c++读取图片_四、faster-rcnn源码阅读：数据流读取
数据读取在faster-rcnn源码里是比较简单的部分，但也是非常重要的部分，不了解数据，就不可能了解算法。
另一方面，由于python环境碎片话化，源码调用的库在你的电脑上如果碰巧（其实概率还蛮大，特别是windows下）不能用，完全可以用另外一种等价的方式取代。
一、图片读取就是把图片转化成矩阵，等待下一个流程进一步处理。图片读取要注意不是所有都是RGB顺序读取
1.cv2（OpenCV-Python ）：BGR顺序
img = cv2.imread(image_path)
h, w, c = image.shape
img = cv2.resize(img, (self.img_width, self.img_height))
img = img[:,:,::-1]#bgr转rgb2.PIL（Pillow）：
from PIL import Image
img = Image.open(img_path).convert('RGB')
img = Image.fromarray(img)3.skimage（scikit-image）：
from skimage import io
img=io.imread(image_path)
from skimage import transform
img = transform.resize(img, (C, H * scale, W * scale), mode='reflect',anti_aliasing=False)4.scipy.misc
import scipy.misc
#或scipy.ndimage.imread
img = scipy.misc.imread(image_path)5.matplotlib
import matplotlib.image as mpimg
img = mpimg.imread(image_path)前两种方式用得很多，后几种方式用的很少。
这些库很多，但万剑归功，读取基本都是调用PIL或libjpeg，详情看
Python的各种imread函数在实现方式和读取速度上有何区别？www.zhihu.com大致结论是：读取PIL最快，resize的话CV2最快。
二、标签读取
1.import xml.etree.ElementTree as ET
这个读取xml是标配
三、pascal_voc数据集
1.在/VOCdevkit/VOC2007/下有五个文件夹，faster-rcnn会用到其中三个：
（1）ImageSets：划分(split)数据，txt文件存文件名（不带后缀），划分得比较多，也比较细，有不同用途，faster-rcnn只要其中的 'ImageSets/Main/{0}.txt'.format(split)即可，这里split in ['train', 'test', 'val']或其他别的也可以。
每个txt文件每行一个文件名，一般一个文件几千行，对应几千个文件。
（2）JPEGImages：存放图片，文件名+.jpg即可。
（3）Annotations：存放标签，文件名+.xml即可。
xml格式为：
VOC2007
000001.jpg
The VOC2007 Database
PASCAL VOC2007
flickr
341012865
Fried Camels
Jinky the Fruit Bat
353
500
3
0
只要关注object部分：size、name和bndbox即可，其他部分不用太关心。
四、pytorch的dataset
这篇文章讲得很清楚：
Elijha：Pytorch数据读取(Dataset, DataLoader, DataLoaderIter)zhuanlan.zhihu.com
概括起来：
torch.utils.data.Dataset：
最基本的读取，负责表示数据集，两个方法__getitem__()和__len__()
torch.utils.data.DataLoader：
在Dataset之上+batch+多线程+数据处理
torch.utils.data.dataloader.DataLoaderIter：
DataLoader之上+迭代
五、部分源码
来自：facebookresearch/maskrcnn-benchmark
继承自最基础的torch.utils.data.Dataset
Dataset可以交给DataLoader，封装batchs和多线程
class PascalVOCDataset(torch.utils.data.Dataset):
第一个是背景，其他是目标类别
CLASSES = (
"__background__ ",
"aeroplane",
"bicycle",
"bird",
"boat",
"bottle",
"bus",
"car",
"cat",
"chair",
"cow",
"diningtable",
"dog",
"horse",
"motorbike",
"person",
"pottedplant",
"sheep",
"sofa",
"train",
"tvmonitor",
)
def __init__(self, data_dir, split, use_difficult=False, transforms=None):
数据根目录
self.root = data_dir
指定用哪个数据，test、val、train？
self.image_set = split
要不要难以识别的图片？
self.keep_difficult = use_difficult
图片处理
self.transforms = transforms
对应三个文件加：
self._annopath = os.path.join(self.root, "Annotations", "%s.xml")
self._imgpath = os.path.join(self.root, "JPEGImages", "%s.jpg")
直接用Main文件夹
self._imgsetpath = os.path.join(self.root, "ImageSets", "Main", "%s.txt")
初始化的时候就把文件名全读出来
with open(self._imgsetpath % self.image_set) as f:
self.ids = f.readlines()
self.ids = [x.strip("n") for x in self.ids]
构造id到图片的字典，
self.id_to_img_map = {k: v for k, v in enumerate(self.ids)}
cls = PascalVOCDataset.CLASSES
类别到序号和序号到类别的两个字典
self.class_to_ind = dict(zip(cls, range(len(cls))))
self.categories = dict(zip(range(len(cls)), cls))
__getitem__是必须的
def __getitem__(self, index):
img_id = self.ids[index]
根据id号读取图片，用的是PIL来读
img = Image.open(self._imgpath % img_id).convert("RGB")
获取目标框，裁剪
target = self.get_groundtruth(index)
target = target.clip_to_image(remove_empty=True)
做归一化，缩放等处理
if self.transforms is not None:
img, target = self.transforms(img, target)
target 前四个表示坐标，第五个值表示类别
return img, target, index
__len__也是必须的
def __len__(self):
return len(self.ids)
def get_groundtruth(self, index):
img_id = self.ids[index]
定位到根节点
anno = ET.parse(self._annopath % img_id).getroot()
读取图片大小、目标类别、目标位置信息
anno = self._preprocess_annotation(anno)
取出高宽信息
height, width = anno["im_info"]
按xyxy顺序的坐标信息，这个地方要注意，并不是每个实现都是相同顺序，还是看读取的时候怎么读的，有的是yxyx顺序
BoxList是自定义的处理这几个不目标框的类
target = BoxList(anno["boxes"], (width, height), mode="xyxy")
BoxList添加标签，难度
target.add_field("labels", anno["labels"])
target.add_field("difficult", anno["difficult"])
return target
def _preprocess_annotation(self, target):
boxes = []
gt_classes = []
difficult_boxes = []
TO_REMOVE = 1
只遍历object节点
for obj in target.iter("object"):
遇到难以识别的，跳过也行，不是强烈要求，就跳过吧
difficult = int(obj.find("difficult").text) == 1
if not self.keep_difficult and difficult:
continue
标签名称
name = obj.find("name").text.lower().strip()
矩形坐标
bb = obj.find("bndbox")
# Make pixel indexes 0-based
# Refer to "https://github.com/rbgirshick/py-faster-rcnn/blob/master/lib/datasets/pascal_voc.py#L208-L211"
box = [
bb.find("xmin").text,
bb.find("ymin").text,
bb.find("xmax").text,
bb.find("ymax").text,
]
两次map：
第一次是把文本转化成int，这里int是函数；
第二次是把int减去1，0-based
得到一个tuple
bndbox = tuple(
map(lambda x: x - TO_REMOVE, list(map(int, box)))
)
把这tuple添加进boxes
boxes.append(bndbox)
把标签转化成类别id
gt_classes.append(self.class_to_ind[name])
difficult_boxes.append(difficult)
循环结束，一张图片目标有一个或多个，但大小只有一个
看图片大小
size = target.find("size")
把高宽从文本转化成int，得到一个tuple
im_info = tuple(map(int, (size.find("height").text, size.find("width").text)))
把这张图片的信息用一个字典返回
并把坐标转化成float
res = {
"boxes": torch.tensor(boxes, dtype=torch.float32),
"labels": torch.tensor(gt_classes),
"difficult": torch.tensor(difficult_boxes),
"im_info": im_info,
}
return res六、coco数据集
coco跟voc差不太多，但是标签不同，voc是单独的xml，而coco是一个json，种类更多，层次更多，数据信息也更多，大致像这样：
{
"info": {
"description": "COCO 2014 Dataset",
"url": "http://cocodataset.org",
"version": "1.0",
"year": 2014,
"contributor": "COCO Consortium",
"date_created": "2017/09/01"
},
"licenses": [{
"url": "http://creativecommons.org/licenses/by-nc-sa/2.0/",
"id": 1,
"name": "Attribution-NonCommercial-ShareAlike License"
}, {
"url": "http://creativecommons.org/licenses/by-nc/2.0/",
"id": 2,
"name": "Attribution-NonCommercial License"
}, {
"url": "http://creativecommons.org/licenses/by-nc-nd/2.0/",
"id": 3,
"name": "Attribution-NonCommercial-NoDerivs License"
}, {
"url": "http://creativecommons.org/licenses/by/2.0/",
"id": 4,
"name": "Attribution License"
}, {
"url": "http://creativecommons.org/licenses/by-sa/2.0/",
"id": 5,
"name": "Attribution-ShareAlike License"
}, {
"url": "http://creativecommons.org/licenses/by-nd/2.0/",
"id": 6,
"name": "Attribution-NoDerivs License"
}, {
"url": "http://flickr.com/commons/usage/",
"id": 7,
"name": "No known copyright restrictions"
}, {
"url": "http://www.usa.gov/copyright.shtml",
"id": 8,
"name": "United States Government Work"
}],
"categories": [{
"supercategory": "person",
"id": 1,
"name": "person"
}, {
"supercategory": "vehicle",
"id": 2,
"name": "bicycle"
}, {
"supercategory": "vehicle",
"id": 3,
"name": "car"
}, {
"supercategory": "vehicle",
"id": 4,
"name": "motorcycle"
}, {
"supercategory": "vehicle",
"id": 5,
"name": "airplane"
}, {
"supercategory": "vehicle",
"id": 6,
"name": "bus"
}, {
"supercategory": "vehicle",
"id": 7,
"name": "train"
}, {
"supercategory": "vehicle",
"id": 8,
"name": "truck"
}, {
"supercategory": "vehicle",
"id": 9,
"name": "boat"
}, {
"supercategory": "outdoor",
"id": 10,
"name": "traffic light"
}, {
"supercategory": "outdoor",
"id": 11,
"name": "fire hydrant"
}, {
"supercategory": "outdoor",
"id": 13,
"name": "stop sign"
}, {
"supercategory": "outdoor",
"id": 14,
"name": "parking meter"
}, {
"supercategory": "outdoor",
"id": 15,
"name": "bench"
}, {
"supercategory": "animal",
"id": 16,
"name": "bird"
}, {
"supercategory": "animal",
"id": 17,
"name": "cat"
}, {
"supercategory": "animal",
"id": 18,
"name": "dog"
}, {
"supercategory": "animal",
"id": 19,
"name": "horse"
}, {
"supercategory": "animal",
"id": 20,
"name": "sheep"
}, {
"supercategory": "animal",
"id": 21,
"name": "cow"
}, {
"supercategory": "animal",
"id": 22,
"name": "elephant"
}, {
"supercategory": "animal",
"id": 23,
"name": "bear"
}, {
"supercategory": "animal",
"id": 24,
"name": "zebra"
}, {
"supercategory": "animal",
"id": 25,
"name": "giraffe"
}, {
"supercategory": "accessory",
"id": 27,
"name": "backpack"
}, {
"supercategory": "accessory",
"id": 28,
"name": "umbrella"
}, {
"supercategory": "accessory",
"id": 31,
"name": "handbag"
}, {
"supercategory": "accessory",
"id": 32,
"name": "tie"
}, {
"supercategory": "accessory",
"id": 33,
"name": "suitcase"
}, {
"supercategory": "sports",
"id": 34,
"name": "frisbee"
}, {
"supercategory": "sports",
"id": 35,
"name": "skis"
}, {
"supercategory": "sports",
"id": 36,
"name": "snowboard"
}, {
"supercategory": "sports",
"id": 37,
"name": "sports ball"
}, {
"supercategory": "sports",
"id": 38,
"name": "kite"
}, {
"supercategory": "sports",
"id": 39,
"name": "baseball bat"
}, {
"supercategory": "sports",
"id": 40,
"name": "baseball glove"
}, {
"supercategory": "sports",
"id": 41,
"name": "skateboard"
}, {
"supercategory": "sports",
"id": 42,
"name": "surfboard"
}, {
"supercategory": "sports",
"id": 43,
"name": "tennis racket"
}, {
"supercategory": "kitchen",
"id": 44,
"name": "bottle"
}, {
"supercategory": "kitchen",
"id": 46,
"name": "wine glass"
}, {
"supercategory": "kitchen",
"id": 47,
"name": "cup"
}, {
"supercategory": "kitchen",
"id": 48,
"name": "fork"
}, {
"supercategory": "kitchen",
"id": 49,
"name": "knife"
}, {
"supercategory": "kitchen",
"id": 50,
"name": "spoon"
}, {
"supercategory": "kitchen",
"id": 51,
"name": "bowl"
}, {
"supercategory": "food",
"id": 52,
"name": "banana"
}, {
"supercategory": "food",
"id": 53,
"name": "apple"
}, {
"supercategory": "food",
"id": 54,
"name": "sandwich"
}, {
"supercategory": "food",
"id": 55,
"name": "orange"
}, {
"supercategory": "food",
"id": 56,
"name": "broccoli"
}, {
"supercategory": "food",
"id": 57,
"name": "carrot"
}, {
"supercategory": "food",
"id": 58,
"name": "hot dog"
}, {
"supercategory": "food",
"id": 59,
"name": "pizza"
}, {
"supercategory": "food",
"id": 60,
"name": "donut"
}, {
"supercategory": "food",
"id": 61,
"name": "cake"
}, {
"supercategory": "furniture",
"id": 62,
"name": "chair"
}, {
"supercategory": "furniture",
"id": 63,
"name": "couch"
}, {
"supercategory": "furniture",
"id": 64,
"name": "potted plant"
}, {
"supercategory": "furniture",
"id": 65,
"name": "bed"
}, {
"supercategory": "furniture",
"id": 67,
"name": "dining table"
}, {
"supercategory": "furniture",
"id": 70,
"name": "toilet"
}, {
"supercategory": "electronic",
"id": 72,
"name": "tv"
}, {
"supercategory": "electronic",
"id": 73,
"name": "laptop"
}, {
"supercategory": "electronic",
"id": 74,
"name": "mouse"
}, {
"supercategory": "electronic",
"id": 75,
"name": "remote"
}, {
"supercategory": "electronic",
"id": 76,
"name": "keyboard"
}, {
"supercategory": "electronic",
"id": 77,
"name": "cell phone"
}, {
"supercategory": "appliance",
"id": 78,
"name": "microwave"
}, {
"supercategory": "appliance",
"id": 79,
"name": "oven"
}, {
"supercategory": "appliance",
"id": 80,
"name": "toaster"
}, {
"supercategory": "appliance",
"id": 81,
"name": "sink"
}, {
"supercategory": "appliance",
"id": 82,
"name": "refrigerator"
}, {
"supercategory": "indoor",
"id": 84,
"name": "book"
}, {
"supercategory": "indoor",
"id": 85,
"name": "clock"
}, {
"supercategory": "indoor",
"id": 86,
"name": "vase"
}, {
"supercategory": "indoor",
"id": 87,
"name": "scissors"
}, {
"supercategory": "indoor",
"id": 88,
"name": "teddy bear"
}, {
"supercategory": "indoor",
"id": 89,
"name": "hair drier"
}, {
"supercategory": "indoor",
"id": 90,
"name": "toothbrush"
}],
"images": [{
"license": 1,
"file_name": "COCO_val2014_000000581062.jpg",
"coco_url": "http://images.cocodataset.org/val2014/COCO_val2014_000000581062.jpg",
"height": 375,
"width": 500,
"date_captured": "2013-11-20 09:12:04",
"flickr_url": "http://farm4.staticflickr.com/3582/3328164554_6765a03a6a_z.jpg",
"id": 581062
}, {
"license": 5,
"file_name": "COCO_val2014_000000581317.jpg",
"coco_url": "http://images.cocodataset.org/val2014/COCO_val2014_000000581317.jpg",
"height": 354,
"width": 640,
"date_captured": "2013-11-24 07:57:55",
"flickr_url": "http://farm1.staticflickr.com/14/19721466_b561e5955f_z.jpg",
"id": 581317
}, {
"license": 2,
"file_name": "COCO_val2014_000000000139.jpg",
"coco_url": "http://images.cocodataset.org/val2014/COCO_val2014_000000000139.jpg",
"height": 426,
"width": 640,
"date_captured": "2013-11-21 01:34:01",
"flickr_url": "http://farm9.staticflickr.com/8035/8024364858_9c41dc1666_z.jpg",
"id": 139
}, {
"license": 3,
"file_name": "COCO_val2014_000000000632.jpg",
"coco_url": "http://images.cocodataset.org/val2014/COCO_val2014_000000000632.jpg",
"height": 483,
"width": 640,
"date_captured": "2013-11-20 21:14:01",
"flickr_url": "http://farm2.staticflickr.com/1241/1243324748_eea455da9f_z.jpg",
"id": 632
}],
"annotations": [{
"segmentation": [
[134.12, 155.64, 136.9, 139.37, 135.31, 121.52, 133.33, 100.09, 139.68, 82.63, 131.74, 76.67, 132.93, 73.5, 149.2, 67.55, 147.61, 59.21, 154.76, 51.28, 163.88, 52.86, 167.06, 69.93, 181.34, 73.1, 194.44, 73.9, 194.44, 77.86, 183.72, 77.86, 162.3, 76.67, 157.14, 98.9, 165.07, 120.72, 162.69, 138.18, 164.28, 147.31, 171.42, 162.79, 163.49, 162.39, 154.36, 153.66, 158.33, 128.26, 148.41, 115.96, 146.03, 129.45, 142.45, 153.26, 140.87, 164.77, 133.33, 162.39]
],
"area": 2470.656449999998,
"iscrowd": 0,
"image_id": 581062,
"bbox": [131.74, 51.28, 62.7, 113.49],
"category_id": 1,
"id": 469201
}, {
"segmentation": [
[129.18, 160.51, 132.46, 159.07, 134.92, 163.17, 139.63, 163.58, 142.09, 158.25, 158.69, 155.18, 163.2, 159.07, 164.63, 161.53, 169.55, 160.3, 167.71, 154.57, 175.7, 152.72, 178.57, 153.34, 178.77, 157.23, 170.78, 162.15, 170.78, 166.04, 164.43, 165.84, 163.81, 164.4, 146.19, 166.66, 144.96, 169.73, 141.07, 169.93, 138.61, 167.89, 128.77, 162.15]
],
"area": 364.30039999999985,
"iscrowd": 0,
"image_id": 581062,
"bbox": [128.77, 152.72, 50.0, 17.21],
"category_id": 41,
"id": 638773
}, {
"segmentation": [
[240.86, 211.31, 240.16, 197.19, 236.98, 192.26, 237.34, 187.67, 245.8, 188.02, 243.33, 176.02, 250.39, 186.96, 251.8, 166.85, 255.33, 142.51, 253.21, 190.49, 261.68, 183.08, 258.86, 191.2, 260.98, 206.37, 254.63, 199.66, 252.51, 201.78, 251.8, 212.01]
],
"area": 531.8071000000001,
"iscrowd": 0,
"image_id": 139,
"bbox": [236.98, 142.51, 24.7, 69.5],
"category_id": 64,
"id": 26547
}, {
"segmentation": [
[9.66, 167.76, 156.35, 173.04, 153.71, 256.48, 82.56, 262.63, 7.03, 260.87]
],
"area": 13244.657700000002,
"iscrowd": 0,
"image_id": 139,
"bbox": [7.03, 167.76, 149.32, 94.87],
"category_id": 72,
"id": 34646
}, {
"segmentation": [
[563.33, 209.19, 637.69, 209.19, 638.56, 287.92, 557.21, 280.04]
],
"area": 5833.117949999999,
"iscrowd": 0,
"image_id": 139,
"bbox": [557.21, 209.19, 81.35, 78.73],
"category_id": 72,
"id": 35802
}, {
"segmentation": [
[368.16, 252.94, 383.77, 255.69, 384.69, 235.49, 389.28, 226.31, 392.03, 219.89, 413.15, 218.05, 411.31, 241.92, 411.31, 256.61, 412.23, 274.05, 414.98, 301.6, 414.98, 316.29, 412.23, 311.7, 406.72, 290.58, 405.8, 270.38, 389.28, 270.38, 381.01, 270.38, 383.77, 319.04, 377.34, 320.88, 377.34, 273.14, 358.98, 266.71, 358.98, 253.86, 370.91, 253.86]
],
"area": 2245.34355,
"iscrowd": 0,
"image_id": 139,
"bbox": [358.98, 218.05, 56.0, 102.83],
"category_id": 62,
"id": 103487
}, {
"segmentation": [
[319.32, 230.98, 317.41, 220.68, 296.03, 218.0, 296.03, 230.22, 297.18, 244.34, 296.03, 258.08, 299.47, 262.28, 296.03, 262.28, 298.32, 266.48, 295.27, 278.69, 291.45, 300.45, 290.69, 310.76, 292.21, 309.23, 294.89, 291.67, 298.32, 274.11, 300.61, 266.1, 323.9, 268.77, 328.09, 272.59, 326.57, 297.02, 323.9, 315.34, 327.71, 316.48, 329.62, 297.78, 329.62, 269.53, 341.84, 266.48, 345.27, 266.1, 350.23, 265.72, 343.74, 312.28, 346.8, 310.76, 351.76, 273.35, 352.52, 264.95, 350.23, 257.32, 326.19, 255.79, 323.51, 254.27, 321.61, 244.72, 320.46, 235.56, 320.08, 231.36]
],
"area": 1833.7840000000017,
"iscrowd": 0,
"image_id": 139,
"bbox": [290.69, 218.0, 61.83, 98.48],
"category_id": 62,
"id": 104368
}, {
"segmentation": [
[436.06, 304.37, 443.37, 300.71, 436.97, 261.4, 439.71, 245.86, 437.88, 223.92, 415.94, 223.01, 413.2, 244.95, 415.03, 258.66, 416.86, 268.72, 415.03, 289.74, 419.6, 280.6, 423.26, 263.23, 434.23, 265.98]
],
"area": 1289.3734500000014,
"iscrowd": 0,
"image_id": 139,
"bbox": [413.2, 223.01, 30.17, 81.36],
"category_id": 62,
"id": 105328
}, {
"segmentation": [
[317.4, 219.24, 319.8, 230.83, 338.98, 230.03, 338.58, 222.44, 338.58, 221.24, 336.58, 219.64, 328.19, 220.44]
],
"area": 210.14820000000023,
"iscrowd": 0,
"image_id": 139,
"bbox": [317.4, 219.24, 21.58, 11.59],
"category_id": 62,
"id": 110334
}, {
"segmentation": [
[428.19, 219.47, 430.94, 209.57, 430.39, 210.12, 421.32, 216.17, 412.8, 217.27, 413.9, 214.24, 422.42, 211.22, 429.29, 201.6, 430.67, 181.8, 430.12, 175.2, 427.09, 168.06, 426.27, 164.21, 430.94, 159.26, 440.29, 157.61, 446.06, 163.93, 448.53, 168.06, 448.53, 173.01, 449.08, 174.93, 454.03, 185.1, 455.41, 188.4, 458.43, 195.0, 460.08, 210.94, 462.28, 226.61, 460.91, 233.76, 454.31, 234.04, 460.08, 256.85, 462.56, 268.13, 465.58, 290.67, 465.85, 293.14, 463.38, 295.62, 452.66, 295.34, 448.26, 294.52, 443.59, 282.7, 446.06, 235.14, 446.34, 230.19, 438.09, 232.39, 438.09, 221.67, 434.24, 221.12, 427.09, 219.74]
],
"area": 2913.1103999999987,
"iscrowd": 0,
"image_id": 139,
"bbox": [412.8, 157.61, 53.05, 138.01],
"category_id": 1,
"id": 230831
}, {
"segmentation": [
[384.98, 206.58, 384.43, 199.98, 385.25, 193.66, 385.25, 190.08, 387.18, 185.13, 387.18, 182.93, 386.08, 181.01, 385.25, 178.81, 385.25, 175.79, 388.0, 172.76, 394.88, 172.21, 398.72, 173.31, 399.27, 176.06, 399.55, 183.48, 397.9, 185.68, 395.15, 188.98, 396.8, 193.38, 398.45, 194.48, 399.0, 205.75, 395.43, 207.95, 388.83, 206.03]
],
"area": 435.1449499999997,
"iscrowd": 0,
"image_id": 139,
"bbox": [384.43, 172.21, 15.12, 35.74],
"category_id": 1,
"id": 233201
}, {
"segmentation": [
[5.45, 269.03, 25.08, 273.39, 44.7, 289.75, 287.84, 318.09, 346.71, 321.36, 368.52, 333.36, 404.5, 419.49, 385.96, 468.55, 385.96, 475.1, 8.72, 471.82, 3.27, 266.85]
],
"area": 64019.87940000001,
"iscrowd": 0,
"image_id": 632,
"bbox": [3.27, 266.85, 401.23, 208.25],
"category_id": 65,
"id": 315724
}, {
"segmentation": [
[216.05, 228.68, 223.38, 228.95, 227.18, 227.46, 230.98, 218.91, 230.71, 212.94, 231.11, 207.78, 232.34, 206.43, 230.71, 204.26, 227.86, 203.71, 224.47, 204.53, 220.53, 204.26, 220.8, 202.49, 224.47, 201.54, 227.04, 201.95, 226.91, 198.97, 222.57, 196.79, 229.21, 195.98, 237.76, 195.44, 241.29, 193.0, 241.97, 190.28, 244.14, 187.98, 243.05, 185.26, 235.73, 182.28, 230.3, 182.28, 227.99, 183.09, 225.69, 183.77, 227.86, 178.21, 227.99, 165.05, 222.43, 162.6, 221.35, 158.94, 216.6, 151.89, 216.05, 150.26, 220.8, 151.21, 222.84, 152.97, 223.52, 149.04, 219.58, 147.14, 214.15, 147.41, 213.07, 142.39, 207.24, 136.69, 205.2, 136.56, 205.06, 139.13, 208.32, 144.15, 210.9, 148.09, 212.26, 149.31, 207.91, 150.53, 205.06, 153.24, 202.89, 157.18, 201.94, 160.3, 201.94, 162.47, 203.57, 165.73, 204.25, 166.13, 205.74, 165.73, 206.15, 167.49, 205.06, 169.25, 203.71, 171.69, 202.89, 174.14, 203.84, 175.63, 205.61, 176.17, 206.01, 177.66, 206.42, 186.62, 203.71, 182.55, 198.82, 183.36, 197.47, 183.91, 196.25, 179.97, 190.55, 179.84, 183.36, 185.53, 183.36, 191.1, 185.26, 195.03, 187.16, 196.12, 189.6, 196.52, 190.95, 197.2, 189.33, 201.95, 189.73, 208.87, 190.82, 210.9, 195.16, 212.4, 197.87, 212.8, 199.77, 212.53, 201.94, 211.99, 200.72, 208.19, 203.57, 208.06, 203.98, 211.31, 206.42, 214.43, 207.91, 217.96, 208.86, 223.12, 210.22, 226.78, 210.76, 227.73, 213.48, 227.86]
],
"area": 2464.9330500000005,
"iscrowd": 0,
"image_id": 632,
"bbox": [183.36, 136.56, 60.78, 92.39],
"category_id": 64,
"id": 1610466
}, {
"segmentation": [
[513.6, 205.75, 526.04, 206.52, 526.96, 208.82, 526.96, 221.72, 512.22, 221.72, 513.6, 205.9]
],
"area": 217.71919999999997,
"iscrowd": 0,
"image_id": 139,
"bbox": [512.22, 205.75, 14.74, 15.97],
"category_id": 78,
"id": 1640282
}, {
"segmentation": [
[493.1, 282.65, 493.73, 174.34, 498.72, 174.34, 504.34, 175.27, 508.09, 176.21, 511.83, 178.08, 513.39, 179.33, 513.08, 280.46, 500.28, 281.09, 494.35, 281.71]
],
"area": 2089.9747999999986,
"iscrowd": 0,
"image_id": 139,
"bbox": [493.1, 174.34, 20.29, 108.31],
"category_id": 82,
"id": 1647285
}, {
"segmentation": [
[611.35, 349.51, 604.77, 305.89, 613.14, 307.99, 619.11, 351.6]
],
"area": 338.60884999999973,
"iscrowd": 0,
"image_id": 139,
"bbox": [604.77, 305.89, 14.34, 45.71],
"category_id": 84,
"id": 1648594
}, {
"segmentation": [
[613.24, 308.24, 620.68, 308.79, 626.12, 354.68, 618.86, 352.32]
],
"area": 322.5935999999982,
"iscrowd": 0,
"image_id": 139,
"bbox": [613.24, 308.24, 12.88, 46.44],
"category_id": 84,
"id": 1654394
}, {
"segmentation": [
[457.3, 224.79, 455.98, 192.5, 464.55, 196.46, 461.25, 228.09]
],
"area": 203.6632999999997,
"iscrowd": 0,
"image_id": 632,
"bbox": [455.98, 192.5, 8.57, 35.59],
"category_id": 84,
"id": 1657298
}, {
"segmentation": [
[454.75, 252.97, 453.31, 286.9, 459.48, 286.7, 461.33, 253.38]
],
"area": 214.5320999999999,
"iscrowd": 0,
"image_id": 632,
"bbox": [453.31, 252.97, 8.02, 33.93],
"category_id": 84,
"id": 1660743
}, {
"segmentation": [
[444.76, 337.31, 446.01, 297.94, 450.08, 297.63, 449.76, 337.31]
],
"area": 179.1241999999999,
"iscrowd": 0,
"image_id": 632,
"bbox": [444.76, 297.63, 5.32, 39.68],
"category_id": 84,
"id": 1660854
}, {
"segmentation": [
[513.12, 226.56, 509.69, 196.01, 505.95, 193.21, 506.57, 191.02, 514.99, 193.83, 518.1, 227.8, 515.3, 227.18]
],
"area": 189.13310000000044,
"iscrowd": 0,
"image_id": 632,
"bbox": [505.95, 191.02, 12.15, 36.78],
"category_id": 84,
"id": 1660921
}, {
"segmentation": [
[494.99, 227.38, 491.56, 227.07, 487.51, 201.82, 490.94, 199.33, 494.37, 225.2]
],
"area": 91.54300000000008,
"iscrowd": 0,
"image_id": 632,
"bbox": [487.51, 199.33, 7.48, 28.05],
"category_id": 84,
"id": 1661908
}, {
"segmentation": [
[454.29, 121.35, 448.71, 125.07, 447.77, 136.25, 451.5, 140.9, 455.92, 143.0, 461.04, 138.34, 461.74, 128.33, 456.39, 121.12]
],
"area": 225.6642000000005,
"iscrowd": 0,
"image_id": 139,
"bbox": [447.77, 121.12, 13.97, 21.88],
"category_id": 85,
"id": 1666628
}, {
"segmentation": [
[553.14, 392.76, 551.33, 370.57, 549.06, 360.15, 571.7, 314.42, 574.42, 309.43, 585.74, 316.23, 579.4, 323.93, 578.04, 331.17, 577.59, 334.34, 578.95, 342.49, 581.21, 351.55, 585.29, 370.57, 584.83, 389.13, 580.31, 399.1, 563.55, 399.1, 554.95, 394.57]
],
"area": 2171.6188500000007,
"iscrowd": 0,
"image_id": 139,
"bbox": [549.06, 309.43, 36.68, 89.67],
"category_id": 86,
"id": 1667817
}, {
"segmentation": [
[361.37, 229.69, 361.56, 226.09, 360.42, 220.02, 359.29, 213.39, 358.72, 208.84, 353.41, 209.22, 353.22, 211.31, 353.41, 216.23, 352.65, 220.21, 350.76, 228.55, 351.71, 231.39, 360.8, 231.39, 362.13, 228.74]
],
"area": 178.18510000000012,
"iscrowd": 0,
"image_id": 139,
"bbox": [350.76, 208.84, 11.37, 22.55],
"category_id": 86,
"id": 1669970
}, {
"segmentation": [
[413.7, 220.47, 412.25, 231.06, 419.96, 231.54, 421.88, 219.02]
],
"area": 90.98724999999988,
"iscrowd": 0,
"image_id": 139,
"bbox": [412.25, 219.02, 9.63, 12.52],
"category_id": 62,
"id": 1941808
}, {
"segmentation": [
[250.96, 309.48, 251.24, 301.66, 251.52, 283.79, 247.33, 282.67, 244.82, 277.64, 248.45, 273.73, 252.36, 275.97, 260.18, 267.59, 263.81, 262.84, 269.39, 274.85, 270.51, 282.39, 273.86, 279.04, 276.93, 250.0, 276.65, 236.31, 275.81, 230.45, 304.02, 234.36, 329.71, 236.31, 327.48, 251.11, 325.52, 274.01, 325.52, 281.55, 329.99, 281.83, 333.06, 281.55, 342.28, 271.78, 348.7, 269.54, 349.54, 280.71, 346.75, 291.05, 347.86, 299.7, 347.03, 313.11, 345.91, 318.14, 334.74, 317.86, 330.55, 316.18, 331.11, 310.88, 331.67, 307.52, 331.11, 304.73, 328.31, 302.22, 271.9, 299.7, 271.07, 312.27]
],
"area": 5184.222599999999,
"iscrowd": 0,
"image_id": 632,
"bbox": [244.82, 230.45, 104.72, 87.69],
"category_id": 62,
"id": 1947237
}, {
"segmentation": [
[363.21, 320.43, 370.05, 332.32, 380.5, 351.05, 381.94, 355.37, 401.76, 353.21, 408.96, 350.33, 409.68, 346.37, 408.24, 344.21, 410.76, 335.92, 414.01, 318.27, 414.37, 310.34, 417.25, 308.9, 424.09, 309.26, 429.86, 292.22, 425.53, 274.93, 425.89, 254.75, 427.34, 232.18, 428.06, 218.13, 426.25, 215.61, 421.57, 225.7, 421.93, 212.37, 417.97, 212.73, 417.25, 218.49, 413.28, 217.77, 404.64, 218.49, 405.36, 222.46, 408.6, 224.98, 408.96, 228.94, 402.12, 232.55, 399.95, 237.23, 397.79, 241.55, 394.55, 243.71, 386.62, 248.4, 383.02, 249.48, 381.58, 247.32, 374.01, 246.96, 369.33, 250.92, 369.33, 251.64, 364.65, 245.51, 359.96, 247.32, 358.16, 250.56, 356.0, 254.52, 350.96, 255.6, 348.44, 259.57, 356.72, 263.53, 359.6, 266.77, 359.6, 270.37, 354.92, 271.09, 347.35, 272.18, 350.6, 275.06, 348.08, 282.98, 356.72, 287.67, 358.88, 290.55, 357.08, 300.38, 358.16, 307.59, 360.68, 312.27, 361.41, 319.47]
],
"area": 7034.62185,
"iscrowd": 0,
"image_id": 632,
"bbox": [347.35, 212.37, 82.51, 143.0],
"category_id": 64,
"id": 1952354
}, {
"segmentation": [
[462.16, 191.67, 488.37, 192.45, 488.68, 198.54, 488.06, 200.41, 490.24, 216.16, 490.24, 226.62, 462.01, 227.71, 463.72, 196.98, 461.38, 197.13, 460.91, 194.48]
],
"area": 936.6684500000003,
"iscrowd": 0,
"image_id": 632,
"bbox": [460.91, 191.67, 29.33, 36.04],
"category_id": 84,
"id": 1987085
}, {
"segmentation": [
[549.33, 248.57, 527.02, 288.31, 529.11, 289.0, 534.69, 289.0, 551.42, 254.14]
],
"area": 245.04669999999973,
"iscrowd": 0,
"image_id": 632,
"bbox": [527.02, 248.57, 24.4, 40.43],
"category_id": 84,
"id": 1988858
}, {
"segmentation": [
[520.64, 226.21, 519.39, 193.43, 522.21, 193.59, 523.47, 227.62]
],
"area": 93.38395000000153,
"iscrowd": 0,
"image_id": 632,
"bbox": [519.39, 193.43, 4.08, 34.19],
"category_id": 84,
"id": 1988994
}, {
"segmentation": [
[497.73, 55.43, 497.39, 82.79, 501.47, 82.62, 501.47, 55.43]
],
"area": 106.6308000000007,
"iscrowd": 0,
"image_id": 632,
"bbox": [497.39, 55.43, 4.08, 27.36],
"category_id": 84,
"id": 1989419
}, {
"segmentation": [
[524.32, 100.04, 524.99, 124.6, 525.25, 131.41, 525.12, 133.68, 525.79, 135.15, 526.85, 135.15, 527.12, 119.67, 527.12, 114.33, 527.12, 111.39, 526.85, 97.38, 524.45, 97.38]
],
"area": 84.2943499999996,
"iscrowd": 0,
"image_id": 632,
"bbox": [524.32, 97.38, 2.8, 37.77],
"category_id": 84,
"id": 1989610
}, {
"segmentation": [
[493.97, 156.41, 525.95, 155.72, 525.95, 161.73, 493.36, 162.08]
],
"area": 188.38580000000024,
"iscrowd": 0,
"image_id": 632,
"bbox": [493.36, 155.72, 32.59, 6.36],
"category_id": 84,
"id": 1990447
}, {
"segmentation": [
[501.65, 257.41, 503.21, 255.06, 454.66, 245.27, 455.06, 247.62]
],
"area": 117.46770000000046,
"iscrowd": 0,
"image_id": 632,
"bbox": [454.66, 245.27, 48.55, 12.14],
"category_id": 84,
"id": 1990614
}, {
"segmentation": [
[464.39, 254.8, 461.77, 286.99, 466.26, 286.99, 470.01, 253.68]
],
"area": 163.7676500000002,
"iscrowd": 0,
"image_id": 632,
"bbox": [461.77, 253.68, 8.24, 33.31],
"category_id": 84,
"id": 2143156
}, {
"segmentation": [
[242.95, 212.06, 241.24, 199.54, 254.32, 194.99, 255.46, 200.68, 253.18, 212.62]
],
"area": 189.56010000000012,
"iscrowd": 0,
"image_id": 139,
"bbox": [241.24, 194.99, 14.22, 17.63],
"category_id": 86,
"id": 2146194
}, {
"segmentation": [
[339.52, 201.72, 336.79, 216.23, 346.35, 214.69, 346.52, 199.5]
],
"area": 120.23200000000004,
"iscrowd": 0,
"image_id": 139,
"bbox": [336.79, 199.5, 9.73, 16.73],
"category_id": 86,
"id": 2146548
}, {
"segmentation": [
[321.21, 231.22, 387.48, 232.09, 385.95, 244.95, 362.85, 245.6, 361.32, 266.53, 361.98, 310.12, 362.41, 319.5, 353.47, 320.15, 350.2, 318.41, 350.86, 277.65, 350.64, 272.63, 351.29, 246.69, 322.96, 245.17],
[411.46, 232.31, 418.87, 231.22, 415.82, 248.87, 409.93, 248.87],
[436.96, 232.31, 446.77, 232.09, 446.77, 235.79, 446.12, 266.53, 445.46, 303.15, 441.54, 302.93, 440.23, 296.17, 438.92, 289.85, 438.92, 244.95, 436.09, 244.29]
],
"area": 2362.4897499999984,
"iscrowd": 0,
"image_id": 139,
"bbox": [321.21, 231.22, 125.56, 88.93],
"category_id": 67,
"id": 2204286
}, {
"segmentation": [
[413.66, 163.89, 406.82, 147.7, 407.96, 143.37, 410.93, 142.23, 414.12, 142.92, 418.22, 149.3, 423.69, 161.15, 421.87, 162.52, 425.97, 165.71, 427.11, 170.04, 428.25, 172.78, 428.02, 175.97, 424.6, 178.48, 420.73, 178.48, 420.04, 177.11, 424.15, 175.97, 424.83, 172.78, 423.92, 171.64, 417.99, 170.73, 417.76, 167.53, 415.71, 165.03]
],
"area": 311.7617500000001,
"iscrowd": 0,
"image_id": 581317,
"bbox": [406.82, 142.23, 21.43, 36.25],
"category_id": 77,
"id": 327762
}, {
"segmentation": [
[604.26, 279.15, 601.26, 288.45, 585.51, 297.91, 576.96, 302.41, 577.41, 315.61, 577.41, 321.46, 588.66, 336.02, 588.06, 338.57, 583.11, 345.62, 585.96, 354.0, 450.96, 354.0, 453.67, 343.82, 461.02, 325.67, 466.72, 317.71, 469.12, 310.81, 473.77, 299.26, 477.67, 295.81, 482.02, 280.2, 483.98, 275.55, 484.88, 271.95, 486.68, 257.09, 483.67, 259.2, 480.52, 259.2, 472.42, 250.34, 459.67, 237.14, 454.12, 227.99, 449.01, 221.08, 441.06, 208.48, 435.36, 199.33, 429.06, 195.73, 421.26, 191.07, 417.2, 187.17, 416.45, 183.72, 417.2, 179.82, 414.5, 177.57, 411.65, 175.32, 412.7, 173.52, 413.45, 171.72, 410.75, 168.87, 409.85, 163.92, 412.1, 163.17, 415.1, 162.72, 418.41, 164.67, 418.86, 167.97, 417.8, 170.07, 424.26, 171.12, 425.61, 173.82, 423.36, 176.67, 426.81, 177.12, 427.86, 176.82, 427.56, 170.82, 426.36, 170.07, 426.06, 166.62, 423.36, 164.67, 421.86, 163.32, 421.86, 161.22, 427.41, 162.42, 433.41, 161.67, 438.36, 168.42, 443.76, 177.72, 446.46, 183.27, 446.76, 187.02, 453.37, 193.78, 462.37, 206.53, 473.17, 217.48, 478.57, 219.28, 482.17, 222.28, 483.67, 223.18, 485.63, 218.08, 487.13, 214.63, 487.13, 211.18, 489.83, 204.43, 499.43, 185.67, 505.43, 176.37, 507.08, 173.37, 506.75, 169.22, 507.05, 161.71, 510.05, 159.01, 513.35, 157.66, 516.96, 157.36, 520.56, 152.41, 524.01, 150.31, 525.06, 149.86, 528.66, 150.76, 529.56, 151.06, 528.66, 149.71, 525.21, 148.96, 521.76, 148.51, 519.06, 148.36, 516.06, 147.61, 514.85, 145.51, 514.1, 142.96, 514.55, 138.31, 513.05, 136.06, 512.15, 136.36, 510.8, 135.31, 512.9, 134.11, 512.0, 131.7, 508.1, 131.7, 506.45, 129.75, 507.05, 126.3, 505.55, 124.8, 500.6, 124.95, 499.25, 123.3, 499.55, 120.0, 502.55, 112.95, 504.05, 109.5, 503.15, 105.6, 502.55, 99.14, 504.35, 85.19, 500.9, 84.29, 499.4, 82.19, 502.85, 78.14, 505.55, 77.24, 507.95, 73.49, 515.0, 67.18, 525.81, 61.63, 536.16, 58.03, 546.21, 55.93, 556.42, 57.13, 568.57, 64.63, 576.37, 71.69, 583.13, 79.49, 585.53, 82.64, 587.33, 83.54, 588.38, 85.19, 588.68, 87.44, 590.78, 88.34, 591.38, 88.64, 591.08, 92.84, 587.03, 95.69, 587.93, 96.74, 590.33, 97.19, 591.38, 103.95, 592.13, 106.05, 594.83, 106.2, 595.43, 107.7, 597.83, 106.95, 599.03, 105.3, 601.58, 105.6, 602.93, 106.8, 603.98, 107.85, 606.53, 107.4, 608.93, 108.45, 609.83, 109.65, 610.88, 111.75, 608.48, 114.0, 605.03, 114.9, 603.23, 115.5, 602.48, 117.15, 604.43, 121.95, 603.68, 127.2, 605.03, 133.96, 604.43, 141.16, 600.98, 142.06, 597.08, 143.26, 593.48, 143.56, 594.68, 147.16, 595.88, 152.26, 597.53, 155.86, 598.13, 160.36, 598.43, 162.91, 604.43, 170.42, 607.43, 176.42, 610.28, 185.27, 613.28, 192.47, 612.38, 199.53, 611.18, 207.78, 608.48, 237.19, 606.23, 263.14, 606.23, 267.8]
],
"area": 33684.522999999994,
"iscrowd": 0,
"image_id": 581317,
"bbox": [409.85, 55.93, 203.43, 298.07],
"category_id": 1,
"id": 460897
}, {
"segmentation": {
"counts": [201255, 6, 328, 6, 142, 8, 326, 8, 140, 10, 324, 10, 138, 12, 322, 12, 137, 12, 321, 13, 137, 12, 321, 13, 137, 12, 321, 13, 137, 12, 320, 14, 18, 6, 113, 12, 320, 14, 17, 8, 112, 13, 299, 8, 12, 14, 16, 10, 111, 14, 297, 10, 11, 14, 15, 12, 81, 6, 6, 6, 11, 15, 295, 12, 4, 20, 15, 12, 80, 8, 4, 8, 11, 14, 293, 15, 2, 21, 15, 12, 79, 10, 2, 10, 1, 23, 292, 16, 1, 22, 6, 6, 3, 12, 78, 47, 291, 40, 5, 8, 2, 12, 1, 9, 12, 7, 49, 47, 290, 41, 4, 34, 10, 9, 48, 47, 289, 42, 3, 36, 8, 11, 47, 46, 289, 43, 3, 37, 6, 13, 46, 46, 288, 43, 4, 37, 6, 13, 46, 47, 287, 44, 3, 37, 6, 13, 46, 47, 287, 44, 3, 37, 6, 13, 46, 47, 287, 44, 3, 37, 6, 13, 47, 46, 287, 44, 3, 37, 6, 13, 48, 45, 287, 43, 4, 37, 6, 14, 47, 45, 287, 42, 5, 37, 7, 13, 46, 46, 288, 41, 6, 36, 8, 12, 45, 48, 287, 41, 6, 36, 8, 12, 45, 48, 287, 41, 6, 36, 8, 13, 44, 48, 288, 40, 6, 36, 7, 14, 43, 39, 8, 2, 288, 40, 7, 35, 6, 15, 42, 9, 39, 2, 287, 41, 8, 35, 4, 16, 42, 8, 40, 2, 287, 41, 9, 34, 4, 16, 42, 8, 40, 3, 286, 41, 9, 34, 4, 16, 42, 8, 40, 4, 285, 41, 9, 34, 4, 16, 42, 8, 10, 34, 285, 41, 9, 34, 4, 16, 42, 52, 285, 41, 9, 34, 4, 17, 41, 52, 285, 40, 10, 34, 4, 18, 40, 52, 285, 40, 10, 33, 5, 19, 39, 52, 285, 40, 10, 32, 6, 14, 2, 4, 38, 52, 285, 40, 11, 29, 8, 14, 2, 4, 39, 51, 285, 40, 34, 3, 11, 14, 3, 3, 40, 50, 286, 38, 49, 14, 3, 3, 40, 50, 287, 37, 49, 15, 2, 3, 40, 50, 288, 36, 49, 15, 2, 3, 40, 49, 289, 36, 48, 16, 2, 3, 40, 50, 288, 36, 48, 16, 3, 1, 41, 50, 288, 36, 48, 16, 3, 1, 42, 49, 288, 35, 49, 17, 2, 1, 42, 48, 289, 35, 49, 17, 2, 1, 42, 49, 288, 35, 49, 17, 2, 1, 36, 1, 5, 49, 288, 35, 49, 17, 3, 1, 29, 7, 5, 49, 288, 35, 48, 18, 3, 2, 19, 16, 5, 49, 197, 10, 81, 34, 49, 19, 2, 3, 9, 25, 6, 48, 196, 12, 80, 34, 49, 19, 2, 5, 2, 30, 6, 48, 195, 14, 80, 33, 49, 19, 2, 6, 1, 30, 6, 48, 194, 16, 79, 33, 49, 19, 3, 36, 6, 48, 194, 16, 79, 33, 49, 19, 3, 36, 5, 50, 193, 16, 79, 33, 49, 20, 2, 36, 5, 50, 193, 16, 79, 33, 49, 20, 2, 36, 5, 51, 192, 16, 79, 33, 49, 20, 3, 35, 5, 51, 191, 18, 79, 32, 49, 20, 3, 35, 5, 52, 189, 20, 3, 7, 68, 32, 49, 20, 3, 34, 6, 52, 188, 22, 1, 9, 68, 31, 49, 21, 2, 34, 6, 52, 187, 34, 67, 31, 49, 21, 2, 34, 6, 53, 186, 35, 66, 31, 49, 21, 3, 33, 5, 54, 186, 35, 66, 32, 48, 21, 3, 33, 5, 54, 186, 35, 66, 32, 48, 21, 3, 33, 5, 55, 185, 35, 67, 31, 48, 22, 2, 33, 5, 55, 185, 35, 67, 31, 48, 22, 2, 33, 5, 55, 185, 35, 67, 30, 49, 22, 3, 32, 4, 55, 187, 34, 67, 31, 48, 22, 3, 32, 3, 56, 188, 33, 67, 31, 48, 22, 3, 32, 3, 56, 189, 32, 67, 31, 14, 5, 29, 23, 2, 33, 2, 57, 188, 32, 68, 30, 13, 6, 29, 23, 2, 34, 1, 39, 1, 17, 188, 32, 69, 29, 12, 6, 24, 1, 5, 23, 3, 65, 2, 4, 3, 17, 189, 31, 71, 4, 2, 21, 12, 14, 23, 22, 3, 64, 10, 17, 189, 31, 77, 21, 12, 21, 17, 22, 2, 64, 10, 17, 190, 30, 79, 19, 12, 29, 9, 22, 2, 64, 10, 17, 190, 30, 79, 19, 12, 34, 4, 22, 3, 63, 11, 16, 190, 29, 80, 19, 12, 35, 3, 22, 3, 63, 12, 14, 191, 28, 81, 19, 12, 35, 3, 22, 3, 62, 14, 12, 192, 2, 107, 19, 13, 34, 4, 22, 2, 61, 17, 8, 194, 2, 107, 19, 14, 33, 4, 22, 2, 54, 1, 4, 222, 1, 107, 19, 14, 33, 4, 22, 3, 53, 227, 1, 106, 20, 14, 33, 4, 22, 3, 53, 227, 26, 81, 20, 14, 33, 4, 22, 2, 34, 1, 20, 226, 26, 81, 20, 14, 33, 4, 58, 1, 21, 225, 26, 81, 20, 15, 32, 4, 58, 1, 21, 225, 26, 81, 20, 16, 31, 4, 58, 1, 21, 225, 26, 81, 20, 17, 30, 5, 56, 3, 20, 225, 26, 82, 19, 16, 31, 5, 19, 1, 35, 5, 19, 224, 28, 80, 20, 15, 32, 5, 54, 7, 18, 223, 29, 80, 20, 14, 33, 5, 54, 7, 18, 223, 29, 80, 20, 17, 29, 6, 54, 7, 18, 223, 29, 80, 20, 26, 20, 7, 53, 8, 17, 223, 29, 80, 20, 10, 1, 24, 11, 6, 54, 8, 17, 222, 30, 80, 20, 9, 3, 32, 1, 7, 54, 8, 16, 222, 31, 80, 19, 9, 4, 40, 54, 8, 16, 222, 31, 80, 19, 9, 4, 41, 53, 8, 16, 221, 32, 80, 19, 9, 15, 30, 53, 9, 15, 220, 33, 80, 19, 9, 18, 2, 6, 19, 53, 9, 14, 221, 33, 80, 18, 10, 27, 18, 53, 10, 13, 220, 34, 80, 18, 10, 34, 11, 53, 10, 12, 220, 35, 80, 18, 10, 4, 16, 15, 11, 52, 10, 12, 220, 35, 27, 6, 34, 6, 7, 17, 11, 4, 43, 51, 10, 12, 220, 35, 26, 8, 32, 8, 6, 17, 11, 4, 43, 51, 10, 12, 220, 36, 24, 15, 4, 6, 15, 9, 6, 17, 11, 25, 22, 51, 10, 12, 220, 36, 23, 17, 2, 8, 13, 10, 6, 17, 11, 37, 10, 51, 10, 12, 220, 36, 42, 9, 12, 10, 6, 16, 12, 37, 10, 51, 10, 12, 220, 36, 63, 31, 14, 36, 11, 50, 11, 10, 221, 36, 18, 5, 21, 8, 11, 31, 15, 36, 10, 49, 13, 8, 222, 36, 17, 35, 11, 34, 12, 36, 10, 48, 16, 4, 225, 35, 17, 35, 11, 35, 11, 36, 10, 47, 247, 34, 17, 35, 11, 36, 10, 37, 9, 46, 247, 35, 17, 35, 11, 37, 9, 37, 9, 44, 248, 36, 17, 35, 10, 38, 9, 37, 9, 42, 250, 35, 18, 35, 10, 38, 9, 37, 10, 39, 252, 35, 18, 35, 10, 38, 9, 37, 11, 36, 253, 36, 18, 35, 10, 38, 9, 38, 10, 35, 254, 36, 19, 34, 9, 39, 9, 38, 10, 24, 2, 7, 256, 36, 19, 34, 9, 39, 9, 38, 9, 25, 4, 3, 257, 37, 19, 34, 9, 39, 9, 38, 9, 25, 264, 37, 19, 33, 10, 39, 9, 38, 9, 25, 264, 37, 19, 32, 11, 39, 9, 38, 9, 25, 264, 36, 21, 10, 4, 15, 13, 39, 8, 39, 9, 24, 265, 36, 22, 8, 5, 12, 16, 39, 8, 39, 9, 23, 266, 36, 15, 13, 8, 10, 17, 39, 8, 39, 9, 21, 268, 36, 14, 14, 9, 13, 13, 39, 8, 39, 9, 20, 269, 36, 13, 16, 10, 12, 12, 39, 8, 39, 9, 18, 270, 37, 12, 18, 1, 6, 5, 10, 12, 38, 8, 39, 9, 16, 271, 38, 12, 26, 3, 12, 12, 10, 8, 18, 9, 39, 9, 14, 273, 39, 11, 27, 2, 12, 14, 6, 10, 19, 8, 39, 9, 12, 275, 39, 11, 41, 31, 18, 8, 39, 9, 11, 276, 40, 10, 41, 31, 18, 8, 39, 10, 10, 276, 40, 10, 41, 31, 17, 9, 39, 11, 8, 277, 40, 10, 41, 31, 17, 10, 38, 13, 4, 279, 39, 12, 40, 31, 16, 12, 37, 296, 39, 13, 38, 33, 14, 14, 36, 297, 37, 16, 4, 2, 4, 2, 23, 35, 12, 15, 36, 298, 37, 27, 22, 38, 4, 21, 36, 299, 37, 27, 21, 63, 12, 1, 23, 300, 36, 28, 8, 1, 10, 64, 12, 1, 22, 302, 35, 30, 4, 4, 8, 65, 12, 1, 21, 304, 11, 1, 22, 40, 4, 68, 10, 3, 19, 306, 9, 4, 5, 1, 14, 113, 8, 5, 18, 308, 5, 12, 14, 115, 4, 9, 15, 326, 14, 128, 15, 327, 12, 129, 14, 329, 10, 130, 12, 333, 6, 132, 12, 472, 10, 474, 8, 477, 4, 34074],
"size": [483, 640]
},
"area": 20933,
"iscrowd": 1,
"image_id": 632,
"bbox": [416, 43, 153, 303],
"category_id": 84,
"id": 908400000632
}]
}七、COCODataset
代码请看：datasets/coco.py