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Update README.md (#272)

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Glenn Jocher 2023-01-12 01:38:42 +01:00 • committed by GitHub
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15 changed files with 74 additions and 72 deletions
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ultralytics/nn/modules.py
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@ -366,7 +366,7 @@ class Concat(nn.Module):
class AutoShape(nn.Module):
# YOLOv5 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMS
# YOLOv8 input-robust model wrapper for passing cv2/np/PIL/torch inputs. Includes preprocessing, inference and NMS
conf = 0.25 # NMS confidence threshold
iou = 0.45 # NMS IoU threshold
agnostic = False # NMS class-agnostic
@ -465,7 +465,7 @@ class AutoShape(nn.Module):
class Detections:
# YOLOv5 detections class for inference results
# YOLOv8 detections class for inference results
def __init__(self, ims, pred, files, times=(0, 0, 0), names=None, shape=None):
super().__init__()
d = pred[0].device # device
@ -572,7 +572,7 @@ class Detections:
return self._run(pprint=True) # print results
def __repr__(self):
return f'YOLOv5 {self.__class__} instance\n' + self.__str__()
return f'YOLOv8 {self.__class__} instance\n' + self.__str__()
class Proto(nn.Module):
@ -603,7 +603,7 @@ class Ensemble(nn.ModuleList):
# heads
class Detect(nn.Module):
# YOLOv5 Detect head for detection models
# YOLOv8 Detect head for detection models
dynamic = False # force grid reconstruction
export = False # export mode
shape = None
@ -650,7 +650,7 @@ class Detect(nn.Module):
class Segment(Detect):
# YOLOv5 Segment head for segmentation models
# YOLOv8 Segment head for segmentation models
def __init__(self, nc=80, nm=32, npr=256, ch=()):
super().__init__(nc, ch)
self.nm = nm # number of masks
@ -673,7 +673,7 @@ class Segment(Detect):
class Classify(nn.Module):
# YOLOv5 classification head, i.e. x(b,c1,20,20) to x(b,c2)
# YOLOv8 classification head, i.e. x(b,c1,20,20) to x(b,c2)
def __init__(self, c1, c2, k=1, s=1, p=None, g=1): # ch_in, ch_out, kernel, stride, padding, groups
super().__init__()
c_ = 1280 # efficientnet_b0 size