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Rename img_size to imgsz (#86)

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This commit is contained in:
Glenn Jocher
2022-12-24 00:39:09 +01:00
committed by GitHub
parent ae2443c210
commit 6432afc5f9
25 changed files with 98 additions and 98 deletions
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20
ultralytics/yolo/data/dataloaders/stream_loaders.py
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@ -18,10 +18,10 @@ from ultralytics.yolo.utils.checks import check_requirements
class LoadStreams:
# YOLOv5 streamloader, i.e. `python detect.py --source 'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP streams`
def __init__(self, sources='file.streams', img_size=640, stride=32, auto=True, transforms=None, vid_stride=1):
def __init__(self, sources='file.streams', imgsz=640, stride=32, auto=True, transforms=None, vid_stride=1):
torch.backends.cudnn.benchmark = True # faster for fixed-size inference
self.mode = 'stream'
self.img_size = img_size
self.imgsz = imgsz
self.stride = stride
self.vid_stride = vid_stride # video frame-rate stride
sources = Path(sources).read_text().rsplit() if os.path.isfile(sources) else [sources]
@ -55,7 +55,7 @@ class LoadStreams:
LOGGER.info('') # newline
# check for common shapes
s = np.stack([LetterBox(img_size, auto, stride=stride)(image=x).shape for x in self.imgs])
s = np.stack([LetterBox(imgsz, auto, stride=stride)(image=x).shape for x in self.imgs])
self.rect = np.unique(s, axis=0).shape[0] == 1 # rect inference if all shapes equal
self.auto = auto and self.rect
self.transforms = transforms # optional
@ -92,7 +92,7 @@ class LoadStreams:
if self.transforms:
im = np.stack([self.transforms(x) for x in im0]) # transforms
else:
im = np.stack([LetterBox(self.img_size, self.auto, stride=self.stride)(image=x) for x in im0])
im = np.stack([LetterBox(self.imgsz, self.auto, stride=self.stride)(image=x) for x in im0])
im = im[..., ::-1].transpose((0, 3, 1, 2)) # BGR to RGB, BHWC to BCHW
im = np.ascontiguousarray(im) # contiguous
@ -104,7 +104,7 @@ class LoadStreams:
class LoadScreenshots:
# YOLOv5 screenshot dataloader, i.e. `python detect.py --source "screen 0 100 100 512 256"`
def __init__(self, source, img_size=640, stride=32, auto=True, transforms=None):
def __init__(self, source, imgsz=640, stride=32, auto=True, transforms=None):
# source = [screen_number left top width height] (pixels)
check_requirements('mss')
import mss
@ -117,7 +117,7 @@ class LoadScreenshots:
left, top, width, height = (int(x) for x in params)
elif len(params) == 5:
self.screen, left, top, width, height = (int(x) for x in params)
self.img_size = img_size
self.imgsz = imgsz
self.stride = stride
self.transforms = transforms
self.auto = auto
@ -144,7 +144,7 @@ class LoadScreenshots:
if self.transforms:
im = self.transforms(im0) # transforms
else:
im = LetterBox(self.img_size, self.auto, stride=self.stride)(image=im0)
im = LetterBox(self.imgsz, self.auto, stride=self.stride)(image=im0)
im = im.transpose((2, 0, 1))[::-1] # HWC to CHW, BGR to RGB
im = np.ascontiguousarray(im) # contiguous
self.frame += 1
@ -153,7 +153,7 @@ class LoadScreenshots:
class LoadImages:
# YOLOv5 image/video dataloader, i.e. `python detect.py --source image.jpg/vid.mp4`
def __init__(self, path, img_size=640, stride=32, auto=True, transforms=None, vid_stride=1):
def __init__(self, path, imgsz=640, stride=32, auto=True, transforms=None, vid_stride=1):
if isinstance(path, str) and Path(path).suffix == ".txt": # *.txt file with img/vid/dir on each line
path = Path(path).read_text().rsplit()
files = []
@ -172,7 +172,7 @@ class LoadImages:
videos = [x for x in files if x.split('.')[-1].lower() in VID_FORMATS]
ni, nv = len(images), len(videos)
self.img_size = img_size
self.imgsz = imgsz
self.stride = stride
self.files = images + videos
self.nf = ni + nv # number of files
@ -226,7 +226,7 @@ class LoadImages:
if self.transforms:
im = self.transforms(im0) # transforms
else:
im = LetterBox(self.img_size, self.auto, stride=self.stride)(image=im0)
im = LetterBox(self.imgsz, self.auto, stride=self.stride)(image=im0)
im = im.transpose((2, 0, 1))[::-1] # HWC to CHW, BGR to RGB
im = np.ascontiguousarray(im) # contiguous