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Feature-request: State-of-art Yolo v4 Detector Β· Issue #17148 Β· opencv/opencv Β· GitHub
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Description
Feature-request: State-of-art Yolo v4 Detector
- paper: https://arxiv.org/abs/2004.10934
- source code: https://github.com/AlexeyAB/darknet
- cfg-file Yolov4: https://github.com/AlexeyAB/darknet/blob/master/cfg/yolov4.cfg
- weights-file Yolov4: https://drive.google.com/open?id=1cewMfusmPjYWbrnuJRuKhPMwRe_b9PaT
Many other features from Darknet were added previously.
But should be added at least new two features:
- Mish-activation:
float softplus(float x, float threshold = 20) {
if (x > threshold) return x; // too large
else if (x < -threshold) return expf(x); // too small
return logf(expf(x) + 1);
}
float mish_activation(float input) {
const float MISH_THRESHOLD = 20;
output = input * tanh( softplus(input, MISH_THRESHOLD) );
return output;
}
- Eliminate grid sensitivity - by using
scale_x_y=
parameter from[yolo]
layer in cfg-file (by default usescale_x_y=1.0
if the value is not set in cfg file)
we should use:
const float x_tmp = logistic_activate(srcData[box_index + 0]) * scale_x_y - (scale_x_y - 1) / 2;
const float y_tmp = logistic_activate(srcData[box_index + 1]) * scale_x_y - (scale_x_y - 1) / 2;
dstData[box_index + 0] = (x + x_tmp)) / cols;
dstData[box_index + 1] = (y + y_tmp)) / rows;
instead of
opencv/modules/dnn/src/layers/region_layer.cpp
Lines 305 to 306 in 51a42c0
dstData[box_index + 0] = (x + logistic_activate(srcData[box_index + 0])) / cols; | |
dstData[box_index + 1] = (y + logistic_activate(srcData[box_index + 1])) / rows; |
Comparison of detectors on Microsoft COCO dataset and Tesla V100 GPU:
YashasSamaga, tompollok, dkurt, simaiden, otamajakusi and 23 moreYashasSamaga, dont32, take2rohit, pablob2292, wooseokyourself and 3 morepablob2292, halvomez, wooseokyourself, Luxonis-Brandon, Luxonis-Brian and 1 more
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