updates

cfg/yolov3-spp.cfg

@@ -4,9 +4,9 @@
 # subdivisions=1
 # Training
 batch=64
-subdivisions=16
-width=608
-height=608
+subdivisions=8
+width=320
+height=320
 channels=3
 momentum=0.9
 decay=0.0005
@@ -16,7 +16,7 @@ exposure = 1.5
 hue=.1
 
 learning_rate=0.001
-burn_in=1000
+burn_in=366
 max_batches = 500200
 policy=steps
 steps=400000,450000

train.py

@@ -233,8 +233,8 @@ def train(
             pbar.set_description(s)  # print(s)
 
         # Report time
-        dt = (time.time() - t0) / 3600
-        print('%g epochs completed in %.3f hours.' % (epoch - start_epoch + 1, dt))
+        # dt = (time.time() - t0) / 3600
+        # print('%g epochs completed in %.3f hours.' % (epoch - start_epoch + 1, dt))
 
         # Calculate mAP (always test final epoch, skip first 5 if opt.nosave)
         if not (opt.notest or (opt.nosave and epoch < 10)) or epoch == epochs - 1:

utils/gcp.sh

@@ -50,7 +50,7 @@ python3 train.py --nosave --data data/coco_10img.data && mv results.txt results0
 python3 train.py --nosave --data data/coco_100img.data && mv results.txt results0r_100img.txt
 # python3 train.py --nosave --data data/coco_100img.data --transfer && mv results.txt results3_100imgTL.txt
 python3 -c "from utils import utils; utils.plot_results()"
-gsutil cp results*.txt gs://ultralytics
+# gsutil cp results*.txt gs://ultralytics
 gsutil cp results.png gs://ultralytics
 sudo shutdown
 
@@ -92,7 +92,6 @@ python3 test.py --data ../supermarket2/supermarket2.data --weights weights/yolov
 python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls-scalexy_variable_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_variable.cfg --img-size 320 --conf-thres 0.2  # test
 
 
-
 # Debug/Development
 python3 train.py --data data/coco.data --img-size 320 --single-scale --batch-size 64 --accumulate 1 --epochs 1 --evolve --giou
 python3 test.py --weights weights/latest.pt --cfg cfg/yolov3-spp.cfg --img-size 320