How to create mask images from COCO dataset?

Question

So I have been using this code,. I am trying to generate the raw mask of the images from COCO dataset.

dataDir='G:'
dataType='train2014'
annFile='{}/annotations/instances_{}.json'.format(dataDir,dataType)


coco=COCO(annFile)
annFile = '{}/annotations/person_keypoints_{}.json'.format(dataDir,dataType)
coco_kps=COCO(annFile)


catIds = coco.getCatIds(catNms=['person'])
imgIds = coco.getImgIds(catIds=catIds );
imgIds = coco.getImgIds(imgIds = imgIds[0])
img = coco.loadImgs(imgIds[np.random.randint(0,len(imgIds))])[0]
I = io.imread('G:/train2014/'+img['file_name'])

plt.imshow(I); plt.axis('off')
annIds = coco.getAnnIds(imgIds=img['id'], catIds=catIds, iscrowd=None)
anns = coco.loadAnns(annIds)
coco.showAnns(anns)

But what i get is some thing like this

But what I want is something like this

How can I get the raw mask against each image ?

Answer 1

The complete code wasn't in the answer so I post it below.

Please install pycocotools first.

pip install pycocotools

Import the required modules. I'm assuming you're using a jupyter notebook.

from pycocotools.coco import COCO
import os
from PIL import Image
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline

Load the annotations for the coco dataset. Here, specify the 74 image.

coco = COCO('../datasets/coco/annotations/instances_train2017.json')
img_dir = '../datasets/coco/train2017'
image_id = 74

img = coco.imgs[image_id]
# loading annotations into memory...
# Done (t=12.70s)
# creating index...
# index created!

The information of the loaded img is as follows.

img
# {'license': 2,
#  'file_name': '000000000074.jpg',
#  'coco_url': # 'http://images.cocodataset.org/train2017/000000000074.jpg',
#  'height': 426,
#  'width': 640,
#  'date_captured': '2013-11-15 03:08:44',
#  'flickr_url': # 'http://farm5.staticflickr.com/4087/5078192399_aaefdb5074_z.jpg# ',
#  'id': 74}

Display the image as follows.

image = np.array(Image.open(os.path.join(img_dir, img['file_name'])))
plt.imshow(image, interpolation='nearest')
plt.show()

If you want to see the overlay result:

plt.imshow(image)
cat_ids = coco.getCatIds()
anns_ids = coco.getAnnIds(imgIds=img['id'], catIds=cat_ids, iscrowd=None)
anns = coco.loadAnns(anns_ids)
coco.showAnns(anns)

If you just want to see the mask, as Farshid Rayhan replied, do the following:

mask = coco.annToMask(anns[0])
for i in range(len(anns)):
    mask += coco.annToMask(anns[i])

plt.imshow(mask)

Answer 2

Following Mr Filippo intuition I was able to make the correct code, which looks something like this.

mask = coco.annToMask(anns[0])
for i in range(len(anns)):
    mask += coco.annToMask(anns[i])

plt.imshow(mask)