mirror of
https://github.com/gaomingqi/Track-Anything.git
synced 2025-12-16 16:37:58 +01:00
101 lines
2.9 KiB
Python
101 lines
2.9 KiB
Python
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"""
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Dumps things to tensorboard and console
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"""
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import os
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import warnings
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import torchvision.transforms as transforms
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from torch.utils.tensorboard import SummaryWriter
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def tensor_to_numpy(image):
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image_np = (image.numpy() * 255).astype('uint8')
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return image_np
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def detach_to_cpu(x):
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return x.detach().cpu()
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def fix_width_trunc(x):
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return ('{:.9s}'.format('{:0.9f}'.format(x)))
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class TensorboardLogger:
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def __init__(self, short_id, id, git_info):
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self.short_id = short_id
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if self.short_id == 'NULL':
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self.short_id = 'DEBUG'
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if id is None:
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self.no_log = True
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warnings.warn('Logging has been disbaled.')
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else:
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self.no_log = False
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self.inv_im_trans = transforms.Normalize(
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mean=[-0.485/0.229, -0.456/0.224, -0.406/0.225],
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std=[1/0.229, 1/0.224, 1/0.225])
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self.inv_seg_trans = transforms.Normalize(
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mean=[-0.5/0.5],
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std=[1/0.5])
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log_path = os.path.join('.', 'logs', '%s' % id)
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self.logger = SummaryWriter(log_path)
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self.log_string('git', git_info)
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def log_scalar(self, tag, x, step):
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if self.no_log:
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warnings.warn('Logging has been disabled.')
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return
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self.logger.add_scalar(tag, x, step)
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def log_metrics(self, l1_tag, l2_tag, val, step, f=None):
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tag = l1_tag + '/' + l2_tag
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text = '{:s} - It {:6d} [{:5s}] [{:13}]: {:s}'.format(self.short_id, step, l1_tag.upper(), l2_tag, fix_width_trunc(val))
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print(text)
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if f is not None:
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f.write(text + '\n')
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f.flush()
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self.log_scalar(tag, val, step)
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def log_im(self, tag, x, step):
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if self.no_log:
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warnings.warn('Logging has been disabled.')
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return
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x = detach_to_cpu(x)
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x = self.inv_im_trans(x)
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x = tensor_to_numpy(x)
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self.logger.add_image(tag, x, step)
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def log_cv2(self, tag, x, step):
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if self.no_log:
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warnings.warn('Logging has been disabled.')
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return
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x = x.transpose((2, 0, 1))
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self.logger.add_image(tag, x, step)
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def log_seg(self, tag, x, step):
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if self.no_log:
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warnings.warn('Logging has been disabled.')
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return
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x = detach_to_cpu(x)
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x = self.inv_seg_trans(x)
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x = tensor_to_numpy(x)
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self.logger.add_image(tag, x, step)
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def log_gray(self, tag, x, step):
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if self.no_log:
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warnings.warn('Logging has been disabled.')
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return
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x = detach_to_cpu(x)
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x = tensor_to_numpy(x)
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self.logger.add_image(tag, x, step)
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def log_string(self, tag, x):
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print(tag, x)
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if self.no_log:
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warnings.warn('Logging has been disabled.')
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return
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self.logger.add_text(tag, x)
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