add logistic activate function

taxuezcy · Dec 9, 2020 · ffb6512 · ffb6512
1 parent bdb3ac3
commit ffb6512
Show file tree

Hide file tree

Showing 4 changed files with 87 additions and 68 deletions.
diff --git a/Yolov4/README.md b/Yolov4/README.md
@@ -10,6 +10,7 @@ model|weights
 yolov4|[weights](https://drive.google.com/open?id=1sWNozS0emz7bmQTUWDLvsubLGnCwUiIS)
 yolov4-tiny|[weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-tiny.weights)
 yolov4x-mish|[weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4x-mish.weights)
+yolov4-csp|[weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-csp.weights)
 yolov3|[weights](https://pjreddie.com/media/files/yolov3.weights)
 yolov3-spp|[weights](https://pjreddie.com/media/files/yolov3-spp.weights)
 yolov3-tiny|[weights](https://pjreddie.com/media/files/yolov3-tiny.weights)
@@ -25,9 +26,10 @@ python3 export_onnx.py
 ```
 python3 export_onnx.py --cfg_file cfg/yolov4-tiny.cfg --weights_file yolov4-tiny.weights --output_file yolov4-tiny.onnx --strides 32 16 --neck FPN
 ```
-- export yolov4x-mish onnx
+- export yolov4x-mish, yolov4-csp onnx
 ```
-python3 export_onnx.py --cfg_file cfg/yolov4x-mish.cfg --weights_file yolov4x-mish.weights --output_file yolov4x-mish.onnx --sigmoid
+python3 export_onnx.py --cfg_file cfg/yolov4x-mish.cfg --weights_file yolov4x-mish.weights --output_file yolov4x-mish.onnx
+python3 export_onnx.py --cfg_file cfg/yolov4-csp.cfg --weights_file yolov4-csp.weights --output_file yolov4-csp.onnx
 ```
 - export yolov3, yolov3-spp onnx
 ```

diff --git a/Yolov4/cfg/yolov4-csp.cfg b/Yolov4/cfg/yolov4-csp.cfg
@@ -15,17 +15,19 @@ saturation = 1.5
 exposure = 1.5
 hue=.1
 
-learning_rate=0.00261
+learning_rate=0.001
 burn_in=1000
 max_batches = 500500
 policy=steps
 steps=400000,450000
 scales=.1,.1
 
-#cutmix=1
 mosaic=1
+
 letter_box=1
 
+#optimized_memory=1
+
 #23:104x104 54:52x52 85:26x26 104:13x13 for 416
 
 
@@ -1021,26 +1023,30 @@ size=1
 stride=1
 pad=1
 filters=255
-activation=linear
+activation=logistic
 
 
 [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=80
 num=9
-jitter=.3
+jitter=.1
+scale_x_y = 2.0
+objectness_smooth=0
 ignore_thresh = .7
 truth_thresh = 1
-random=1
-scale_x_y = 1.05
-iou_thresh=0.213
-cls_normalizer=1.0
-iou_normalizer=0.07
+#random=1
+resize=1.5
+iou_thresh=0.2
+iou_normalizer=0.05
+cls_normalizer=0.5
+obj_normalizer=4.0
 iou_loss=ciou
-nms_kind=greedynms
+nms_kind=diounms
 beta_nms=0.6
 new_coords=1
+max_delta=5
 
 [route]
 layers = -4
@@ -1131,26 +1137,30 @@ size=1
 stride=1
 pad=1
 filters=255
-activation=linear
+activation=logistic
 
 
 [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=80
 num=9
-jitter=.3
+jitter=.1
+scale_x_y = 2.0
+objectness_smooth=1
 ignore_thresh = .7
 truth_thresh = 1
-random=1
-scale_x_y = 1.05
-iou_thresh=0.213
-cls_normalizer=1.0
-iou_normalizer=0.07
+#random=1
+resize=1.5
+iou_thresh=0.2
+iou_normalizer=0.05
+cls_normalizer=0.5
+obj_normalizer=1.0
 iou_loss=ciou
-nms_kind=greedynms
+nms_kind=diounms
 beta_nms=0.6
 new_coords=1
+max_delta=5
 
 [route]
 layers = -4
@@ -1241,23 +1251,27 @@ size=1
 stride=1
 pad=1
 filters=255
-activation=linear
+activation=logistic
 
 
 [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=80
 num=9
-jitter=.3
+jitter=.1
+scale_x_y = 2.0
+objectness_smooth=1
 ignore_thresh = .7
 truth_thresh = 1
-random=1
-scale_x_y = 1.05
-iou_thresh=0.213
-cls_normalizer=1.0
-iou_normalizer=0.07
+#random=1
+resize=1.5
+iou_thresh=0.2
+iou_normalizer=0.05
+cls_normalizer=0.5
+obj_normalizer=0.4
 iou_loss=ciou
-nms_kind=greedynms
+nms_kind=diounms
 beta_nms=0.6
 new_coords=1
+max_delta=2
diff --git a/Yolov4/cfg/yolov4x-mish.cfg b/Yolov4/cfg/yolov4x-mish.cfg
@@ -15,7 +15,7 @@ saturation = 1.5
 exposure = 1.5
 hue=.1
 
-learning_rate=0.00261
+learning_rate=0.001
 burn_in=1000
 max_batches = 500500
 policy=steps
@@ -26,6 +26,8 @@ mosaic=1
 
 letter_box=1
 
+#optimized_memory=1
+
 [convolutional]
 batch_normalize=1
 filters=32
@@ -1148,7 +1150,7 @@ size=1
 stride=1
 pad=1
 filters=255
-activation=linear
+activation=logistic
 
 
 [yolo]
@@ -1157,6 +1159,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
 classes=80
 num=9
 jitter=.1
+scale_x_y = 2.0
 objectness_smooth=0
 ignore_thresh = .7
 truth_thresh = 1
@@ -1170,7 +1173,7 @@ iou_loss=ciou
 nms_kind=diounms
 beta_nms=0.6
 new_coords=1
-max_delta=20
+max_delta=5
 
 [route]
 layers = -4
@@ -1277,7 +1280,7 @@ size=1
 stride=1
 pad=1
 filters=255
-activation=linear
+activation=logistic
 
 
 [yolo]
@@ -1286,6 +1289,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
 classes=80
 num=9
 jitter=.1
+scale_x_y = 2.0
 objectness_smooth=1
 ignore_thresh = .7
 truth_thresh = 1
@@ -1299,7 +1303,7 @@ iou_loss=ciou
 nms_kind=diounms
 beta_nms=0.6
 new_coords=1
-max_delta=20
+max_delta=5
 
 [route]
 layers = -4
@@ -1406,7 +1410,7 @@ size=1
 stride=1
 pad=1
 filters=255
-activation=linear
+activation=logistic
 
 
 [yolo]
@@ -1415,6 +1419,7 @@ anchors = 12, 16, 19, 36, 40, 28, 36, 75, 76, 55, 72, 146, 142, 110, 192, 243, 4
 classes=80
 num=9
 jitter=.1
+scale_x_y = 2.0
 objectness_smooth=1
 ignore_thresh = .7
 truth_thresh = 1
@@ -1428,4 +1433,4 @@ iou_loss=ciou
 nms_kind=diounms
 beta_nms=0.6
 new_coords=1
-max_delta=20
+max_delta=2