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In this section, we will read the coco labels file. This file contains the labels of the object the model was trained against. We will also create a COLORS array which will give a different color for each label. Note that the coco has 90 labels by default.
label_file to the file path
/cxldata/dlcourse/mask_rcnn_model_data/object_detection_classes_coco.txt where the labels are stored. Remember to put quotes (" ") around the path.
label_file=<< your code comes here >>
Get the labels
LABELS from the file:
LABELS = open(label_file).read().strip().split("\n")
Randomly generate the colors(the R value, G value and B value) using
np.random.randint for each label(thus the size (len(LABELS), 3). These colors will be used to highlight the detected object of that class later.
COLORS = np.random.<< your code comes here >>(0, 255, size=(len(LABELS), 3), dtype="uint8")
Let us have a look at the first 5 classes in the file:
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