From 50b1bb71be7289ef55fb4f29af01e98854b8d3c9 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 6 Aug 2019 14:38:03 +0200 Subject: [PATCH] updates --- train.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/train.py b/train.py index 9970a252..1277e34a 100644 --- a/train.py +++ b/train.py @@ -61,7 +61,7 @@ hyp = {'giou': 1.43, # giou loss gain 'cls': 11.7, # cls loss gain 'cls_pw': 4.81, # cls BCELoss positive_weight 'obj': 11.5, # obj loss gain - 'obj_pw': 1.0, # obj BCELoss positive_weight + '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) @@ -386,7 +386,7 @@ if __name__ == '__main__': # Clip to limits keys = ['lr0', 'iou_t', 'momentum', 'weight_decay', 'hsv_s', 'hsv_v', 'translate', 'scale'] - limits = [(1e-4, 1e-2), (0.00, 0.70), (0.60, 0.97), (0, 0.001), (0, .9), (0, .9), (0, .9), (0, .9)] + limits = [(1e-4, 1e-2), (0.00, 0.70), (0.60, 0.98), (0, 0.001), (0, .9), (0, .9), (0, .9), (0, .9)] for k, v in zip(keys, limits): hyp[k] = np.clip(hyp[k], v[0], v[1])