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Bubbliiiing main #40

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aac4bd6
update
TomatoAndCucumber May 14, 2022
869dbd5
update
TomatoAndCucumber May 14, 2022
153c730
update backbone
TomatoAndCucumber May 16, 2022
bc4386c
commit
TomatoAndCucumber Jun 13, 2022
f7fb500
Merge branch 'main' into bubbliiiing-main
EvethingIsOK Jun 13, 2022
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@TomatoAndCucumber
TomatoAndCucumber committed Jun 13, 2022
commit bc4386c8edd189e14d8a9ead7a0673b46f207242
1 change: 0 additions & 1 deletion VOCdevkit/VOC2007/Annotations/README.md
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1 change: 0 additions & 1 deletion VOCdevkit/VOC2007/JPEGImages/README.md
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2 changes: 1 addition & 1 deletion get_map.py
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Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@
#-------------------------------------------------------#
map_out_path = 'map_out'

image_ids = open(os.path.join(VOCdevkit_path, "VOC2007/ImageSets/Main/test.txt")).read().strip().split()
image_ids = open(os.path.join(VOCdevkit_path, "VOC2007/ImageSets/Main/train.txt")).read().strip().split()

if not os.path.exists(map_out_path):
os.makedirs(map_out_path)
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1 change: 0 additions & 1 deletion logs/README.md
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9 changes: 5 additions & 4 deletions train.py
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Expand Up @@ -416,8 +416,8 @@
# 判断当前batch_size，自适应调整学习率
#-------------------------------------------------------------------#
nbs = 64
lr_limit_max = 1e-3 if optimizer_type == 'adam' else 5e-2
lr_limit_min = 3e-4 if optimizer_type == 'adam' else 5e-4
lr_limit_max = 1e-3 if optimizer_type == ['adam','adamw'] else 5e-2
lr_limit_min = 3e-4 if optimizer_type == ['adam','adamw'] else 5e-4
Init_lr_fit = min(max(batch_size / nbs * Init_lr, lr_limit_min), lr_limit_max)
Min_lr_fit = min(max(batch_size / nbs * Min_lr, lr_limit_min * 1e-2), lr_limit_max * 1e-2)

Expand All @@ -434,6 +434,7 @@
pg1.append(v.weight)
optimizer = {
'adam' : optim.Adam(pg0, Init_lr_fit, betas = (momentum, 0.999)),
'adamw': optim.AdamW(pg0, Init_lr_fit, betas=(momentum, 0.999)),
'sgd' : optim.SGD(pg0, Init_lr_fit, momentum = momentum, nesterov=True)
}[optimizer_type]
optimizer.add_param_group({"params": pg1, "weight_decay": weight_decay})
Expand Down Expand Up @@ -501,8 +502,8 @@
# 判断当前batch_size，自适应调整学习率
#-------------------------------------------------------------------#
nbs = 64
lr_limit_max = 1e-3 if optimizer_type == 'adam' else 5e-2
lr_limit_min = 3e-4 if optimizer_type == 'adam' else 5e-4
lr_limit_max = 1e-3 if optimizer_type == ['adam', 'adamw'] else 5e-2
lr_limit_min = 3e-4 if optimizer_type == ['adam', 'adamw'] else 5e-4
Init_lr_fit = min(max(batch_size / nbs * Init_lr, lr_limit_min), lr_limit_max)
Min_lr_fit = min(max(batch_size / nbs * Min_lr, lr_limit_min * 1e-2), lr_limit_max * 1e-2)
#---------------------------------------#
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8 changes: 4 additions & 4 deletions yolo.py
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Expand Up @@ -25,8 +25,8 @@ class YOLO(object):
# 验证集损失较低不代表mAP较高，仅代表该权值在验证集上泛化性能较好。
# 如果出现shape不匹配，同时要注意训练时的model_path和classes_path参数的修改
#--------------------------------------------------------------------------#
"model_path" : 'model_data/yolov5_s.pth',
"classes_path" : 'model_data/coco_classes.txt',
"model_path" : 'logs\ep1000-loss0.136-val_loss0.149.pth',
"classes_path" : 'model_data/voc_classes.txt',
#---------------------------------------------------------------------#
# anchors_path代表先验框对应的txt文件，一般不修改。
# anchors_mask用于帮助代码找到对应的先验框，一般不修改。
Expand All @@ -36,7 +36,7 @@ class YOLO(object):
#---------------------------------------------------------------------#
# 输入图片的大小，必须为32的倍数。
#---------------------------------------------------------------------#
"input_shape" : [640, 640],
"input_shape" : [224, 224],
#------------------------------------------------------#
# backbone cspdarknet（默认）
# convnext_tiny
Expand All @@ -48,7 +48,7 @@ class YOLO(object):
# 所使用的YoloV5的版本。s、m、l、x
# 在除cspdarknet的其它主干中仅影响panet的大小
#------------------------------------------------------#
"phi" : 's',
"phi" : 'l',
#---------------------------------------------------------------------#
# 只有得分大于置信度的预测框会被保留下来
#---------------------------------------------------------------------#
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