chrise96/image-to-coco-json-converter

Convert segmentation RGB mask images to COCO JSON format

image-to-coco-json-converter's Issues

Keyerror '(1, 1, 1)'

Hi,
I have a mask with values "(2, 2, 2)": 0 which I added in the category_colors. Why is it giving me a key error of "(1, 1, 1)" ? The pixel values in my mask are either (0, 0, 0) for background or (2, 2, 2) for mask. Thanks

get alot of polygon points

Hello @chrise96,

thank you for providing this amazing repo. I have just successfully ran and visualized annotations as well. But when I load this json file into annotation tool then it has so many multiple points because of many polygon points. is it possible to discard unnecessary points and stores only required points if shape changes??

Your help will be appreciated. thank you inadvance.

KeyError: '(0, 0, 0)'

'MultiPolygon' object has no attribute 'exterior'

Hi
Thank you for putting the effort on creating this great repo.

I am trying to convert binary images to coco annotations, but i get this error. can you please explain why is this happening and how can i solve it. I also googled it, but have not been lucky yet.
"""

AttributeError Traceback (most recent call last)
Input In [5], in
84 coco_format["categories"] = create_category_annotation(category_ids)
86 # Create images and annotations sections
---> 87 coco_format["images"], coco_format["annotations"], annotation_cnt = images_annotations_info(mask_path)
89 with open("output/{}.json".format(keyword),"w") as outfile:
90 json.dump(coco_format, outfile)

Input In [5], in images_annotations_info(maskpath)
50 category_id = category_colors[color]
52 # "annotations" info
---> 53 polygons, segmentations = create_sub_mask_annotation(sub_mask)
55 # Check if we have classes that are a multipolygon
56 if category_id in multipolygon_ids:
57 # Combine the polygons to calculate the bounding box and area

File ~/Desktop/Py_js/Data/python_with_vlad/pycharm/polymore/Binary-Image_to_coco/image-to-coco-json-converter-master/src/create_annotations.py:56, in create_sub_mask_annotation(sub_mask)
52 continue
54 polygons.append(poly)
---> 56 segmentation = np.array(poly.exterior.coords).ravel().tolist()
57 segmentations.append(segmentation)
59 return polygons, segmentations

AttributeError: 'MultiPolygon' object has no attribute 'exterior'

"""

Thanks in advance.

I don't know this error

KeyError Traceback (most recent call last)
in ()
84
85 # Create images and annotations sections
---> 86 coco_format["images"], coco_format["annotations"], annotation_cnt = images_annotations_info(mask_path)
87
88 with open("output/{}.json".format(keyword),"w") as outfile:

in images_annotations_info(maskpath)
47 sub_masks = create_sub_masks(mask_image_open, w, h)
48 for color, sub_mask in sub_masks.items():
---> 49 category_id = category_colors[color]
50
51 # "annotations" info

KeyError: '(130, 130, 130)'

Interior contours

I have been using your code for a while, and I noticed that object that have a inside ring, this inside ring gets ignored and only keeps the exterior contours.
Example
here is the submask generated for a category by your code

after all the code is executed, I tried to reconstruct the mask from the segmentation generated using the following code

from pycocotools import mask as maskUtils
def annToRLE( ann, height, width):
        """
        Convert annotation which can be polygons, uncompressed RLE to RLE.
        :return: binary mask (numpy 2D array)
        """
        segm = ann['segmentation']
        if isinstance(segm, list):
            # polygon -- a single object might consist of multiple parts
            # we merge all parts into one mask rle code
            rles = maskUtils.frPyObjects(segm, height, width)
            rle = maskUtils.merge(rles)
        elif isinstance(segm['counts'], list):
            # uncompressed RLE
            rle = maskUtils.frPyObjects(segm, height, width)
        else:
            # rle
            rle = ann['segmentation']
        return rle

def annToMask( ann, height, width):
    """
    Convert annotation which can be polygons, uncompressed RLE, or RLE to binary mask.
    :return: binary mask (numpy 2D array)
    """
    rle = annToRLE(ann, height, width)
    m = maskUtils.decode(rle)
    return m

and this is the reconstructed mask

as you can see the object now is only one piece without the inside contours

is there a way to keep the inside ring also ?
Do you think the problem is in the functions that reconstruct the mask or your code?

'MultiPolygon' object has no attribute 'exterior'

Get this error when trying to convert these types of masks to json . I assume its because of the weird polygons:

mask_sample

Similar issue reported here akTwelve/cocosynth#9 and maybe fixed here https://github.com/akTwelve/cocosynth/blob/3909837290ab3511ff03ffe57ae870c929bd40a0/python/coco_json_utils.py

double annotations

I was trying your code, and it seems i am getting 13 segmentations, including one for the entire image.
my mask has only 6 annotations, all same category id.
I have commented the multipolygon, since I do not need it and changed some codes since I have only 1 catgeory.

Any ideas?

AttributeError: 'MultiPolygon' object has no attribute 'exterior'

I try to run the script, if the annotations more than 300, it will error with 'AttributeError: 'MultiPolygon' object has no attribute 'exterior''. How I can solve this problem?

Error When running script AttributeError: 'Image' object has no attribute 'shape'

Hello,
I have clones the repo and done absolutly 0 modification.
When running your notebook i get AttributeError: 'Image' object has no attribute 'shape'.
More details :

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-77e827a19691> in <module>
     67     for keyword in ['train', 'val']:
     68         mask_path = 'dataset/{}_mask'.format(keyword)
---> 69         coco_format['images'], coco_format['annotations'] = images_annotations_info(mask_path)
     70         #print(json.dumps(coco_format))
     71         with open('output/{}.json'.format(keyword),'w') as outfile:

<ipython-input-2-77e827a19691> in images_annotations_info(maskpath)
     41 
     42             # 'annotations' info
---> 43             polygons, segmentations = create_sub_mask_annotation(sub_mask)
     44 
     45             # Three labels are multipolygons in our case: wall, roof and sky

D:\PERSO\PERSONAL WORK\15 - AI MachineLearning\image-to-coco-json-converter\create_annotations.py in create_sub_mask_annotation(sub_mask)
     35     # Note: there could be multiple contours if the object
     36     # is partially occluded. (E.g. an elephant behind a tree)
---> 37     contours = measure.find_contours(sub_mask, 0.5, positive_orientation='low')
     38 
     39     polygons = []

c:\users\richa\appdata\local\programs\python\python37\lib\site-packages\skimage\measure\_find_contours.py in find_contours(array, level, fully_connected, positive_orientation, mask)
    121         raise ValueError('Parameters "positive_orientation" must be either '
    122                          '"high" or "low".')
--> 123     if array.shape[0] < 2 or array.shape[1] < 2:
    124         raise ValueError("Input array must be at least 2x2.")
    125     if array.ndim != 2:

AttributeError: 'Image' object has no attribute 'shape'

Pip versions :
Pillow 8.0.1
numpy 1.18.5
scikit-image 0.17.2
Shapely 1.7.1

Mabey this is linked to a different version of a library ?

Thanks in advance

how to clip overlay area?

i have a dataset from a lot of complex shape.
but this model was not able to clip overlay area.
how to clip overlay area?
this is my dataset, thanks.

https://drive.google.com/drive/folders/1butmjjGTgMIEr6bq1nQ3ejjm0M7oN_YR?usp=share_link

Grayscale image

I want to use your code but I have grayscale masks, where each category is coded with a value, could you guide me to what should be changed in order to achieve this.
Thanks

Background annotations

Hello,

I have a question about background annotations:

I have a Black and White mask: Black == Background ; White == The object I segmented

Unfortunately now, when I only add the white part to the category the script complains, that it has a key error at (0,0,0). But if I add the (0,0,0) I have the issue, that the background also is an annotation.

Do you have any idea how to resolve this?