From fd653eca8a891a5c08fccbe8b37e03d59b83b321 Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Fri, 23 Aug 2019 13:25:27 +0200
Subject: [PATCH] updates

---
 train.py | 40 ++++++++++++++++------------------------
 1 file changed, 16 insertions(+), 24 deletions(-)

diff --git a/train.py b/train.py
index e19d6cbc..7708d065 100644
--- a/train.py
+++ b/train.py
@@ -75,12 +75,14 @@ hyp = {'giou': 1.582,  # giou loss gain
 #        'shear': 0.434}  # image shear (+/- deg)
 
 
-def train(cfg,
-          data,
-          img_size=416,
-          epochs=100,  # 500200 batches at bs 16, 117263 images = 273 epochs
-          batch_size=16,
-          accumulate=4):  # effective bs = batch_size * accumulate = 16 * 4 = 64
+def train():
+    cfg = opt.cfg
+    data = opt.data
+    img_size = opt.img_size
+    epochs = opt.epochs  # 500200 batches at bs 16, 117263 images = 273 epochs
+    batch_size = opt.batch_size
+    accumulate = opt.accumulate  # effective bs = batch_size * accumulate = 16 * 4 = 64
+
     # Initialize
     init_seeds()
     weights = 'weights' + os.sep
@@ -359,16 +361,16 @@ def train(cfg,
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
-    parser.add_argument('--epochs', type=int, default=273, help='number of epochs')
-    parser.add_argument('--batch-size', type=int, default=32, help='batch size')
-    parser.add_argument('--accumulate', type=int, default=2, help='number of batches to accumulate before optimizing')
+    parser.add_argument('--epochs', type=int, default=273)  # 500200 batches at bs 16, 117263 images = 273 epochs
+    parser.add_argument('--batch-size', type=int, default=32)  # effective bs = batch_size * accumulate = 16 * 4 = 64
+    parser.add_argument('--accumulate', type=int, default=2, help='batches to accumulate before optimizing')
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
-    parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
+    parser.add_argument('--data', type=str, default='data/coco.data', help='*.data file path')
     parser.add_argument('--multi-scale', action='store_true', help='train at (1/1.5)x - 1.5x sizes')
     parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
     parser.add_argument('--rect', action='store_true', help='rectangular training')
-    parser.add_argument('--resume', action='store_true', help='resume training flag')
-    parser.add_argument('--transfer', action='store_true', help='transfer learning flag')
+    parser.add_argument('--resume', action='store_true', help='resume training from last.pt')
+    parser.add_argument('--transfer', action='store_true', help='transfer learning')
     parser.add_argument('--nosave', action='store_true', help='only save final checkpoint')
     parser.add_argument('--notest', action='store_true', help='only test final epoch')
     parser.add_argument('--evolve', action='store_true', help='evolve hyperparameters')
@@ -388,12 +390,7 @@ if __name__ == '__main__':
         except:
             pass
 
-        results = train(opt.cfg,
-                        opt.data,
-                        img_size=opt.img_size,
-                        epochs=opt.epochs,
-                        batch_size=opt.batch_size,
-                        accumulate=opt.accumulate)
+        results = train()
 
     else:  # Evolve hyperparameters (optional)
         opt.notest = True  # only test final epoch
@@ -423,12 +420,7 @@ if __name__ == '__main__':
                 hyp[k] = np.clip(hyp[k], v[0], v[1])
 
             # Train mutation
-            results = train(opt.cfg,
-                            opt.data,
-                            img_size=opt.img_size,
-                            epochs=opt.epochs,
-                            batch_size=opt.batch_size,
-                            accumulate=opt.accumulate)
+            results = train()
 
             # Write mutation results
             print_mutation(hyp, results, opt.bucket)