v3.0 Release (#725)

* initial commit

* remove yolov3-spp from test.py study

* update study --img range

* update mAP

* cleanup and speed updates

* update README plot

models/common.py

@@ -23,7 +23,7 @@ class Conv(nn.Module):
         super(Conv, self).__init__()
         self.conv = nn.Conv2d(c1, c2, k, s, autopad(k, p), groups=g, bias=False)
         self.bn = nn.BatchNorm2d(c2)
-        self.act = nn.LeakyReLU(0.1, inplace=True) if act else nn.Identity()
+        self.act = nn.Hardswish() if act else nn.Identity()
 
     def forward(self, x):
         return self.act(self.bn(self.conv(x)))

models/yolo.py

@@ -15,10 +15,13 @@ from utils.torch_utils import (
 
 logger = logging.getLogger(__name__)
 
+
 class Detect(nn.Module):
+    stride = None  # strides computed during build
+    export = False  # onnx export
+
     def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
         super(Detect, self).__init__()
-        self.stride = None  # strides computed during build
         self.nc = nc  # number of classes
         self.no = nc + 5  # number of outputs per anchor
         self.nl = len(anchors)  # number of detection layers
@@ -28,7 +31,6 @@ class Detect(nn.Module):
         self.register_buffer('anchors', a)  # shape(nl,na,2)
         self.register_buffer('anchor_grid', a.clone().view(self.nl, 1, -1, 1, 1, 2))  # shape(nl,1,na,1,1,2)
         self.m = nn.ModuleList(nn.Conv2d(x, self.no * self.na, 1) for x in ch)  # output conv
-        self.export = False  # onnx export
 
     def forward(self, x):
         # x = x.copy()  # for profiling