updates

data/coco_100img.data

@@ -1,6 +1,6 @@
 classes=80
-train=../coco/coco_100img.txt
-valid=../coco/coco_100img.txt
+train=./data/coco_100img.txt
+valid=./data/coco_100img.txt
 names=data/coco.names
 backup=backup/
 eval=coco

data/coco_10img.data

@@ -1,6 +1,6 @@
 classes=80
-train=../coco/coco_10img.txt
-valid=../coco/coco_10img.txt
+train=./data/coco_10img.txt
+valid=./data/coco_10img.txt
 names=data/coco.names
 backup=backup/
 eval=coco

data/coco_1cls.data

@@ -1,6 +1,6 @@
-classes=80
-train=../coco/coco_1cls.txt
-valid=../coco/coco_1cls.txt
+classes=1
+train=./data/coco_1cls.txt
+valid=./data/coco_1cls.txt
 names=data/coco.names
 backup=backup/
 eval=coco

data/coco_1img.data

@@ -1,6 +1,6 @@
 classes=80
-train=../coco/coco_1img.txt
-valid=../coco/coco_1img.txt
+train=./data/coco_1img.txt
+valid=./data/coco_1img.txt
 names=data/coco.names
 backup=backup/
 eval=coco

train.py

@@ -33,7 +33,7 @@ def train(
         img_size = 608  # initiate with maximum multi_scale size
         num_workers = 0  # bug https://github.com/ultralytics/yolov3/issues/174
     else:
-        pass  # torch.backends.cudnn.benchmark = True  # unsuitable for multiscale
+        torch.backends.cudnn.benchmark = True  # unsuitable for multiscale
 
     # Configure run
     train_path = parse_data_cfg(data_cfg)['train']