Comments (1)
Presently you cannot export the anchors of the bounding boxes into a json file.
But you can obtain the following arrays.
-Detected Objects' arrays
-Objects' corresponding class_ids' arrays
-Segmentation masks' arrays
-Output's array
By using this code
segmask, output = segment_image.segmentImage()
You can test the code for obtaining arrays and print out the shape of the output by modifying the instance segmentation code below.
`import pixellib
from pixellib.instance import instance_segmentation
import cv2
instance_seg = instance_segmentation()
instance_seg.load_model("mask_rcnn_coco.h5")
segmask, output = instance_seg.segmentImage("sample2.jpg")
cv2.imwrite("img.jpg", output)
print(output.shape)`
Obtain arrays of segmentation with bounding boxes by including the parameter show_bboxes.
segmask, output = segment_image.segmentImage(show_bboxes = True)
The full code
`import pixellib
from pixellib.instance import instance_segmentation
import cv2
instance_seg = instance_segmentation()
instance_seg.load_model("mask_rcnn_coco.h5")
segmask, output = instance_seg.segmentImage("sample2.jpg", show_bboxes= True)
cv2.imwrite("img.jpg", output)
print(output.shape)
`
I will consider the exportation of anchors of bounding boxes into json in the future version of this library.
from pixellib.
Related Issues (20)
- #389 layer
- ImportError: cannot import name 'semantic_segmentation' from 'pixellib.semantic' HOT 7
- Error when checking input: expected input_image_meta to have shape (18,) but got array with shape (16,) during last step HOT 1
- Error when loading a pretrained model
- Loading Custom Dataset error HOT 4
- Is training with different labels in the same image possible? HOT 3
- labelme2coco does not work with Windows 11 HOT 4
- training time does not reduces after increasing batch_size on 32 GB CPU instance HOT 1
- What are the correct corresponding versions of pixlib and TensorFlow? HOT 1
- sometimes image does not get segmented with polygon bounding boxes but only with rectangle bounding boxes
- Using pixelLib simply for segmetnation. HOT 1
- Custom Segmentation - Errno 13 error HOT 2
- Semantic segmentation output rgb values do not match input class values
- Error:No pointrend_resnet50 model found
- PIL.Image AttributeError HOT 1
- mask label for training
- Make segment overlay invisible
- For newer version of Tensorflow, you should change code.
- not useful
- Import pixellib.tune_bg
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from pixellib.