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Resume with custom anchors fix #2361

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merged 2 commits into from
Mar 4, 2021
Merged

Resume with custom anchors fix #2361

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e8d7954
Resume with custom anchors fix
glenn-jocher Mar 4, 2021
5f9d6a6
Update train.py
glenn-jocher Mar 4, 2021
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7 changes: 3 additions & 4 deletions train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,10 +75,8 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
with torch_distributed_zero_first(rank):
attempt_download(weights) # download if not found locally
ckpt = torch.load(weights, map_location=device) # load checkpoint
if hyp.get('anchors'):
ckpt['model'].yaml['anchors'] = round(hyp['anchors']) # force autoanchor
model = Model(opt.cfg or ckpt['model'].yaml, ch=3, nc=nc).to(device) # create
exclude = ['anchor'] if opt.cfg or hyp.get('anchors') else [] # exclude keys
model = Model(opt.cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
exclude = ['anchor'] if (opt.cfg or hyp.get('anchors')) and not opt.resume else [] # exclude keys
state_dict = ckpt['model'].float().state_dict() # to FP32
state_dict = intersect_dicts(state_dict, model.state_dict(), exclude=exclude) # intersect
model.load_state_dict(state_dict, strict=False) # load
Expand Down Expand Up @@ -216,6 +214,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
# Anchors
if not opt.noautoanchor:
check_anchors(dataset, model=model, thr=hyp['anchor_t'], imgsz=imgsz)
model.half().float() # pre-reduce anchor precision

# Model parameters
hyp['box'] *= 3. / nl # scale to layers
Expand Down