W&B log epoch (#1946)
* W&B log epoch * capitalize * W&B log epoch * capitalize * Update train.py New try using https://docs.wandb.ai/library/log#incremental-logging * Update train.py * Update test.py * Update train.py * Update plots.py * Update train.py * Update train.py * label plot step -1 * update * update * update * update * update * update * Update train.py * Update train.py
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@@ -239,8 +239,8 @@ def test(data,
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if plots:
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confusion_matrix.plot(save_dir=save_dir, names=list(names.values()))
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if wandb and wandb.run:
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wandb.log({"Images": wandb_images})
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wandb.log({"Validation": [wandb.Image(str(f), caption=f.name) for f in sorted(save_dir.glob('test*.jpg'))]})
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val_batches = [wandb.Image(str(f), caption=f.name) for f in sorted(save_dir.glob('test*.jpg'))]
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wandb.log({"Images": wandb_images, "Validation": val_batches}, commit=False)
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# Save JSON
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if save_json and len(jdict):
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@@ -321,7 +321,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
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# tb_writer.add_graph(model, imgs) # add model to tensorboard
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elif plots and ni == 10 and wandb:
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wandb.log({"Mosaics": [wandb.Image(str(x), caption=x.name) for x in save_dir.glob('train*.jpg')
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if x.exists()]})
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if x.exists()]}, commit=False)
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# end batch ------------------------------------------------------------------------------------------------
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# end epoch ----------------------------------------------------------------------------------------------------
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@@ -295,7 +295,7 @@ def plot_labels(labels, save_dir=Path(''), loggers=None):
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# loggers
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for k, v in loggers.items() or {}:
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if k == 'wandb' and v:
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v.log({"Labels": [v.Image(str(x), caption=x.name) for x in save_dir.glob('*labels*.jpg')]})
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v.log({"Labels": [v.Image(str(x), caption=x.name) for x in save_dir.glob('*labels*.jpg')]}, commit=False)
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def plot_evolution(yaml_file='data/hyp.finetune.yaml'): # from utils.plots import *; plot_evolution()
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