblet) cup(tea cup) fork(fork) ) knife (knife)
spoon (spoon) bowl (bowl)
banana (banana) apple (apple) sandwich (sandwich) orange (orange) broccoli (broccoli) carrot (carrot) hot dog (hot dog) pizza (pizza) donut (sweet) Donut) cake (cake)
chair sofa (sofa) pottedplant (potted plant) bed (bed) diningtable (dining table) toilet (toilet) tvmonitor (television)
laptop (notebook) mouse (mouse) remote (remote control) keyboard (keyboard) cell phone( Phone)
microwave (microwave oven) oven (oven) toaster (toaster) sink (sink) refrigerator (refrigerator)
book (book) clock (alarm clock) vase (vase) scissors (scissors) teddy bear (teddy bear) hair drier( Hair dryer) toothbrush (toothbrush)
1. The meaning of COCO data set
The full name of MS COCO is Microsoft Common Objects in Context, which originated from the Microsoft COCO dataset that Microsoft funded and annotated in 2014. Like the ImageNet competition, it is regarded as one of the most watched and authoritative competitions in the field of computer vision.
After the ImageNet competition was discontinued, the COCO competition became the most authoritative and important benchmark in the current target recognition, detection and other fields. It is also the only one in the world that can bring together Google, Microsoft, Facebook, and many top institutions at home and abroad. A competition jointly participated by the school and outstanding innovative companies.
This data set mainly solves three problems: target detection, contextual relationship between targets, and precise positioning of targets in 2 dimensions. The COCO data set has 91 categories. Although there are fewer categories than ImageNet and SUN, there are more images in each category. This is conducive to obtaining more capabilities in a specific scene in each category. Compared with PASCAL VOC, it has more categories. And images.
1. COCO target detection challenge
- The COCO data set contains 200,000 images;
- With more than 500,000 target annotations in 80 categories, it is the most widely publicized target detection database;
- The average number of targets per image is 7.2. These are well-known datasets for target detection challenges.
2. Features of COCO data set
COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features:
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3. The size and version of the data set
Size: 25 GB (compressed)
Number of records: 330K images, 80 object categories, each image has 5 tags, and 250,000 key points.
The COCO data set is released in two parts. The first part was released in 2014, and the latter part was released in 2015. The 2014 version: 82,783 training, 40,504 validation, and 40,775 testing images, with 270k segmented people and 886k segmented objects; the 2015 version : 165,482 train, 81,208 val, and 81,434 test images.
(1) The data of the 2014 version has a total of about 20G of pictures and about 500M of label files. The label file marks the precise position of each segmentation pixel + the precise coordinates of the bounding box, and the accuracy is two decimal places.
COCO data set download
Data set download address
1. Download the 2014 data set
http://msvocds.blob.core.windows.net/coco2014/train2014.zip
2. Download the 2017 data set
http://images.cocodataset.org/zips/train2017.zip
http://images.cocodataset.org/annotations/annotations_trainval2017.zip
http://images.cocodataset.org/zips/val2017.zip
http://images.cocodataset.org/annotations/stuff_annotations_trainval2017.zip
http://images.cocodataset.org/zips/test2017.zip
http://images.cocodataset.org/annotations/image_info_test2017.zip
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