From c654d18f0015c396fb01b0a89fe588831e07ae9b Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Wed, 8 Jul 2020 16:11:22 -0700 Subject: [PATCH] Update utils.py --- utils/utils.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/utils/utils.py b/utils/utils.py index 35be9ea..d9d8eb8 100755 --- a/utils/utils.py +++ b/utils/utils.py @@ -1034,7 +1034,7 @@ def plot_images(images, targets, paths=None, fname='images.jpg', names=None, max return mosaic -def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir='./'): +def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir=''): # Plot LR simulating training for full epochs optimizer, scheduler = copy(optimizer), copy(scheduler) # do not modify originals y = [] @@ -1048,7 +1048,7 @@ def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir='./'): plt.xlim(0, epochs) plt.ylim(0) plt.tight_layout() - plt.savefig(os.path.join(save_dir, 'LR.png'), dpi=200) + plt.savefig(Path(save_dir) / 'LR.png', dpi=200) def plot_test_txt(): # from utils.utils import *; plot_test() @@ -1113,7 +1113,7 @@ def plot_study_txt(f='study.txt', x=None): # from utils.utils import *; plot_st plt.savefig(f.replace('.txt', '.png'), dpi=200) -def plot_labels(labels, save_dir= '.'): +def plot_labels(labels, save_dir= ''): # plot dataset labels c, b = labels[:, 0], labels[:, 1:].transpose() # classees, boxes @@ -1134,7 +1134,7 @@ def plot_labels(labels, save_dir= '.'): ax[2].scatter(b[2], b[3], c=hist2d(b[2], b[3], 90), cmap='jet') ax[2].set_xlabel('width') ax[2].set_ylabel('height') - plt.savefig(os.path.join(save_dir,'labels.png'), dpi=200) + plt.savefig(Path(save_dir) / 'labels.png', dpi=200) plt.close() @@ -1180,7 +1180,7 @@ def plot_results_overlay(start=0, stop=0): # from utils.utils import *; plot_re fig.savefig(f.replace('.txt', '.png'), dpi=200) -def plot_results(start=0, stop=0, bucket='', id=(), labels=(), save_dir= '.'): # from utils.utils import *; plot_results() +def plot_results(start=0, stop=0, bucket='', id=(), labels=(), save_dir= ''): # from utils.utils import *; plot_results() # Plot training 'results*.txt' as seen in https://github.com/ultralytics/yolov5#reproduce-our-training fig, ax = plt.subplots(2, 5, figsize=(12, 6)) ax = ax.ravel() @@ -1190,7 +1190,7 @@ def plot_results(start=0, stop=0, bucket='', id=(), labels=(), save_dir= '.'): os.system('rm -rf storage.googleapis.com') files = ['https://storage.googleapis.com/%s/results%g.txt' % (bucket, x) for x in id] else: - files = glob.glob(os.path.join(save_dir,'results*.txt')) + glob.glob('../../Downloads/results*.txt') + files = glob.glob(str(Path(save_dir) / 'results*.txt')) + glob.glob('../../Downloads/results*.txt') for fi, f in enumerate(files): try: results = np.loadtxt(f, usecols=[2, 3, 4, 8, 9, 12, 13, 14, 10, 11], ndmin=2).T @@ -1211,4 +1211,4 @@ def plot_results(start=0, stop=0, bucket='', id=(), labels=(), save_dir= '.'): fig.tight_layout() ax[1].legend() - fig.savefig('results.png', dpi=200) + fig.savefig(Path(save_dir) / 'results.png', dpi=200)