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改进项目结构

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sunyg
2025-03-14 15:44:41 +08:00
parent 8478b4a102
commit 9e79fb6a6d
95 changed files with 13745 additions and 64 deletions
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yolov5/train.py
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@ -409,7 +409,7 @@ def train(hyp, opt, device, callbacks):
imgs = nn.functional.interpolate(imgs, size=ns, mode="bilinear", align_corners=False)
# Forward
with torch.amp.autocast(device_type='cuda',enabled=amp):
with torch.cuda.amp.autocast(amp):
pred = model(imgs) # forward
loss, loss_items = compute_loss(pred, targets.to(device)) # loss scaled by batch_size
if RANK != -1:
@ -566,7 +566,7 @@ 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=ROOT / "data/5t5.yaml", help="dataset.yaml path")
parser.add_argument("--data", type=str, default=ROOT / "data/coco128.yaml", help="dataset.yaml path")
parser.add_argument("--hyp", type=str, default=ROOT / "data/hyps/hyp.scratch-low.yaml", help="hyperparameters path")
parser.add_argument("--epochs", type=int, default=100, help="total training epochs")
parser.add_argument("--batch-size", type=int, default=16, help="total batch size for all GPUs, -1 for autobatch")