How to understand YOLO_LABELS in noscope_motherdog.py

[janhuang6]

I see this in noscope_motherdog.py:

YOLO_LABELS["coral-reef-long"] = (
0,
[("coral-reef-long_convnet_32_32_1.pb", None),
("coral-reef-long_convnet_32_32_2.pb", None),],
648000 + 1188000,
1188000,
648000 + 1188000 * 2,
1188000
)

So what do those numbers mean? Is there a document explaining those?
I really need to understand those so I can add my own
YOLO_LABELS["my-video"] session with the correct numbers to have Yolo process my video.

Right now, Yolo is not processing my video correctly because those numbers are not setup right.

[janhuang6]

I found the answer. The meanings are:
0 means “yolo_label_num”
[("coral-reef-long_convnet_32_32_1.pb", None),
("coral-reef-long_convnet_32_32_2.pb", None),] is the pipelines
648000 + 1188000 is the TRAIN_START_IDX
1188000 is the TRAIN_LEN,
648000 + 1188000 * 2 is the TEST_START_IDX,
1188000 is the TEST_LEN

[sxhexe]

@janhuang6 Is pipeline just the cnn model? Why is there only two instead of all the 12 CNN's they've trained?
Also, do you know how they index the videos? I thought there were only 1188000 frames, and 648000 + 1188000 would be out of range.