jaclearn.vision.coco.pycocotools package

Submodules

jaclearn.vision.coco.pycocotools.coco module

class jaclearn.vision.coco.pycocotools.coco.COCO(annotation_file=None)

Bases: object

annToMask(ann)

Convert annotation which can be polygons, uncompressed RLE, or RLE to binary mask. :return: binary mask (numpy 2D array)

annToRLE(ann)

Convert annotation which can be polygons, uncompressed RLE to RLE. :return: binary mask (numpy 2D array)

createIndex()

download(tarDir=None, imgIds=[])

Download COCO images from mscoco.org server. :param tarDir (str): COCO results directory name

imgIds (list): images to be downloaded

Returns:

getAnnIds(imgIds=[], catIds=[], areaRng=[], iscrowd=None)

Get ann ids that satisfy given filter conditions. default skips that filter :param imgIds (int array) : get anns for given imgs

catIds (int array) : get anns for given cats areaRng (float array) : get anns for given area range (e.g. [0 inf]) iscrowd (boolean) : get anns for given crowd label (False or True)

Returns:ids (int array) : integer array of ann ids

getCatIds(catNms=[], supNms=[], catIds=[])

filtering parameters. default skips that filter. :param catNms (str array) : get cats for given cat names :param supNms (str array) : get cats for given supercategory names :param catIds (int array) : get cats for given cat ids :return: ids (int array) : integer array of cat ids

getImgIds(imgIds=[], catIds=[])

Get img ids that satisfy given filter conditions. :param imgIds (int array) : get imgs for given ids :param catIds (int array) : get imgs with all given cats :return: ids (int array) : integer array of img ids

info()

Print information about the annotation file. :return:

loadAnns(ids=[])

Load anns with the specified ids. :param ids (int array) : integer ids specifying anns :return: anns (object array) : loaded ann objects

loadCats(ids=[])

Load cats with the specified ids. :param ids (int array) : integer ids specifying cats :return: cats (object array) : loaded cat objects

loadImgs(ids=[])

Load anns with the specified ids. :param ids (int array) : integer ids specifying img :return: imgs (object array) : loaded img objects

loadNumpyAnnotations(data)

Convert result data from a numpy array [Nx7] where each row contains {imageID,x1,y1,w,h,score,class} :param data (numpy.ndarray) :return: annotations (python nested list)

loadRes(resFile)

Load result file and return a result api object. :param resFile (str) : file name of result file :return: res (obj) : result api object

showAnns(anns)

Display the specified annotations. :param anns (array of object): annotations to display :return: None

jaclearn.vision.coco.pycocotools.cocoeval module

class jaclearn.vision.coco.pycocotools.cocoeval.COCOeval(cocoGt=None, cocoDt=None, iouType='segm')

Bases: object

accumulate(p=None)

Accumulate per image evaluation results and store the result in self.eval :param p: input params for evaluation :return: None

computeIoU(imgId, catId)

computeOks(imgId, catId)

evaluate()

Run per image evaluation on given images and store results (a list of dict) in self.evalImgs :return: None

evaluateImg(imgId, catId, aRng, maxDet)

perform evaluation for single category and image :return: dict (single image results)

summarize()

Compute and display summary metrics for evaluation results. Note this functin can only be applied on the default parameter setting

class jaclearn.vision.coco.pycocotools.cocoeval.Params(iouType='segm')

Bases: object

Params for coco evaluation api

setDetParams()

setKpParams()

jaclearn.vision.coco.pycocotools.mask module

jaclearn.vision.coco.pycocotools.mask.area(rleObjs)

jaclearn.vision.coco.pycocotools.mask.decode(rleObjs)

jaclearn.vision.coco.pycocotools.mask.encode(bimask)

jaclearn.vision.coco.pycocotools.mask.toBbox(rleObjs)