Segmentation Masks and Metadata

Celantur container can generate two different segmentation masks and metadata per processed image:
  • Binary Segmentation
  • Instance Segmentation
It's activated with the --save-mask {all, instance, binary} parameter. The segmentation is saved as a PNG file.
Anonymization, binary segmentation and instance segmentation applied to an image with Celantur software.

Binary Segmentation

The binary segmentation mask consist of two colors:
  • Background is black
  • Anonymized segments are white
The file will be saved as image-name_bin_mask.png.

Instance Segmentation

The instance segmentation mask consists of multiple colors. The RGB color values are used to differentiate to individual instances/objects.
  • The R (red) channel encodes the object type:
    • License plate: 64
    • Person: 128
    • Face: 192
    • Vehicle: 255
  • The G (green) channel encodes individual instances/objects.
  • The B (blue) channel is 0.
E.g. [192, 85, 0] is a face.
The file will be saved as image-name_ins_maks.png.

Scale Down Mask Files

By adding the optional --mask-scale {0-100} (CLI) or /v1/file/1/instance-mask?mask-scale={0-100} (Container API) parameter, mask files will be scaled down by the specified ratio.


Metadata about detected instances/objects are stored in the corresponding image-name.json file.
Detected instances/objects provided as a list under the detections attribute:
The id of the detection
The name of the image the detected instance/object was found on
The offset of the detection's bounding box from the upper left corner of the image (x/y coordinates in pixels)
The coordinates of the detection's bounding box (x1, y1, x2, y2)
The detection's confidence score. States how confident the model is about the detection being a specific label (see type_label) between 0.0 and 1.0.
Specifies whether the detection was anonymized.
The detection's label assigned by the model. E.g. face, license plates, etc.
The detections color (RGB) in the instance segmentation mask.
"id": "image-name.jpg",
"detections": [
"id": 0,
"parent_image": "image-name.jpg",
"offset": [1586, 776],
"bbox": [1586, 776, 3094, 3453],
"type": 102,
"score": 0.9994864463806152,
"is_anonymised": true,
"type_label": "person",
"color": [128, 85, 0]
"id": 0,
"parent_image": "image-name.jpg",
"offset": [3691, 674],
"bbox": [3691, 674, 5180, 3431],
"type": 102,
"score": 0.9987647533416748,
"is_anonymised": true,
"type_label": "person",
"color": [128, 170, 0]