Update tensorboard logging

test.py

@@ -191,9 +191,9 @@ def test(data,
 
         # Plot images
         if plots and batch_i < 1:
-            f = save_dir / ('test_batch%g_gt.jpg' % batch_i)  # filename
+            f = save_dir / f'test_batch{batch_i}_gt.jpg'  # filename
             plot_images(img, targets, paths, str(f), names)  # ground truth
-            f = save_dir / ('test_batch%g_pred.jpg' % batch_i)
+            f = save_dir / f'test_batch{batch_i}_pred.jpg'
             plot_images(img, output_to_target(output, width, height), paths, str(f), names)  # predictions
 
     # Compute statistics

train.py

@@ -291,10 +291,10 @@ def train(hyp, opt, device, tb_writer=None):
 
                 # Plot
                 if ni < 3:
-                    f = str(log_dir / ('train_batch%g.jpg' % ni))  # filename
+                    f = str(log_dir / f'train_batch{ni}.jpg')  # filename
                     result = plot_images(images=imgs, targets=targets, paths=paths, fname=f)
-                    if tb_writer and result is not None:
-                        tb_writer.add_image(f, result, dataformats='HWC', global_step=epoch)
+                    # if tb_writer and result is not None:
+                    # tb_writer.add_image(f, result, dataformats='HWC', global_step=epoch)
                     # tb_writer.add_graph(model, imgs)  # add model to tensorboard
 
             # end batch ------------------------------------------------------------------------------------------------

utils/general.py

@@ -19,6 +19,7 @@ import numpy as np
 import torch
 import torch.nn as nn
 import yaml
+from PIL import Image
 from scipy.cluster.vq import kmeans
 from scipy.signal import butter, filtfilt
 from tqdm import tqdm
@@ -1096,8 +1097,8 @@ def plot_images(images, targets, paths=None, fname='images.jpg', names=None, max
 
     if fname is not None:
         mosaic = cv2.resize(mosaic, (int(ns * w * 0.5), int(ns * h * 0.5)), interpolation=cv2.INTER_AREA)
-        cv2.imwrite(fname, cv2.cvtColor(mosaic, cv2.COLOR_BGR2RGB))
-
+        # cv2.imwrite(fname, cv2.cvtColor(mosaic, cv2.COLOR_BGR2RGB))  # cv2 save
+        Image.fromarray(mosaic).save(fname)  # PIL save
     return mosaic