Add save_dir to plot_lr_scheduler and plot_labels

data/coco128.yaml

@@ -8,8 +8,8 @@
 
 
 # train and val datasets (image directory or *.txt file with image paths)
-train: ../coco128/images/train2017/
-val: ../coco128/images/train2017/
+train: C:/Users/astoken/projects/yolov5/data/coco/images/train2017
+val: C:/Users/astoken/projects/yolov5/data/coco/images/train2017
 
 # number of classes
 nc: 80

train.py

@@ -196,7 +196,7 @@ def train(hyp):
     c = torch.tensor(labels[:, 0])  # classes
     # cf = torch.bincount(c.long(), minlength=nc) + 1.
     # model._initialize_biases(cf.to(device))
-    plot_labels(labels)
+    plot_labels(labels, save_dir=log_dir)
     tb_writer.add_histogram('classes', c, 0)
 
     # Check anchors

utils/utils.py

@@ -1025,7 +1025,7 @@ def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir='./'):
     plt.xlim(0, epochs)
     plt.ylim(0)
     plt.tight_layout()
-    plt.savefig('LR.png', dpi=200)
+    plt.savefig(os.path.join(save_dir, 'LR.png'), dpi=200)
 
 
 def plot_test_txt():  # from utils.utils import *; plot_test()
@@ -1088,7 +1088,7 @@ 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):
+def plot_labels(labels, save_dir= '.'):
     # plot dataset labels
     c, b = labels[:, 0], labels[:, 1:].transpose()  # classees, boxes
 
@@ -1109,7 +1109,7 @@ def plot_labels(labels):
     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('labels.png', dpi=200)
+    plt.savefig(os.path.join(save_dir,'labels.png'), dpi=200)
 
 
 def plot_evolution_results(hyp):  # from utils.utils import *; plot_evolution_results(hyp)