Update setup.cfg (#11814)
* Update setup.cfg Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update .pre-commit-config.yaml Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update export.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update downloads.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update yolo.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> --------- Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -310,7 +310,7 @@ class TFDetect(keras.layers.Layer):
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y = tf.concat([xy, wh, tf.sigmoid(y[..., 4:5 + self.nc]), y[..., 5 + self.nc:]], -1)
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z.append(tf.reshape(y, [-1, self.na * ny * nx, self.no]))
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return tf.transpose(x, [0, 2, 1, 3]) if self.training else (tf.concat(z, 1),)
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return tf.transpose(x, [0, 2, 1, 3]) if self.training else (tf.concat(z, 1), )
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@staticmethod
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def _make_grid(nx=20, ny=20):
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@@ -486,7 +486,7 @@ class TFModel:
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iou_thres,
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conf_thres,
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clip_boxes=False)
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return (nms,)
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return (nms, )
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return x # output [1,6300,85] = [xywh, conf, class0, class1, ...]
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# x = x[0] # [x(1,6300,85), ...] to x(6300,85)
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# xywh = x[..., :4] # x(6300,4) boxes
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+4
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@@ -21,8 +21,8 @@ if str(ROOT) not in sys.path:
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if platform.system() != 'Windows':
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ROOT = Path(os.path.relpath(ROOT, Path.cwd())) # relative
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from models.common import *
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from models.experimental import *
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from models.common import * # noqa
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from models.experimental import * # noqa
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from utils.autoanchor import check_anchor_order
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from utils.general import LOGGER, check_version, check_yaml, make_divisible, print_args
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from utils.plots import feature_visualization
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@@ -76,7 +76,7 @@ class Detect(nn.Module):
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y = torch.cat((xy, wh, conf), 4)
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z.append(y.view(bs, self.na * nx * ny, self.no))
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return x if self.training else (torch.cat(z, 1),) if self.export else (torch.cat(z, 1), x)
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return x if self.training else (torch.cat(z, 1), ) if self.export else (torch.cat(z, 1), x)
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def _make_grid(self, nx=20, ny=20, i=0, torch_1_10=check_version(torch.__version__, '1.10.0')):
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d = self.anchors[i].device
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@@ -126,7 +126,7 @@ class BaseModel(nn.Module):
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def _profile_one_layer(self, m, x, dt):
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c = m == self.model[-1] # is final layer, copy input as inplace fix
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o = thop.profile(m, inputs=(x.copy() if c else x,), verbose=False)[0] / 1E9 * 2 if thop else 0 # FLOPs
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o = thop.profile(m, inputs=(x.copy() if c else x, ), verbose=False)[0] / 1E9 * 2 if thop else 0 # FLOPs
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t = time_sync()
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for _ in range(10):
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m(x.copy() if c else x)
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