glenn-jocher commited on
Commit
f5da528
1 Parent(s): b35f76e

reformat code

Browse files
.github/workflows/rebase.yml CHANGED
@@ -11,11 +11,11 @@ jobs:
11
  if: github.event.issue.pull_request != '' && contains(github.event.comment.body, '/rebase')
12
  runs-on: ubuntu-latest
13
  steps:
14
- - name: Checkout the latest code
15
- uses: actions/checkout@v2
16
- with:
17
- fetch-depth: 0
18
- - name: Automatic Rebase
19
- uses: cirrus-actions/rebase@1.3.1
20
- env:
21
- GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
11
  if: github.event.issue.pull_request != '' && contains(github.event.comment.body, '/rebase')
12
  runs-on: ubuntu-latest
13
  steps:
14
+ - name: Checkout the latest code
15
+ uses: actions/checkout@v2
16
+ with:
17
+ fetch-depth: 0
18
+ - name: Automatic Rebase
19
+ uses: cirrus-actions/rebase@1.3.1
20
+ env:
21
+ GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
detect.py CHANGED
@@ -13,7 +13,7 @@ from numpy import random
13
  from models.experimental import attempt_load
14
  from utils.datasets import LoadStreams, LoadImages
15
  from utils.general import (
16
- check_img_size, non_max_suppression, apply_classifier, scale_coords,
17
  xyxy2xywh, plot_one_box, strip_optimizer, set_logging)
18
  from utils.torch_utils import select_device, load_classifier, time_synchronized
19
 
 
13
  from models.experimental import attempt_load
14
  from utils.datasets import LoadStreams, LoadImages
15
  from utils.general import (
16
+ check_img_size, non_max_suppression, apply_classifier, scale_coords,
17
  xyxy2xywh, plot_one_box, strip_optimizer, set_logging)
18
  from utils.torch_utils import select_device, load_classifier, time_synchronized
19
 
test.py CHANGED
@@ -13,7 +13,7 @@ from tqdm import tqdm
13
  from models.experimental import attempt_load
14
  from utils.datasets import create_dataloader
15
  from utils.general import (
16
- coco80_to_coco91_class, check_dataset, check_file, check_img_size, compute_loss, non_max_suppression, scale_coords,
17
  xyxy2xywh, clip_coords, plot_images, xywh2xyxy, box_iou, output_to_target, ap_per_class, set_logging)
18
  from utils.torch_utils import select_device, time_synchronized
19
 
 
13
  from models.experimental import attempt_load
14
  from utils.datasets import create_dataloader
15
  from utils.general import (
16
+ coco80_to_coco91_class, check_dataset, check_file, check_img_size, compute_loss, non_max_suppression, scale_coords,
17
  xyxy2xywh, clip_coords, plot_images, xywh2xyxy, box_iou, output_to_target, ap_per_class, set_logging)
18
  from utils.torch_utils import select_device, time_synchronized
19
 
utils/datasets.py CHANGED
@@ -423,7 +423,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
423
  ne += 1 # print('empty labels for image %s' % self.img_files[i]) # file empty
424
  # os.system("rm '%s' '%s'" % (self.img_files[i], self.label_files[i])) # remove
425
 
426
- if rank in [-1,0]:
427
  pbar.desc = 'Scanning labels %s (%g found, %g missing, %g empty, %g duplicate, for %g images)' % (
428
  cache_path, nf, nm, ne, nd, n)
429
  if nf == 0:
 
423
  ne += 1 # print('empty labels for image %s' % self.img_files[i]) # file empty
424
  # os.system("rm '%s' '%s'" % (self.img_files[i], self.label_files[i])) # remove
425
 
426
+ if rank in [-1, 0]:
427
  pbar.desc = 'Scanning labels %s (%g found, %g missing, %g empty, %g duplicate, for %g images)' % (
428
  cache_path, nf, nm, ne, nd, n)
429
  if nf == 0:
utils/torch_utils.py CHANGED
@@ -12,6 +12,7 @@ import torchvision.models as models
12
 
13
  logger = logging.getLogger(__name__)
14
 
 
15
  def init_seeds(seed=0):
16
  torch.manual_seed(seed)
17
 
@@ -43,7 +44,7 @@ def select_device(device='', batch_size=None):
43
  if i == 1:
44
  s = ' ' * len(s)
45
  logger.info("%sdevice%g _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
46
- (s, i, x[i].name, x[i].total_memory / c))
47
  else:
48
  logger.info('Using CPU')
49
 
@@ -144,7 +145,8 @@ def model_info(model, verbose=False):
144
  except:
145
  fs = ''
146
 
147
- logger.info('Model Summary: %g layers, %g parameters, %g gradients%s' % (len(list(model.parameters())), n_p, n_g, fs))
 
148
 
149
 
150
  def load_classifier(name='resnet101', n=2):
 
12
 
13
  logger = logging.getLogger(__name__)
14
 
15
+
16
  def init_seeds(seed=0):
17
  torch.manual_seed(seed)
18
 
 
44
  if i == 1:
45
  s = ' ' * len(s)
46
  logger.info("%sdevice%g _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
47
+ (s, i, x[i].name, x[i].total_memory / c))
48
  else:
49
  logger.info('Using CPU')
50
 
 
145
  except:
146
  fs = ''
147
 
148
+ logger.info(
149
+ 'Model Summary: %g layers, %g parameters, %g gradients%s' % (len(list(model.parameters())), n_p, n_g, fs))
150
 
151
 
152
  def load_classifier(name='resnet101', n=2):