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.
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.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.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:{
"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]
},
...
Last modified 30d ago