AssertionError occurred during program execution.

[masahiro1101]

hello. @GeekAlexis I am building FastMOT on Jetson Xavier NX Docker. Using Yolov4-tiny trained by myself. I changed the settings in FastMOT/fastmot/models/yolo.py. After making the changes, I get the following error when I run the program. Do you know what is the cause of this?

In addition, although we are using the initial value for Fast-Reid this time, Could this be the cause?

[GeekAlexis]

Make sure you set the network parameters in fastmot.models correctly for your model.

[masahiro1101]

@GeekAlexis Thank you for your comment. ＞Make sure you set the network parameters in fastmot.models correctly for your model. As above, I have rewritten the following: ・FastMOT/fastmot/models/yolo.py.

I don't know how to write network parameters, so I would appreciate it if you could tell me where to change specifically. I apologize for asking such a strange question. . .

As a config of yolov4-tiny, Below is the content.

[net]

Testing

batch=1 subdivisions=1

Training

batch=64

subdivisions=16

width=416 height=416 channels=3 momentum=0.9 decay=0.0005 angle=0 saturation = 1.5 exposure = 1.5 hue=.1

learning_rate=0.00261 burn_in=1000 max_batches = 12880 policy=steps steps=10304,11592 scales=.1,.1

[convolutional] batch_normalize=1 filters=32 size=3 stride=2 pad=1 activation=leaky

[convolutional] batch_normalize=1 filters=64 size=3 stride=2 pad=1 activation=leaky

[convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=leaky

[route] layers=-1 groups=2 group_id=1

[convolutional] batch_normalize=1 filters=32 size=3 stride=1 pad=1 activation=leaky

[convolutional] batch_normalize=1 filters=32 size=3 stride=1 pad=1 activation=leaky

[route] layers = -1,-2

[convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=leaky

[route] layers = -6,-1

[maxpool] size=2 stride=2

[convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=leaky

[route] layers=-1 groups=2 group_id=1

[convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=leaky

[convolutional] batch_normalize=1 filters=64 size=3 stride=1 pad=1 activation=leaky

[route] layers = -1,-2

[convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky

[route] layers = -6,-1

[maxpool] size=2 stride=2

[convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky

[route] layers=-1 groups=2 group_id=1

[convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=leaky

[convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=leaky

[route] layers = -1,-2

[convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky

[route] layers = -6,-1

[maxpool] size=2 stride=2

[convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky

##################################

[convolutional] batch_normalize=1 filters=256 size=1 stride=1 pad=1 activation=leaky

[convolutional] batch_normalize=1 filters=512 size=3 stride=1 pad=1 activation=leaky

[convolutional] size=1 stride=1 pad=1 filters=18 activation=linear

[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

[route] layers = -4

[convolutional] batch_normalize=1 filters=128 size=1 stride=1 pad=1 activation=leaky

[upsample] stride=2

[route] layers = -1, 23

[convolutional] batch_normalize=1 filters=256 size=3 stride=1 pad=1 activation=leaky

[convolutional] size=1 stride=1 pad=1 filters=18 activation=linear

[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

[route] layers = -3

[convolutional] batch_normalize=1 filters=64 size=1 stride=1 pad=1 activation=leaky

[upsample] stride=2

[route] layers = -1, 15

[convolutional] batch_normalize=1 filters=128 size=3 stride=1 pad=1 activation=leaky

[convolutional] size=1 stride=1 pad=1 filters=18 activation=linear

[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

[masahiro1101]

@GeekAlexis

There was a mistake in the setting, so I set it again. How the content of AssertionError changed. I would like to know what the cause is, but could you give me some advice?

[masahiro1101]

@GeekAlexis The movement of the TRT file was strange, so I converted it again. As a result, it is now readable. I apologize for the trouble. Thank you for your response.