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Can anyone explain the following code for training Yolov5 (training.py)

Can anyone explain the following code for training Yolov5 (training.py)

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Can anyone explain the following code for training Yolov5 (training.py)

Thank you so much

parser.add_argument('--entity', default=None, help='W&B: Entity') parser.add_argument(' --upload_dataset', nargs='?', const=True, default=False, help="W&B: Upload data, "val" option') parser.add_argument(' --bbox_interval', type=int, default=-1, help='W&B: Set bounding-box image logging interval') parser.add_argument('--artifact_alias', type=str, default='latest', help='W&B: Version of dataset artifact to use') opt = parser.parse_known_args()[0] if known else parser.parse_args() return opt
Transcribed Image Text:parser.add_argument('--entity', default=None, help='W&B: Entity') parser.add_argument(' --upload_dataset', nargs='?', const=True, default=False, help="W&B: Upload data, "val" option') parser.add_argument(' --bbox_interval', type=int, default=-1, help='W&B: Set bounding-box image logging interval') parser.add_argument('--artifact_alias', type=str, default='latest', help='W&B: Version of dataset artifact to use') opt = parser.parse_known_args()[0] if known else parser.parse_args() return opt
def parse_opt(known=False): parser = argparse.ArgumentParser() parser.add_argument('--weights', type=str, default=ROOT / 'yolov5s.pt', help='initial weights path') parser.add_argument(' --cfg', type=str, default='', help='model.yaml path') parser.add_argument(' --data', type=str, default=R0OT / 'data/my_yaml.yaml', help='dataset.yaml path') parser.add_argument('--hyp', type=str, default=ROOT / 'data/hyps/hyp.scratch.yaml', help='hyperparameters path') parser.add_argument(' --epochs', type=int, default=300) parser.add_argument('--batch-size', type=int, default=8, help='total batch size for all GPUS, -1 for autobatch')### parser.add_argument(' --imgsz', '--img', '--img-size', type=int, default=640, help='train, val image size (pixels)') parser.add_argument(' --rect', action='store_true', help='rectangular training') parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training') parser.add_argument('--nosave', action='store_true', help='only save final checkpoint') parser.add_argument('--noval', action='store_true', help='only validate final epoch') parser.add_argument(' --noautoanchor', action='store_true', help='disable autoanchor check') parser.add_argument('--evolve', type=int, nargs='?', const=300, help='evolve hyperparameters for x generations') parser.add_argument('--bucket', type=str, default='', help='gsutil bucket') parser.add_argument('--cache', type=str, nargs='?', const='ram', help='--cache images in "ram" (default) or "disk"') parser.add_argument(' parser.add_argument( parser.add_argument(' parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class') parser.add_argument(' --adam', action='store_true', help='use torch.optim.Adam() optimizer') parser.add_argument(' parser.add_argument('--workers', type=int, default=2, help='max dataloader workers (per RANK in DDP mode)')### parser.add_argument('--project', default=R00T / 'runs/train', help='save to project/name') parser.add_argument('--name', default='exp', help='save to project/name') parser.add_argument(' --exist-ok', action='store_true', help='existing project/name ok, do not increment') parser.add_argument('--quad', action='store_true', help='quad dataloader') parser.add_argument('--linear-lr', action='store_true', help='linear LR') parser.add_argument(' --label- Smoothing', type=float, default=0.0, help='Label smoothing epsilon') parser.add_argument(' --patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)') parser.add_argument( parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)') parser.add_argument(' --local_rank', type=int, default=-1, help='DDP parameter, do not modify') -image-weights', action='store_true', help='use weighted image selection for training') -device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu') -multi-scale', action='store_true', help='vary img-size +/- 50%%') -sync-bn', action='store_true', help='use syncBatchNorm, only available in DDP mode') -freeze', type=int, default=0, help='Number of layers to freeze. backbone=10, all=24')
Transcribed Image Text:def parse_opt(known=False): parser = argparse.ArgumentParser() parser.add_argument('--weights', type=str, default=ROOT / 'yolov5s.pt', help='initial weights path') parser.add_argument(' --cfg', type=str, default='', help='model.yaml path') parser.add_argument(' --data', type=str, default=R0OT / 'data/my_yaml.yaml', help='dataset.yaml path') parser.add_argument('--hyp', type=str, default=ROOT / 'data/hyps/hyp.scratch.yaml', help='hyperparameters path') parser.add_argument(' --epochs', type=int, default=300) parser.add_argument('--batch-size', type=int, default=8, help='total batch size for all GPUS, -1 for autobatch')### parser.add_argument(' --imgsz', '--img', '--img-size', type=int, default=640, help='train, val image size (pixels)') parser.add_argument(' --rect', action='store_true', help='rectangular training') parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training') parser.add_argument('--nosave', action='store_true', help='only save final checkpoint') parser.add_argument('--noval', action='store_true', help='only validate final epoch') parser.add_argument(' --noautoanchor', action='store_true', help='disable autoanchor check') parser.add_argument('--evolve', type=int, nargs='?', const=300, help='evolve hyperparameters for x generations') parser.add_argument('--bucket', type=str, default='', help='gsutil bucket') parser.add_argument('--cache', type=str, nargs='?', const='ram', help='--cache images in "ram" (default) or "disk"') parser.add_argument(' parser.add_argument( parser.add_argument(' parser.add_argument('--single-cls', action='store_true', help='train multi-class data as single-class') parser.add_argument(' --adam', action='store_true', help='use torch.optim.Adam() optimizer') parser.add_argument(' parser.add_argument('--workers', type=int, default=2, help='max dataloader workers (per RANK in DDP mode)')### parser.add_argument('--project', default=R00T / 'runs/train', help='save to project/name') parser.add_argument('--name', default='exp', help='save to project/name') parser.add_argument(' --exist-ok', action='store_true', help='existing project/name ok, do not increment') parser.add_argument('--quad', action='store_true', help='quad dataloader') parser.add_argument('--linear-lr', action='store_true', help='linear LR') parser.add_argument(' --label- Smoothing', type=float, default=0.0, help='Label smoothing epsilon') parser.add_argument(' --patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)') parser.add_argument( parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)') parser.add_argument(' --local_rank', type=int, default=-1, help='DDP parameter, do not modify') -image-weights', action='store_true', help='use weighted image selection for training') -device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu') -multi-scale', action='store_true', help='vary img-size +/- 50%%') -sync-bn', action='store_true', help='use syncBatchNorm, only available in DDP mode') -freeze', type=int, default=0, help='Number of layers to freeze. backbone=10, all=24')
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