cocoapi中提供的函数：

# The following API functions are defined:
#  COCO       - COCO api class that loads COCO annotation file and prepare data structures.
#  decodeMask - Decode binary mask M encoded via run-length encoding.
#  encodeMask - Encode binary mask M using run-length encoding.
#  getAnnIds  - Get ann ids that satisfy given filter conditions.
#  getCatIds  - Get cat ids that satisfy given filter conditions.
#  getImgIds  - Get img ids that satisfy given filter conditions.
#  loadAnns   - Load anns with the specified ids.
#  loadCats   - Load cats with the specified ids.
#  loadImgs   - Load imgs with the specified ids.
#  annToMask  - Convert segmentation in an annotation to binary mask.
#  showAnns   - Display the specified annotations.
#  loadRes    - Load algorithm results and create API for accessing them.
#  download   - Download COCO images from mscoco.org server.
# Throughout the API "ann"=annotation, "cat"=category, and "img"=image.
# Help on each functions can be accessed by: "help COCO>function".

coco的标注文件ground_truth

1.加载标注文件

from pycocotools.coco import COCO

cocoGt=COCO(annFile)

2.方法：

cocoGt.getImgIds()  获得所有图像的id，有多少张图像就有多少个id

coco.getCatIds() 获得所偶有类别的id

#获得所有类别的名字

cats = coco.loadCats(coco.getCatIds())
nms=[cat['name'] for cat in cats] 

#获得满足指定条件的ID

catIds = coco.getCatIds(catNms=['person','dog','skateboard']);
imgIds = coco.getImgIds(catIds=catIds );
imgIds = coco.getImgIds(imgIds = [324158])

#获得标注

annIds = coco.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None)
anns = coco.loadAnns(annIds)
coco.showAnns(anns) #显示标注

coco的预测结果文件detection_result:

文件格式：

参考https://blog.csdn.net/u014734886/article/details/78831382

目标检测的文件格式：

[{"image_id":42,"category_id":18,"bbox":[258.15,41.29,348.26,243.78],"score":0.236},{"image_id":73,"category_id":11,"bbox":[61,22.75,504,609.67],"score":0.318}]
其中bbox中是左上角坐标和宽度，高度

通过ground_truth和detection_result评估结果：

# running evaluation
cocoEval = COCOeval(cocoGt,cocoDt,annType)
cocoEval.params.imgIds  = imgIds
cocoEval.evaluate()
cocoEval.accumulate()
cocoEval.summarize()