Large objects with large custom anchors - How to modify masks in CFG?

[marvision-ai]

How does one input custom anchors that do not follow the same trend as the original anchors (x<30, 30>x<60, and x>60)?
For reference: Img size = 1280x736

Original Anchors :

anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401

This leaves you with:

[yolo]
mask = 6,7,8
anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
classes=1
num=9
jitter=.3
scale_x_y = 1.05
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
ignore_thresh = .7
truth_thresh = 1
random=0
resize=1.5
nms_kind=greedynms
beta_nms=0.6

[yolo]
mask = 3,4,5
anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
classes=1
num=9
jitter=.3
scale_x_y = 1.05
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
ignore_thresh = .7
truth_thresh = 1
random=0
resize=1.5
nms_kind=greedynms
beta_nms=0.6

[yolo]
mask = 0,1,2
anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 459, 401
classes=1
num=9
jitter=.3
scale_x_y = 1.05
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
ignore_thresh = .7
truth_thresh = 1
random=0
resize=1.5
nms_kind=greedynms
beta_nms=0.6

New Anchors:

./darknet detector calc_anchors object.data -num_of_clusters 9 -width 1280 -height 736 -show

anchors = 242,237, 311,314, 388,390, 444,454, 459,495, 506,472, 512,547, 565,578, 599,613

new masks in .cfg file?

I am not sure how to do this because everything is above 60x60, and the layers of the 3l Model require x<30, 30>x<60, and x>60

[yolo]
mask = ?? 
anchors = 242,237, 311,314, 388,390, 444,454, 459,495, 506,472, 512,547, 565,578, 599,613
classes=1
num=9
jitter=.3
scale_x_y = 1.05
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
ignore_thresh = .7
truth_thresh = 1
random=0
resize=1.5
nms_kind=greedynms
beta_nms=0.6

[yolo]
mask = ??
anchors = 242,237, 311,314, 388,390, 444,454, 459,495, 506,472, 512,547, 565,578, 599,613
classes=1
num=9
jitter=.3
scale_x_y = 1.05
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
ignore_thresh = .7
truth_thresh = 1
random=0
resize=1.5
nms_kind=greedynms
beta_nms=0.6

[yolo]
mask = ??
anchors = 242,237, 311,314, 388,390, 444,454, 459,495, 506,472, 512,547, 565,578, 599,613
classes=1
num=9
jitter=.3
scale_x_y = 1.05
cls_normalizer=1.0
iou_normalizer=0.07
iou_loss=ciou
ignore_thresh = .7
truth_thresh = 1
random=0
resize=1.5
nms_kind=greedynms
beta_nms=0.6

Thank you in advance!

[JeremyKeusters]

I have a similar issue actually. I'm using a YOLOv4-tiny and all my calculated anchors are between 200-350. My objects will always be the same size and I'm not applying any rescaling augmentation. What would be the best practice for the mask indices? Because in the case of YOLOv4-tiny, I wouldn't have any anchors for my last YOLO layer (as there are none below 60). @AlexeyAB do you have any advice on this? Thanks in advance!

[meetyogi98]

I also have a similar issue but for yolov4 having all layers

I have calculated anchor boxes for my custom dataset and got the following anchor boxes: 109, 9, 66, 17, 168, 7, 179, 11, 129, 25, 290, 21, 219, 75, 539, 49, 546,214

Alexey suggests the following thing for anchors: Only if you are an expert in neural detection networks - recalculate anchors for your dataset for width and height from cfg-file: darknet.exe detector calc_anchors data/obj.data -num_of_clusters 9 -width 416 -height 416 then set the same 9 anchors in each of 3 [yolo]-layers in your cfg-file. But you should change indexes of anchors masks= for each [yolo]-layer, so for YOLOv4 the 1st-[yolo]-layer has anchors smaller than 30x30, 2nd smaller than 60x60, 3rd remaining, and vice versa for YOLOv3. Also, you should change the filters=(classes + 5)* before each [yolo]-layer. If many of the calculated anchors do not fit under the appropriate layers - then just try using all the default anchors.

I do not get the point "so for YOLOv4 the 1st-[yolo]-layer has anchors smaller than 30x30, 2nd smaller than 60x60, 3rd remaining, and vice versa for YOLOv3."

How should I make changes in cfg according to anchors boxes I have generated in all three yolo layers in mask and anchors variable of cfg?