Update datasets.py comments (#5088)
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@ -155,7 +155,8 @@ class _RepeatSampler(object):
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yield from iter(self.sampler)
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class LoadImages: # for inference
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class LoadImages:
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# YOLOv5 image/video dataloader, i.e. `python detect.py --source image.jpg/vid.mp4`
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def __init__(self, path, img_size=640, stride=32, auto=True):
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p = str(Path(path).resolve()) # os-agnostic absolute path
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if '*' in p:
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@ -237,6 +238,7 @@ class LoadImages: # for inference
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class LoadWebcam: # for inference
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# YOLOv5 local webcam dataloader, i.e. `python detect.py --source 0`
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def __init__(self, pipe='0', img_size=640, stride=32):
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self.img_size = img_size
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self.stride = stride
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@ -277,7 +279,8 @@ class LoadWebcam: # for inference
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return 0
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class LoadStreams: # multiple IP or RTSP cameras
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class LoadStreams:
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# YOLOv5 streamloader, i.e. `python detect.py --source 'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP streams`
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def __init__(self, sources='streams.txt', img_size=640, stride=32, auto=True):
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self.mode = 'stream'
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self.img_size = img_size
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@ -365,7 +368,8 @@ def img2label_paths(img_paths):
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return [sb.join(x.rsplit(sa, 1)).rsplit('.', 1)[0] + '.txt' for x in img_paths]
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class LoadImagesAndLabels(Dataset): # for training/testing
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class LoadImagesAndLabels(Dataset):
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# YOLOv5 train_loader/val_loader, loads images and labels for training and validation
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cache_version = 0.5 # dataset labels *.cache version
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def __init__(self, path, img_size=640, batch_size=16, augment=False, hyp=None, rect=False, image_weights=False,
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@ -659,8 +663,7 @@ def load_image(self, i):
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def load_mosaic(self, index):
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# loads images in a 4-mosaic
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# YOLOv5 4-mosaic loader. Loads 1 image + 3 random images into a 4-image mosaic
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labels4, segments4 = [], []
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s = self.img_size
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yc, xc = [int(random.uniform(-x, 2 * s + x)) for x in self.mosaic_border] # mosaic center x, y
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@ -717,8 +720,7 @@ def load_mosaic(self, index):
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def load_mosaic9(self, index):
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# loads images in a 9-mosaic
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# YOLOv5 9-mosaic loader. Loads 1 image + 8 random images into a 9-image mosaic
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labels9, segments9 = [], []
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s = self.img_size
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indices = [index] + random.choices(self.indices, k=8) # 8 additional image indices
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