Ankle/yolov5_birdproject
1
0 Fork 0
Code Issues Pull Requests Actions 6 Packages Projects Releases Wiki Activity

Update train.py test batch_size (#2148)

Browse Source 
* Update train.py

* Update loss.py
This commit is contained in:
Glenn Jocher authored and GitHub committed 2021-02-06 10:29:32 -08:00
1 parent e9b3de463a
commit 86897e3663
2 files changed
+3 -4
Download Patch File Download Diff File Expand all files Collapse all files

No files matched your search

train.py
+2 -2
View File
@@ -190,7 +190,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
# Process 0 # Process 0
if rank in [-1, 0]: if rank in [-1, 0]:
ema.updates = start_epoch * nb // accumulate # set EMA updates ema.updates = start_epoch * nb // accumulate # set EMA updates
testloader = create_dataloader(test_path, imgsz_test, total_batch_size, gs, opt, # testloader testloader = create_dataloader(test_path, imgsz_test, batch_size * 2, gs, opt, # testloader
hyp=hyp, cache=opt.cache_images and not opt.notest, rect=True, rank=-1, hyp=hyp, cache=opt.cache_images and not opt.notest, rect=True, rank=-1,
world_size=opt.world_size, workers=opt.workers, world_size=opt.world_size, workers=opt.workers,
pad=0.5, prefix=colorstr('val: '))[0] pad=0.5, prefix=colorstr('val: '))[0]
@@ -338,7 +338,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
final_epoch = epoch + 1 == epochs final_epoch = epoch + 1 == epochs
if not opt.notest or final_epoch: # Calculate mAP if not opt.notest or final_epoch: # Calculate mAP
results, maps, times = test.test(opt.data, results, maps, times = test.test(opt.data,
batch_size=total_batch_size, batch_size=batch_size * 2,
imgsz=imgsz_test, imgsz=imgsz_test,
model=ema.ema, model=ema.ema,
single_cls=opt.single_cls, single_cls=opt.single_cls,
utils/loss.py
+1 -2
View File
@@ -105,8 +105,7 @@ class ComputeLoss:
BCEcls, BCEobj = FocalLoss(BCEcls, g), FocalLoss(BCEobj, g) BCEcls, BCEobj = FocalLoss(BCEcls, g), FocalLoss(BCEobj, g)
det = model.module.model[-1] if is_parallel(model) else model.model[-1] # Detect() module det = model.module.model[-1] if is_parallel(model) else model.model[-1] # Detect() module
self.balance = {3: [3.67, 1.0, 0.43], 4: [3.78, 1.0, 0.39, 0.22], 5: [3.88, 1.0, 0.37, 0.17, 0.10]}[det.nl] self.balance = {3: [3.67, 1.0, 0.43], 4: [4.0, 1.0, 0.25, 0.06], 5: [4.0, 1.0, 0.25, 0.06, .02]}[det.nl]
# self.balance = [1.0] * det.nl
self.ssi = (det.stride == 16).nonzero(as_tuple=False).item() # stride 16 index self.ssi = (det.stride == 16).nonzero(as_tuple=False).item() # stride 16 index
self.BCEcls, self.BCEobj, self.gr, self.hyp, self.autobalance = BCEcls, BCEobj, model.gr, h, autobalance self.BCEcls, self.BCEobj, self.gr, self.hyp, self.autobalance = BCEcls, BCEobj, model.gr, h, autobalance
for k in 'na', 'nc', 'nl', 'anchors': for k in 'na', 'nc', 'nl', 'anchors':