Introduction to COCO Dataset
The coco data set download needs to go over the wall
COCO - Common Objects in Context
key index
Take instances_val2017.json as an example, some blogs say there is a key index type, but I can't find it
info/licenses
There is nothing to say about these two goods, data information and copyright, I don’t need it personally
images
There is a list in images, one of which is taken out separately is as follows
{"license": 4,"file_name": "000000397133.jpg","coco_url": "http://images.cocodataset.org/val2017/000000397133.jpg","height": 427,"width": 640,"date_captured": "2013-11-14 17:02:52","flickr_url": "http://farm7.staticflickr.com/6116/6255196340_da26cf2c9e_z.jpg","id": 397133}
The information that needs attention is
Image name: "file_name": "000000397133.jpg"
The location of the image in the network: "coco_url": " http://images.cocodataset.org/val2017/000000397133.jpg "
Image height: "height": 427
Image width: "width": 640
Image ID: "id": 397133
annotations
There is also a list in annotations, which is taken out separately as follows
{"segmentation": [[510.66,423.01,511.72,420.03,510.45......]],"area": 702.1057499999998,"iscrowd": 0,"image_id": 289343,"bbox": [473.07,395.93,38.65,28.67],"category_id": 18,"id": 1768}
Semantic segmentation: "segmentation": [[510.66, 423.01, 511.72, 420.03, 510.45......] This is the point around the target circle
Area area: "area": 702.1057499999998 ? ? This location needs to be confirmed, it should be the area of the target
Is it a crowd: "iscrowd": 0
Image ID: "image_id": 289343 This corresponds to the id in images
Detection box: "bbox":[473.07,395.93,38.65,28.67] upper left point xy+wh
Category ID: "category_id": 18 The first category in the dataset, the default category 0 is background
Label ID: "id": 1768 is the number of the label. This id is not corresponding to the id in the picture, but the number of the label in the entire data set.
categories
It's also a list, and there's nothing to say about this
{"supercategory": "animal","id": 18,"name": "dog"}
Category parent class: "supercategory": "animal" I haven't used it much, but it's pretty good. For example, if I want to classify animals, people, and cars, I can use this parent class
Category id: "id": 18 The id of the dog category in the category list, corresponding to the above "category_id"
Category name: "name": "dog"
class_name = [ '__background__', 'person', 'bicycle', 'car', 'motorcycle', 'airplane','bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush']
self._valid_ids = [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 70, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 88, 89, 90]
The original data set ID is not continuous, I don't know why
Data introduction
COCO category
index:0 id:1 name:person supercategory:person index:1 id:2 name:bicycle supercategory:vehicle index:2 id:3 name:car supercategory:vehicle index:3 id:4 name:motorcycle supercategory:vehicle index:4 id:5 name:airplane supercategory:vehicle index:5 id:6 name:bus supercategory:vehicle index:6 id:7 name:train supercategory:vehicle index:7 id:8 name:truck supercategory:vehicle index:8 id:9 name:boat supercategory:vehicle index:9 id:10 name:traffic light supercategory:outdoor index:10 id:11 name:fire hydrant supercategory:outdoor index:11 id:13 name:stop sign supercategory:outdoor index:12 id:14 name:parking meter supercategory:outdoor index:13 id:15 name:bench supercategory:outdoor index:14 id:16 name:bird supercategory:animal index:15 id:17 name:cat supercategory:animal index:16 id:18 name:dog supercategory:animal index:17 id:19 name:horse supercategory:animal index:18 id:20 name:sheep supercategory:animal index:19 id:21 name:cow supercategory:animal index:20 id:22 name:elephant supercategory:animal index:21 id:23 name:bear supercategory:animal index:22 id:24 name:zebra supercategory:animal index:23 id:25 name:giraffe supercategory:animal index:24 id:27 name:backpack supercategory:accessory index:25 id:28 name:umbrella supercategory:accessory index:26 id:31 name:handbag supercategory:accessory index:27 id:32 name:tie supercategory:accessory index:28 id:33 name:suitcase supercategory:accessory index:29 id:34 name:frisbee supercategory:sports index:30 id:35 name:skis supercategory:sports index:31 id:36 name:snowboard supercategory:sports index:32 id:37 name:sports ball supercategory:sports index:33 id:38 name:kite supercategory:sports index:34 id:39 name:baseball bat supercategory:sports index:35 id:40 name:baseball glove supercategory:sports index:36 id:41 name:skateboard supercategory:sports index:37 id:42 name:surfboard supercategory:sports index:38 id:43 name:tennis racket supercategory:sports index:39 id:44 name:bottle supercategory:kitchen index:40 id:46 name:wine glass supercategory:kitchen index:41 id:47 name:cup supercategory:kitchen index:42 id:48 name:fork supercategory:kitchen index:43 id:49 name:knife supercategory:kitchen index:44 id:50 name:spoon supercategory:kitchen index:45 id:51 name:bowl supercategory:kitchen index:46 id:52 name:banana supercategory:food index:47 id:53 name:apple supercategory:food index:48 id:54 name:sandwich supercategory:food index:49 id:55 name:orange supercategory:food index:50 id:56 name:broccoli supercategory:food index:51 id:57 name:carrot supercategory:food index:52 id:58 name:hot dog supercategory:food index:53 id:59 name:pizza supercategory:food index:54 id:60 name:donut supercategory:food index:55 id:61 name:cake supercategory:food index:56 id:62 name:chair supercategory:furniture index:57 id:63 name:couch supercategory:furniture index:58 id:64 name:potted plant supercategory:furniture index:59 id:65 name:bed supercategory:furniture index:60 id:67 name:dining table supercategory:furniture index:61 id:70 name:toilet supercategory:furniture index:62 id:72 name:tv supercategory:electronic index:63 id:73 name:laptop supercategory:electronic index:64 id:74 name:mouse supercategory:electronic index:65 id:75 name:remote supercategory:electronic index:66 id:76 name:keyboard supercategory:electronic index:67 id:77 name:cell phone supercategory:electronic index:68 id:78 name:microwave supercategory:appliance index:69 id:79 name:oven supercategory:appliance index:70 id:80 name:toaster supercategory:appliance index:71 id:81 name:sink supercategory:appliance index:72 id:82 name:refrigerator supercategory:appliance index:73 id:84 name:book supercategory:indoor index:74 id:85 name:clock supercategory:indoor index:75 id:86 name:vase supercategory:indoor index:76 id:87 name:scissors supercategory:indoor index:77 id:88 name:teddy bear supercategory:indoor index:78 id:89 name:hair drier supercategory:indoor index:79 id:90 name:toothbrush supercategory:indoor