From 5edb0ec40d596e6b3b0d6fd2fd7663ce7781a17f Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Wed, 12 Jun 2019 11:50:24 +0200
Subject: [PATCH] updates

---
 train.py          | 12 +++++-------
 utils/datasets.py |  1 +
 2 files changed, 6 insertions(+), 7 deletions(-)

diff --git a/train.py b/train.py
index 50d29b5f..9b219254 100644
--- a/train.py
+++ b/train.py
@@ -64,7 +64,7 @@ def train(
         epochs=100,  # 500200 batches at bs 4, 117263 images = 68 epochs
         batch_size=16,
         accumulate=4,  # effective bs = 64 = batch_size * accumulate
-        multi_scale=False,
+        multi_scale=True,
         freeze_backbone=False,
         transfer=False  # Transfer learning (train only YOLO layers)
 ):
@@ -73,12 +73,13 @@ def train(
     latest = weights + 'latest.pt'
     best = weights + 'best.pt'
     device = torch_utils.select_device()
+    torch.backends.cudnn.benchmark = True  # unsuitable for multiscale
 
     if multi_scale:
-        img_size = round((img_size / 32) * 1.5) * 32  # initiate with maximum multi_scale size
+        min_size = round(img_size / 32 / 1.5)
+        max_size = round(img_size / 32 * 1.5)
+        img_size = max_size * 32  # initiate with maximum multi_scale size
         # opt.num_workers = 0  # bug https://github.com/ultralytics/yolov3/issues/174
-    else:
-        torch.backends.cudnn.benchmark = True  # unsuitable for multiscale
 
     # Configure run
     data_dict = parse_data_cfg(data_cfg)
@@ -244,10 +245,7 @@ def train(
 
             # Multi-Scale training (67% - 150%) every 10 batches
             if multi_scale and (i + 1) % 10 == 0:
-                min_size = round(img_size / 32 / 1.5)
-                max_size = round(img_size / 32 * 1.5)
                 dataset.img_size = random.choice(range(min_size, max_size + 1)) * 32
-
                 dataloader = DataLoader(dataset,
                                         batch_size=batch_size,
                                         num_workers=opt.num_workers,
diff --git a/utils/datasets.py b/utils/datasets.py
index c8d23395..6ad6c564 100755
--- a/utils/datasets.py
+++ b/utils/datasets.py
@@ -153,6 +153,7 @@ class LoadImagesAndLabels(Dataset):  # for training/testing
                                 replace('.bmp', '.txt').
                                 replace('.png', '.txt') for x in self.img_files]
 
+        multi_scale = False
         if multi_scale:
             s = img_size / 32
             self.multi_scale = ((np.linspace(0.5, 1.5, nb) * s).round().astype(np.int) * 32)