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ultralytics 8.0.42 DDP fix and Docs updates (#1065)

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Glenn Jocher 2023-02-20 12:56:20 +01:00 • committed by GitHub
parent f6e393c1d2
commit f2a7a29e53
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33 changed files with 196 additions and 93 deletions
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42
ultralytics/yolo/engine/results.py
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@ -28,13 +28,14 @@ class Results:
"""
def __init__(self, boxes=None, masks=None, probs=None, orig_img=None, names=None) -> None:
def __init__(self, orig_img, path, names, boxes=None, masks=None, probs=None) -> None:
self.orig_img = orig_img
self.orig_shape = orig_img.shape[:2]
self.boxes = Boxes(boxes, self.orig_shape) if boxes is not None else None # native size boxes
self.masks = Masks(masks, self.orig_shape) if masks is not None else None # native size or imgsz masks
self.probs = probs if probs is not None else None
self.names = names
self.path = path
self.comp = ['boxes', 'masks', 'probs']
def pandas(self):
@ -42,7 +43,7 @@ class Results:
# TODO masks.pandas + boxes.pandas + cls.pandas
def __getitem__(self, idx):
r = Results(orig_img=self.orig_img)
r = Results(orig_img=self.orig_img, path=self.path, names=self.names)
for item in self.comp:
if getattr(self, item) is None:
continue
@ -58,7 +59,7 @@ class Results:
self.probs = probs
def cpu(self):
r = Results(orig_img=self.orig_img)
r = Results(orig_img=self.orig_img, path=self.path, names=self.names)
for item in self.comp:
if getattr(self, item) is None:
continue
@ -66,7 +67,7 @@ class Results:
return r
def numpy(self):
r = Results(orig_img=self.orig_img)
r = Results(orig_img=self.orig_img, path=self.path, names=self.names)
for item in self.comp:
if getattr(self, item) is None:
continue
@ -74,7 +75,7 @@ class Results:
return r
def cuda(self):
r = Results(orig_img=self.orig_img)
r = Results(orig_img=self.orig_img, path=self.path, names=self.names)
for item in self.comp:
if getattr(self, item) is None:
continue
@ -82,7 +83,7 @@ class Results:
return r
def to(self, *args, **kwargs):
r = Results(orig_img=self.orig_img)
r = Results(orig_img=self.orig_img, path=self.path, names=self.names)
for item in self.comp:
if getattr(self, item) is None:
continue
@ -123,7 +124,7 @@ class Results:
orig_shape (tuple, optional): Original image size.
""")
def visualize(self, show_conf=True, line_width=None, font_size=None, font='Arial.ttf', pil=False, example='abc'):
def plot(self, show_conf=True, line_width=None, font_size=None, font='Arial.ttf', pil=False, example='abc'):
"""
Plots the given result on an input RGB image. Accepts cv2(numpy) or PIL Image
@ -146,9 +147,9 @@ class Results:
annotator.box_label(d.xyxy.squeeze(), label, color=colors(c, True))
if masks is not None:
im_gpu = torch.as_tensor(img, dtype=torch.float16).permute(2, 0, 1).flip(0).contiguous()
im_gpu = F.resize(im_gpu, masks.data.shape[1:]) / 255
annotator.masks(masks.data, colors=[colors(x, True) for x in boxes.cls], im_gpu=im_gpu)
im = torch.as_tensor(img, dtype=torch.float16, device=masks.data.device).permute(2, 0, 1).flip(0)
im = F.resize(im.contiguous(), masks.data.shape[1:]) / 255
annotator.masks(masks.data, colors=[colors(x, True) for x in boxes.cls], im_gpu=im)
if logits is not None:
top5i = logits.argsort(0, descending=True)[:5].tolist() # top 5 indices
@ -371,24 +372,3 @@ class Masks:
Properties:
segments (list): A list of segments which includes x,y,w,h,label,confidence, and mask of each detection masks.
""")
if __name__ == '__main__':
# test examples
results = Results(boxes=torch.randn((2, 6)), masks=torch.randn((2, 160, 160)), orig_shape=[640, 640])
results = results.cuda()
print('--cuda--pass--')
results = results.cpu()
print('--cpu--pass--')
results = results.to('cuda:0')
print('--to-cuda--pass--')
results = results.to('cpu')
print('--to-cpu--pass--')
results = results.numpy()
print('--numpy--pass--')
# box = Boxes(boxes=torch.randn((2, 6)), orig_shape=[5, 5])
# box = box.cuda()
# box = box.cpu()
# box = box.numpy()
# for b in box:
# print(b)