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PyTorch Hub model.save() increment as runs/hub/exp (#2684) 

* PyTorch Hub model.save() increment as runs/hub/exp

This chane will align PyTorch Hub results saving with the existing unified results saving directory structure of

runs/
  /train
  /detect
  /test
  /hub
    /exp
    /exp2
    ...

* cleanup
This commit is contained in:
Glenn Jocher 2021-04-02 11:55:10 +02:00 committed by GitHub
parent 514ebcdf33
commit 2af059c0d8
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 7 additions and 6 deletions
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13
models/common.py
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@ -11,7 +11,7 @@ from PIL import Image
from torch.cuda import amp from torch.cuda import amp
from utils.datasets import letterbox from utils.datasets import letterbox
from utils.general import non_max_suppression, make_divisible, scale_coords, xyxy2xywh from utils.general import non_max_suppression, make_divisible, scale_coords, increment_path, xyxy2xywh
from utils.plots import color_list, plot_one_box from utils.plots import color_list, plot_one_box
from utils.torch_utils import time_synchronized from utils.torch_utils import time_synchronized
@ -324,9 +324,9 @@ class Detections:
if show: if show:
img.show(self.files[i]) # show img.show(self.files[i]) # show
if save: if save:
f = Path(save_dir) / self.files[i] f = self.files[i]
img.save(f) # save img.save(Path(save_dir) / f) # save
print(f"{'Saving' * (i == 0)} {f},", end='' if i < self.n - 1 else ' done.\n') print(f"{'Saved' * (i == 0)} {f}", end=',' if i < self.n - 1 else f' to {save_dir}\n')
if render: if render:
self.imgs[i] = np.asarray(img) self.imgs[i] = np.asarray(img)
@ -337,8 +337,9 @@ class Detections:
def show(self): def show(self):
self.display(show=True) # show results self.display(show=True) # show results
def save(self, save_dir='results/'): def save(self, save_dir='runs/hub/exp'):
Path(save_dir).mkdir(exist_ok=True) save_dir = increment_path(save_dir, exist_ok=save_dir != 'runs/hub/exp') # increment save_dir
Path(save_dir).mkdir(parents=True, exist_ok=True)
self.display(save=True, save_dir=save_dir) # save results self.display(save=True, save_dir=save_dir) # save results
def render(self): def render(self):