Update utils.py

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)