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Add xyxy2xywhn() #3765

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Jun 25, 2021
Merged

Add xyxy2xywhn() #3765

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2ee1b24
Edit Comments for numpy2torch tensor process
developer0hye Jun 25, 2021
76df386
add xyxy2xywhn
developer0hye Jun 25, 2021
e4aa0a8
add xyxy2xywhn
developer0hye Jun 25, 2021
b77693f
formatting
developer0hye Jun 25, 2021
aabec2f
pass arguments
developer0hye Jun 25, 2021
d335485
edit comment for xyxy2xywhn()
developer0hye Jun 25, 2021
a212f6e
cleanup datasets.py
glenn-jocher Jun 25, 2021
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14 changes: 6 additions & 8 deletions utils/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,8 +23,8 @@
from torch.utils.data import Dataset
from tqdm import tqdm

from utils.general import check_requirements, check_file, check_dataset, xyxy2xywh, xywh2xyxy, xywhn2xyxy, xyn2xy, \
segment2box, segments2boxes, resample_segments, clean_str
from utils.general import check_requirements, check_file, check_dataset, xywh2xyxy, xywhn2xyxy, xyxy2xywhn, \
xyn2xy, segment2box, segments2boxes, resample_segments, clean_str
from utils.torch_utils import torch_distributed_zero_first

# Parameters
Expand Down Expand Up @@ -192,7 +192,7 @@ def __next__(self):
img = letterbox(img0, self.img_size, stride=self.stride)[0]

# Convert
img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB, to 3x416x416
img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB and HWC to CHW
img = np.ascontiguousarray(img)

return path, img, img0, self.cap
Expand Down Expand Up @@ -255,7 +255,7 @@ def __next__(self):
img = letterbox(img0, self.img_size, stride=self.stride)[0]

# Convert
img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB, to 3x416x416
img = img[:, :, ::-1].transpose(2, 0, 1) # BGR to RGB and HWC to CHW
img = np.ascontiguousarray(img)

return img_path, img, img0, None
Expand Down Expand Up @@ -336,7 +336,7 @@ def __next__(self):
img = np.stack(img, 0)

# Convert
img = img[:, :, :, ::-1].transpose(0, 3, 1, 2) # BGR to RGB, to bsx3x416x416
img = img[:, :, :, ::-1].transpose(0, 3, 1, 2) # BGR to RGB and BHWC to BCHW
img = np.ascontiguousarray(img)

return self.sources, img, img0, None
Expand Down Expand Up @@ -552,9 +552,7 @@ def __getitem__(self, index):

nL = len(labels) # number of labels
if nL:
labels[:, 1:5] = xyxy2xywh(labels[:, 1:5]) # convert xyxy to xywh
labels[:, [2, 4]] /= img.shape[0] # normalized height 0-1
labels[:, [1, 3]] /= img.shape[1] # normalized width 0-1
labels[:, 1:5] = xyxy2xywhn(labels[:, 1:5], w=img.shape[1], h=img.shape[0]) # xyxy to xywh normalized

if self.augment:
# flip up-down
Expand Down
10 changes: 10 additions & 0 deletions utils/general.py
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Expand Up @@ -393,6 +393,16 @@ def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
return y


def xyxy2xywhn(x, w=640, h=640):
# Convert nx4 boxes from [x1, y1, x2, y2] to [x, y, w, h] normalized where xy1=top-left, xy2=bottom-right
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
y[:, 0] = ((x[:, 0] + x[:, 2]) / 2) / w # x center
y[:, 1] = ((x[:, 1] + x[:, 3]) / 2) / h # y center
y[:, 2] = (x[:, 2] - x[:, 0]) / w # width
y[:, 3] = (x[:, 3] - x[:, 1]) / h # height
return y


def xyn2xy(x, w=640, h=640, padw=0, padh=0):
# Convert normalized segments into pixel segments, shape (n,2)
y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
Expand Down