From 95c55f2e62782cab68ccab5b426596318298c571 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Fri, 23 Aug 2019 13:41:12 +0200 Subject: [PATCH] updates --- train.py | 22 +--------------------- 1 file changed, 1 insertion(+), 21 deletions(-) diff --git a/train.py b/train.py index 8b859539..2d32ca6b 100644 --- a/train.py +++ b/train.py @@ -34,6 +34,7 @@ except: # 0.161 0.327 0.190 0.193 7.82 1.153 4.062 0.1845 24.28 3.05 20.93 2.842 0.2759 0.001357 -4 0.916 0.000572 # hd 0.438 mAP @ epoch 100 # Hyperparameters (j-series, 50.5 mAP yolov3-320) evolved by @ktian08 https://github.com/ultralytics/yolov3/issues/310 +# Transfer learning edge layers: 0.1 lr0, 0.9 momentum hyp = {'giou': 1.582, # giou loss gain 'xy': 4.688, # xy loss gain 'wh': 0.1857, # wh loss gain @@ -54,27 +55,6 @@ hyp = {'giou': 1.582, # giou loss gain 'shear': 0.5768} # image shear (+/- deg) -# # Hyperparameters (i-series) -# hyp = {'giou': 1.43, # giou loss gain -# 'xy': 4.688, # xy loss gain -# 'wh': 0.1857, # wh loss gain -# 'cls': 11.7, # cls loss gain -# 'cls_pw': 4.81, # cls BCELoss positive_weight -# 'obj': 11.5, # obj loss gain -# 'obj_pw': 1.56, # obj BCELoss positive_weight -# 'iou_t': 0.281, # iou training threshold -# 'lr0': 0.0013, # initial learning rate -# 'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf) -# 'momentum': 0.944, # SGD momentum -# 'weight_decay': 0.000427, # optimizer weight decay -# 'hsv_s': 0.0599, # image HSV-Saturation augmentation (fraction) -# 'hsv_v': 0.142, # image HSV-Value augmentation (fraction) -# 'degrees': 1.03, # image rotation (+/- deg) -# 'translate': 0.0552, # image translation (+/- fraction) -# 'scale': 0.0555, # image scale (+/- gain) -# 'shear': 0.434} # image shear (+/- deg) - - def train(): cfg = opt.cfg data = opt.data