From 81b31824f550dfd5ba9322a114864d9843de0c75 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Sun, 4 Jul 2021 16:55:08 +0200 Subject: [PATCH] Models `*.yaml` reformat (#3875) --- models/hub/yolov3-spp.yaml | 68 ++++++++++++++--------------- models/hub/yolov3-tiny.yaml | 50 ++++++++++----------- models/hub/yolov3.yaml | 68 ++++++++++++++--------------- models/hub/yolov5-fpn.yaml | 50 ++++++++++----------- models/hub/yolov5-p2.yaml | 4 +- models/hub/yolov5-p6.yaml | 4 +- models/hub/yolov5-p7.yaml | 4 +- models/hub/yolov5-panet.yaml | 60 ++++++++++++------------- models/hub/yolov5l6.yaml | 4 +- models/hub/yolov5m6.yaml | 4 +- models/hub/yolov5s-transformer.yaml | 60 ++++++++++++------------- models/hub/yolov5s6.yaml | 4 +- models/hub/yolov5x6.yaml | 4 +- models/yolo.py | 2 +- models/yolov5l.yaml | 4 +- models/yolov5m.yaml | 4 +- models/yolov5s.yaml | 4 +- models/yolov5x.yaml | 4 +- 18 files changed, 184 insertions(+), 218 deletions(-) diff --git a/models/hub/yolov3-spp.yaml b/models/hub/yolov3-spp.yaml index 38dcc449f0d0..0ca7b7f6577b 100644 --- a/models/hub/yolov3-spp.yaml +++ b/models/hub/yolov3-spp.yaml @@ -1,51 +1,49 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - - [10,13, 16,30, 33,23] # P3/8 - - [30,61, 62,45, 59,119] # P4/16 - - [116,90, 156,198, 373,326] # P5/32 + - [ 10,13, 16,30, 33,23 ] # P3/8 + - [ 30,61, 62,45, 59,119 ] # P4/16 + - [ 116,90, 156,198, 373,326 ] # P5/32 # darknet53 backbone backbone: # [from, number, module, args] - [[-1, 1, Conv, [32, 3, 1]], # 0 - [-1, 1, Conv, [64, 3, 2]], # 1-P1/2 - [-1, 1, Bottleneck, [64]], - [-1, 1, Conv, [128, 3, 2]], # 3-P2/4 - [-1, 2, Bottleneck, [128]], - [-1, 1, Conv, [256, 3, 2]], # 5-P3/8 - [-1, 8, Bottleneck, [256]], - [-1, 1, Conv, [512, 3, 2]], # 7-P4/16 - [-1, 8, Bottleneck, [512]], - [-1, 1, Conv, [1024, 3, 2]], # 9-P5/32 - [-1, 4, Bottleneck, [1024]], # 10 + [ [ -1, 1, Conv, [ 32, 3, 1 ] ], # 0 + [ -1, 1, Conv, [ 64, 3, 2 ] ], # 1-P1/2 + [ -1, 1, Bottleneck, [ 64 ] ], + [ -1, 1, Conv, [ 128, 3, 2 ] ], # 3-P2/4 + [ -1, 2, Bottleneck, [ 128 ] ], + [ -1, 1, Conv, [ 256, 3, 2 ] ], # 5-P3/8 + [ -1, 8, Bottleneck, [ 256 ] ], + [ -1, 1, Conv, [ 512, 3, 2 ] ], # 7-P4/16 + [ -1, 8, Bottleneck, [ 512 ] ], + [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 9-P5/32 + [ -1, 4, Bottleneck, [ 1024 ] ], # 10 ] # YOLOv3-SPP head head: - [[-1, 1, Bottleneck, [1024, False]], - [-1, 1, SPP, [512, [5, 9, 13]]], - [-1, 1, Conv, [1024, 3, 1]], - [-1, 1, Conv, [512, 1, 1]], - [-1, 1, Conv, [1024, 3, 1]], # 15 (P5/32-large) + [ [ -1, 1, Bottleneck, [ 1024, False ] ], + [ -1, 1, SPP, [ 512, [ 5, 9, 13 ] ] ], + [ -1, 1, Conv, [ 1024, 3, 1 ] ], + [ -1, 1, Conv, [ 512, 1, 1 ] ], + [ -1, 1, Conv, [ 1024, 3, 1 ] ], # 15 (P5/32-large) - [-2, 1, Conv, [256, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 8], 1, Concat, [1]], # cat backbone P4 - [-1, 1, Bottleneck, [512, False]], - [-1, 1, Bottleneck, [512, False]], - [-1, 1, Conv, [256, 1, 1]], - [-1, 1, Conv, [512, 3, 1]], # 22 (P4/16-medium) + [ -2, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 8 ], 1, Concat, [ 1 ] ], # cat backbone P4 + [ -1, 1, Bottleneck, [ 512, False ] ], + [ -1, 1, Bottleneck, [ 512, False ] ], + [ -1, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, Conv, [ 512, 3, 1 ] ], # 22 (P4/16-medium) - [-2, 1, Conv, [128, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 6], 1, Concat, [1]], # cat backbone P3 - [-1, 1, Bottleneck, [256, False]], - [-1, 2, Bottleneck, [256, False]], # 27 (P3/8-small) + [ -2, 1, Conv, [ 128, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P3 + [ -1, 1, Bottleneck, [ 256, False ] ], + [ -1, 2, Bottleneck, [ 256, False ] ], # 27 (P3/8-small) - [[27, 22, 15], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5) + [ [ 27, 22, 15 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5) ] diff --git a/models/hub/yolov3-tiny.yaml b/models/hub/yolov3-tiny.yaml index ff7638cad3be..d39a6b1f581c 100644 --- a/models/hub/yolov3-tiny.yaml +++ b/models/hub/yolov3-tiny.yaml @@ -1,41 +1,39 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - - [10,14, 23,27, 37,58] # P4/16 - - [81,82, 135,169, 344,319] # P5/32 + - [ 10,14, 23,27, 37,58 ] # P4/16 + - [ 81,82, 135,169, 344,319 ] # P5/32 # YOLOv3-tiny backbone backbone: # [from, number, module, args] - [[-1, 1, Conv, [16, 3, 1]], # 0 - [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 1-P1/2 - [-1, 1, Conv, [32, 3, 1]], - [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 3-P2/4 - [-1, 1, Conv, [64, 3, 1]], - [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 5-P3/8 - [-1, 1, Conv, [128, 3, 1]], - [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 7-P4/16 - [-1, 1, Conv, [256, 3, 1]], - [-1, 1, nn.MaxPool2d, [2, 2, 0]], # 9-P5/32 - [-1, 1, Conv, [512, 3, 1]], - [-1, 1, nn.ZeroPad2d, [[0, 1, 0, 1]]], # 11 - [-1, 1, nn.MaxPool2d, [2, 1, 0]], # 12 + [ [ -1, 1, Conv, [ 16, 3, 1 ] ], # 0 + [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ], # 1-P1/2 + [ -1, 1, Conv, [ 32, 3, 1 ] ], + [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ], # 3-P2/4 + [ -1, 1, Conv, [ 64, 3, 1 ] ], + [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ], # 5-P3/8 + [ -1, 1, Conv, [ 128, 3, 1 ] ], + [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ], # 7-P4/16 + [ -1, 1, Conv, [ 256, 3, 1 ] ], + [ -1, 1, nn.MaxPool2d, [ 2, 2, 0 ] ], # 9-P5/32 + [ -1, 1, Conv, [ 512, 3, 1 ] ], + [ -1, 1, nn.ZeroPad2d, [ [ 0, 1, 0, 1 ] ] ], # 11 + [ -1, 1, nn.MaxPool2d, [ 2, 1, 0 ] ], # 12 ] # YOLOv3-tiny head head: - [[-1, 1, Conv, [1024, 3, 1]], - [-1, 1, Conv, [256, 1, 1]], - [-1, 1, Conv, [512, 3, 1]], # 15 (P5/32-large) + [ [ -1, 1, Conv, [ 1024, 3, 1 ] ], + [ -1, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, Conv, [ 512, 3, 1 ] ], # 15 (P5/32-large) - [-2, 1, Conv, [128, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 8], 1, Concat, [1]], # cat backbone P4 - [-1, 1, Conv, [256, 3, 1]], # 19 (P4/16-medium) + [ -2, 1, Conv, [ 128, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 8 ], 1, Concat, [ 1 ] ], # cat backbone P4 + [ -1, 1, Conv, [ 256, 3, 1 ] ], # 19 (P4/16-medium) - [[19, 15], 1, Detect, [nc, anchors]], # Detect(P4, P5) + [ [ 19, 15 ], 1, Detect, [ nc, anchors ] ], # Detect(P4, P5) ] diff --git a/models/hub/yolov3.yaml b/models/hub/yolov3.yaml index f2e761355469..09df0d9ef362 100644 --- a/models/hub/yolov3.yaml +++ b/models/hub/yolov3.yaml @@ -1,51 +1,49 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - - [10,13, 16,30, 33,23] # P3/8 - - [30,61, 62,45, 59,119] # P4/16 - - [116,90, 156,198, 373,326] # P5/32 + - [ 10,13, 16,30, 33,23 ] # P3/8 + - [ 30,61, 62,45, 59,119 ] # P4/16 + - [ 116,90, 156,198, 373,326 ] # P5/32 # darknet53 backbone backbone: # [from, number, module, args] - [[-1, 1, Conv, [32, 3, 1]], # 0 - [-1, 1, Conv, [64, 3, 2]], # 1-P1/2 - [-1, 1, Bottleneck, [64]], - [-1, 1, Conv, [128, 3, 2]], # 3-P2/4 - [-1, 2, Bottleneck, [128]], - [-1, 1, Conv, [256, 3, 2]], # 5-P3/8 - [-1, 8, Bottleneck, [256]], - [-1, 1, Conv, [512, 3, 2]], # 7-P4/16 - [-1, 8, Bottleneck, [512]], - [-1, 1, Conv, [1024, 3, 2]], # 9-P5/32 - [-1, 4, Bottleneck, [1024]], # 10 + [ [ -1, 1, Conv, [ 32, 3, 1 ] ], # 0 + [ -1, 1, Conv, [ 64, 3, 2 ] ], # 1-P1/2 + [ -1, 1, Bottleneck, [ 64 ] ], + [ -1, 1, Conv, [ 128, 3, 2 ] ], # 3-P2/4 + [ -1, 2, Bottleneck, [ 128 ] ], + [ -1, 1, Conv, [ 256, 3, 2 ] ], # 5-P3/8 + [ -1, 8, Bottleneck, [ 256 ] ], + [ -1, 1, Conv, [ 512, 3, 2 ] ], # 7-P4/16 + [ -1, 8, Bottleneck, [ 512 ] ], + [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 9-P5/32 + [ -1, 4, Bottleneck, [ 1024 ] ], # 10 ] # YOLOv3 head head: - [[-1, 1, Bottleneck, [1024, False]], - [-1, 1, Conv, [512, [1, 1]]], - [-1, 1, Conv, [1024, 3, 1]], - [-1, 1, Conv, [512, 1, 1]], - [-1, 1, Conv, [1024, 3, 1]], # 15 (P5/32-large) + [ [ -1, 1, Bottleneck, [ 1024, False ] ], + [ -1, 1, Conv, [ 512, [ 1, 1 ] ] ], + [ -1, 1, Conv, [ 1024, 3, 1 ] ], + [ -1, 1, Conv, [ 512, 1, 1 ] ], + [ -1, 1, Conv, [ 1024, 3, 1 ] ], # 15 (P5/32-large) - [-2, 1, Conv, [256, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 8], 1, Concat, [1]], # cat backbone P4 - [-1, 1, Bottleneck, [512, False]], - [-1, 1, Bottleneck, [512, False]], - [-1, 1, Conv, [256, 1, 1]], - [-1, 1, Conv, [512, 3, 1]], # 22 (P4/16-medium) + [ -2, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 8 ], 1, Concat, [ 1 ] ], # cat backbone P4 + [ -1, 1, Bottleneck, [ 512, False ] ], + [ -1, 1, Bottleneck, [ 512, False ] ], + [ -1, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, Conv, [ 512, 3, 1 ] ], # 22 (P4/16-medium) - [-2, 1, Conv, [128, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 6], 1, Concat, [1]], # cat backbone P3 - [-1, 1, Bottleneck, [256, False]], - [-1, 2, Bottleneck, [256, False]], # 27 (P3/8-small) + [ -2, 1, Conv, [ 128, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P3 + [ -1, 1, Bottleneck, [ 256, False ] ], + [ -1, 2, Bottleneck, [ 256, False ] ], # 27 (P3/8-small) - [[27, 22, 15], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5) + [ [ 27, 22, 15 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5) ] diff --git a/models/hub/yolov5-fpn.yaml b/models/hub/yolov5-fpn.yaml index e772bffecbbc..b8b7fc1a23d4 100644 --- a/models/hub/yolov5-fpn.yaml +++ b/models/hub/yolov5-fpn.yaml @@ -1,42 +1,40 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - - [10,13, 16,30, 33,23] # P3/8 - - [30,61, 62,45, 59,119] # P4/16 - - [116,90, 156,198, 373,326] # P5/32 + - [ 10,13, 16,30, 33,23 ] # P3/8 + - [ 30,61, 62,45, 59,119 ] # P4/16 + - [ 116,90, 156,198, 373,326 ] # P5/32 # YOLOv5 backbone backbone: # [from, number, module, args] - [[-1, 1, Focus, [64, 3]], # 0-P1/2 - [-1, 1, Conv, [128, 3, 2]], # 1-P2/4 - [-1, 3, Bottleneck, [128]], - [-1, 1, Conv, [256, 3, 2]], # 3-P3/8 - [-1, 9, BottleneckCSP, [256]], - [-1, 1, Conv, [512, 3, 2]], # 5-P4/16 - [-1, 9, BottleneckCSP, [512]], - [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32 - [-1, 1, SPP, [1024, [5, 9, 13]]], - [-1, 6, BottleneckCSP, [1024]], # 9 + [ [ -1, 1, Focus, [ 64, 3 ] ], # 0-P1/2 + [ -1, 1, Conv, [ 128, 3, 2 ] ], # 1-P2/4 + [ -1, 3, Bottleneck, [ 128 ] ], + [ -1, 1, Conv, [ 256, 3, 2 ] ], # 3-P3/8 + [ -1, 9, BottleneckCSP, [ 256 ] ], + [ -1, 1, Conv, [ 512, 3, 2 ] ], # 5-P4/16 + [ -1, 9, BottleneckCSP, [ 512 ] ], + [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 7-P5/32 + [ -1, 1, SPP, [ 1024, [ 5, 9, 13 ] ] ], + [ -1, 6, BottleneckCSP, [ 1024 ] ], # 9 ] # YOLOv5 FPN head head: - [[-1, 3, BottleneckCSP, [1024, False]], # 10 (P5/32-large) + [ [ -1, 3, BottleneckCSP, [ 1024, False ] ], # 10 (P5/32-large) - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 6], 1, Concat, [1]], # cat backbone P4 - [-1, 1, Conv, [512, 1, 1]], - [-1, 3, BottleneckCSP, [512, False]], # 14 (P4/16-medium) + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P4 + [ -1, 1, Conv, [ 512, 1, 1 ] ], + [ -1, 3, BottleneckCSP, [ 512, False ] ], # 14 (P4/16-medium) - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 4], 1, Concat, [1]], # cat backbone P3 - [-1, 1, Conv, [256, 1, 1]], - [-1, 3, BottleneckCSP, [256, False]], # 18 (P3/8-small) + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 4 ], 1, Concat, [ 1 ] ], # cat backbone P3 + [ -1, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 3, BottleneckCSP, [ 256, False ] ], # 18 (P3/8-small) - [[18, 14, 10], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5) + [ [ 18, 14, 10 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5) ] diff --git a/models/hub/yolov5-p2.yaml b/models/hub/yolov5-p2.yaml index 0633a90fd065..62122363df2d 100644 --- a/models/hub/yolov5-p2.yaml +++ b/models/hub/yolov5-p2.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: 3 # YOLOv5 backbone diff --git a/models/hub/yolov5-p6.yaml b/models/hub/yolov5-p6.yaml index 3728a118f090..c5ef5177f0c8 100644 --- a/models/hub/yolov5-p6.yaml +++ b/models/hub/yolov5-p6.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: 3 # YOLOv5 backbone diff --git a/models/hub/yolov5-p7.yaml b/models/hub/yolov5-p7.yaml index ca8f8492ce0e..505c590ca168 100644 --- a/models/hub/yolov5-p7.yaml +++ b/models/hub/yolov5-p7.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: 3 # YOLOv5 backbone diff --git a/models/hub/yolov5-panet.yaml b/models/hub/yolov5-panet.yaml index 340f95a4dbc9..aee5dab01fa1 100644 --- a/models/hub/yolov5-panet.yaml +++ b/models/hub/yolov5-panet.yaml @@ -1,48 +1,46 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - - [10,13, 16,30, 33,23] # P3/8 - - [30,61, 62,45, 59,119] # P4/16 - - [116,90, 156,198, 373,326] # P5/32 + - [ 10,13, 16,30, 33,23 ] # P3/8 + - [ 30,61, 62,45, 59,119 ] # P4/16 + - [ 116,90, 156,198, 373,326 ] # P5/32 # YOLOv5 backbone backbone: # [from, number, module, args] - [[-1, 1, Focus, [64, 3]], # 0-P1/2 - [-1, 1, Conv, [128, 3, 2]], # 1-P2/4 - [-1, 3, BottleneckCSP, [128]], - [-1, 1, Conv, [256, 3, 2]], # 3-P3/8 - [-1, 9, BottleneckCSP, [256]], - [-1, 1, Conv, [512, 3, 2]], # 5-P4/16 - [-1, 9, BottleneckCSP, [512]], - [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32 - [-1, 1, SPP, [1024, [5, 9, 13]]], - [-1, 3, BottleneckCSP, [1024, False]], # 9 + [ [ -1, 1, Focus, [ 64, 3 ] ], # 0-P1/2 + [ -1, 1, Conv, [ 128, 3, 2 ] ], # 1-P2/4 + [ -1, 3, BottleneckCSP, [ 128 ] ], + [ -1, 1, Conv, [ 256, 3, 2 ] ], # 3-P3/8 + [ -1, 9, BottleneckCSP, [ 256 ] ], + [ -1, 1, Conv, [ 512, 3, 2 ] ], # 5-P4/16 + [ -1, 9, BottleneckCSP, [ 512 ] ], + [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 7-P5/32 + [ -1, 1, SPP, [ 1024, [ 5, 9, 13 ] ] ], + [ -1, 3, BottleneckCSP, [ 1024, False ] ], # 9 ] # YOLOv5 PANet head head: - [[-1, 1, Conv, [512, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 6], 1, Concat, [1]], # cat backbone P4 - [-1, 3, BottleneckCSP, [512, False]], # 13 + [ [ -1, 1, Conv, [ 512, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P4 + [ -1, 3, BottleneckCSP, [ 512, False ] ], # 13 - [-1, 1, Conv, [256, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 4], 1, Concat, [1]], # cat backbone P3 - [-1, 3, BottleneckCSP, [256, False]], # 17 (P3/8-small) + [ -1, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 4 ], 1, Concat, [ 1 ] ], # cat backbone P3 + [ -1, 3, BottleneckCSP, [ 256, False ] ], # 17 (P3/8-small) - [-1, 1, Conv, [256, 3, 2]], - [[-1, 14], 1, Concat, [1]], # cat head P4 - [-1, 3, BottleneckCSP, [512, False]], # 20 (P4/16-medium) + [ -1, 1, Conv, [ 256, 3, 2 ] ], + [ [ -1, 14 ], 1, Concat, [ 1 ] ], # cat head P4 + [ -1, 3, BottleneckCSP, [ 512, False ] ], # 20 (P4/16-medium) - [-1, 1, Conv, [512, 3, 2]], - [[-1, 10], 1, Concat, [1]], # cat head P5 - [-1, 3, BottleneckCSP, [1024, False]], # 23 (P5/32-large) + [ -1, 1, Conv, [ 512, 3, 2 ] ], + [ [ -1, 10 ], 1, Concat, [ 1 ] ], # cat head P5 + [ -1, 3, BottleneckCSP, [ 1024, False ] ], # 23 (P5/32-large) - [[17, 20, 23], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5) + [ [ 17, 20, 23 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5) ] diff --git a/models/hub/yolov5l6.yaml b/models/hub/yolov5l6.yaml index 11298b01f479..91c57da1939e 100644 --- a/models/hub/yolov5l6.yaml +++ b/models/hub/yolov5l6.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - [ 19,27, 44,40, 38,94 ] # P3/8 - [ 96,68, 86,152, 180,137 ] # P4/16 diff --git a/models/hub/yolov5m6.yaml b/models/hub/yolov5m6.yaml index 48afc865593a..4bef2e074a96 100644 --- a/models/hub/yolov5m6.yaml +++ b/models/hub/yolov5m6.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 0.67 # model depth multiple width_multiple: 0.75 # layer channel multiple - -# anchors anchors: - [ 19,27, 44,40, 38,94 ] # P3/8 - [ 96,68, 86,152, 180,137 ] # P4/16 diff --git a/models/hub/yolov5s-transformer.yaml b/models/hub/yolov5s-transformer.yaml index f2d666722b30..8023ba480d24 100644 --- a/models/hub/yolov5s-transformer.yaml +++ b/models/hub/yolov5s-transformer.yaml @@ -1,48 +1,46 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 0.33 # model depth multiple width_multiple: 0.50 # layer channel multiple - -# anchors anchors: - - [10,13, 16,30, 33,23] # P3/8 - - [30,61, 62,45, 59,119] # P4/16 - - [116,90, 156,198, 373,326] # P5/32 + - [ 10,13, 16,30, 33,23 ] # P3/8 + - [ 30,61, 62,45, 59,119 ] # P4/16 + - [ 116,90, 156,198, 373,326 ] # P5/32 # YOLOv5 backbone backbone: # [from, number, module, args] - [[-1, 1, Focus, [64, 3]], # 0-P1/2 - [-1, 1, Conv, [128, 3, 2]], # 1-P2/4 - [-1, 3, C3, [128]], - [-1, 1, Conv, [256, 3, 2]], # 3-P3/8 - [-1, 9, C3, [256]], - [-1, 1, Conv, [512, 3, 2]], # 5-P4/16 - [-1, 9, C3, [512]], - [-1, 1, Conv, [1024, 3, 2]], # 7-P5/32 - [-1, 1, SPP, [1024, [5, 9, 13]]], - [-1, 3, C3TR, [1024, False]], # 9 <-------- C3TR() Transformer module + [ [ -1, 1, Focus, [ 64, 3 ] ], # 0-P1/2 + [ -1, 1, Conv, [ 128, 3, 2 ] ], # 1-P2/4 + [ -1, 3, C3, [ 128 ] ], + [ -1, 1, Conv, [ 256, 3, 2 ] ], # 3-P3/8 + [ -1, 9, C3, [ 256 ] ], + [ -1, 1, Conv, [ 512, 3, 2 ] ], # 5-P4/16 + [ -1, 9, C3, [ 512 ] ], + [ -1, 1, Conv, [ 1024, 3, 2 ] ], # 7-P5/32 + [ -1, 1, SPP, [ 1024, [ 5, 9, 13 ] ] ], + [ -1, 3, C3TR, [ 1024, False ] ], # 9 <-------- C3TR() Transformer module ] # YOLOv5 head head: - [[-1, 1, Conv, [512, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 6], 1, Concat, [1]], # cat backbone P4 - [-1, 3, C3, [512, False]], # 13 + [ [ -1, 1, Conv, [ 512, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 6 ], 1, Concat, [ 1 ] ], # cat backbone P4 + [ -1, 3, C3, [ 512, False ] ], # 13 - [-1, 1, Conv, [256, 1, 1]], - [-1, 1, nn.Upsample, [None, 2, 'nearest']], - [[-1, 4], 1, Concat, [1]], # cat backbone P3 - [-1, 3, C3, [256, False]], # 17 (P3/8-small) + [ -1, 1, Conv, [ 256, 1, 1 ] ], + [ -1, 1, nn.Upsample, [ None, 2, 'nearest' ] ], + [ [ -1, 4 ], 1, Concat, [ 1 ] ], # cat backbone P3 + [ -1, 3, C3, [ 256, False ] ], # 17 (P3/8-small) - [-1, 1, Conv, [256, 3, 2]], - [[-1, 14], 1, Concat, [1]], # cat head P4 - [-1, 3, C3, [512, False]], # 20 (P4/16-medium) + [ -1, 1, Conv, [ 256, 3, 2 ] ], + [ [ -1, 14 ], 1, Concat, [ 1 ] ], # cat head P4 + [ -1, 3, C3, [ 512, False ] ], # 20 (P4/16-medium) - [-1, 1, Conv, [512, 3, 2]], - [[-1, 10], 1, Concat, [1]], # cat head P5 - [-1, 3, C3, [1024, False]], # 23 (P5/32-large) + [ -1, 1, Conv, [ 512, 3, 2 ] ], + [ [ -1, 10 ], 1, Concat, [ 1 ] ], # cat head P5 + [ -1, 3, C3, [ 1024, False ] ], # 23 (P5/32-large) - [[17, 20, 23], 1, Detect, [nc, anchors]], # Detect(P3, P4, P5) + [ [ 17, 20, 23 ], 1, Detect, [ nc, anchors ] ], # Detect(P3, P4, P5) ] diff --git a/models/hub/yolov5s6.yaml b/models/hub/yolov5s6.yaml index 1df577a2cc97..ba1025ec87ad 100644 --- a/models/hub/yolov5s6.yaml +++ b/models/hub/yolov5s6.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 0.33 # model depth multiple width_multiple: 0.50 # layer channel multiple - -# anchors anchors: - [ 19,27, 44,40, 38,94 ] # P3/8 - [ 96,68, 86,152, 180,137 ] # P4/16 diff --git a/models/hub/yolov5x6.yaml b/models/hub/yolov5x6.yaml index 5ebc02124fe7..4fc9c9a119b8 100644 --- a/models/hub/yolov5x6.yaml +++ b/models/hub/yolov5x6.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.33 # model depth multiple width_multiple: 1.25 # layer channel multiple - -# anchors anchors: - [ 19,27, 44,40, 38,94 ] # P3/8 - [ 96,68, 86,152, 180,137 ] # P4/16 diff --git a/models/yolo.py b/models/yolo.py index 4c9456edd687..826590bd9783 100644 --- a/models/yolo.py +++ b/models/yolo.py @@ -154,7 +154,7 @@ def forward_once(self, x, profile=False, feature_vis=False): x = m(x) # run y.append(x if m.i in self.save else None) # save output - + if feature_vis and m.type == 'models.common.SPP': feature_visualization(x, m.type, m.i) diff --git a/models/yolov5l.yaml b/models/yolov5l.yaml index 71ebf86e5791..0c130c1514af 100644 --- a/models/yolov5l.yaml +++ b/models/yolov5l.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.0 # model depth multiple width_multiple: 1.0 # layer channel multiple - -# anchors anchors: - [10,13, 16,30, 33,23] # P3/8 - [30,61, 62,45, 59,119] # P4/16 diff --git a/models/yolov5m.yaml b/models/yolov5m.yaml index 3c749c916246..e477b3433d39 100644 --- a/models/yolov5m.yaml +++ b/models/yolov5m.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 0.67 # model depth multiple width_multiple: 0.75 # layer channel multiple - -# anchors anchors: - [10,13, 16,30, 33,23] # P3/8 - [30,61, 62,45, 59,119] # P4/16 diff --git a/models/yolov5s.yaml b/models/yolov5s.yaml index aca669d60d8b..e85442dc9188 100644 --- a/models/yolov5s.yaml +++ b/models/yolov5s.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 0.33 # model depth multiple width_multiple: 0.50 # layer channel multiple - -# anchors anchors: - [10,13, 16,30, 33,23] # P3/8 - [30,61, 62,45, 59,119] # P4/16 diff --git a/models/yolov5x.yaml b/models/yolov5x.yaml index d3babdf7baf0..c7ca03589ab8 100644 --- a/models/yolov5x.yaml +++ b/models/yolov5x.yaml @@ -1,9 +1,7 @@ -# parameters +# Parameters nc: 80 # number of classes depth_multiple: 1.33 # model depth multiple width_multiple: 1.25 # layer channel multiple - -# anchors anchors: - [10,13, 16,30, 33,23] # P3/8 - [30,61, 62,45, 59,119] # P4/16