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cfg.py 1.54 KB
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# -*- coding: utf-8 -*-
'''
@Time : 2020/05/06 21:05
@Author : Tianxiaomo
@File : Cfg.py
@Noice :
@Modificattion :
@Author :
@Time :
@Detail :
'''
import os
from easydict import EasyDict
_BASE_DIR = os.path.dirname(os.path.abspath(__file__))
Cfg = EasyDict()
Cfg.use_darknet_cfg = True
Cfg.cfgfile = os.path.join(_BASE_DIR, 'cfg', 'yolov4.cfg')
Cfg.batch = 64
Cfg.subdivisions = 16
Cfg.width = 608
Cfg.height = 608
Cfg.channels = 3
Cfg.momentum = 0.949
Cfg.decay = 0.0005
Cfg.angle = 0
Cfg.saturation = 1.5
Cfg.exposure = 1.5
Cfg.hue = .1
Cfg.learning_rate = 0.00261
Cfg.burn_in = 1000
Cfg.max_batches = 500500
Cfg.steps = [400000, 450000]
Cfg.policy = Cfg.steps
Cfg.scales = .1, .1
Cfg.cutmix = 0
Cfg.mosaic = 1
Cfg.letter_box = 0
Cfg.jitter = 0.2
Cfg.classes = 80
Cfg.track = 0
Cfg.w = Cfg.width
Cfg.h = Cfg.height
Cfg.flip = 1
Cfg.blur = 0
Cfg.gaussian = 0
Cfg.boxes = 60 # box num
Cfg.TRAIN_EPOCHS = 300
Cfg.train_label = os.path.join(_BASE_DIR, 'data', 'train.txt')
Cfg.val_label = os.path.join(_BASE_DIR, 'data' ,'val.txt')
Cfg.TRAIN_OPTIMIZER = 'adam'
'''
image_path1 x1,y1,x2,y2,id x1,y1,x2,y2,id x1,y1,x2,y2,id ...
image_path2 x1,y1,x2,y2,id x1,y1,x2,y2,id x1,y1,x2,y2,id ...
...
'''
if Cfg.mosaic and Cfg.cutmix:
Cfg.mixup = 4
elif Cfg.cutmix:
Cfg.mixup = 2
elif Cfg.mosaic:
Cfg.mixup = 3
Cfg.checkpoints = os.path.join(_BASE_DIR, 'checkpoints')
Cfg.TRAIN_TENSORBOARD_DIR = os.path.join(_BASE_DIR, 'log')
Cfg.iou_type = 'iou' # 'giou', 'diou', 'ciou'
Cfg.keep_checkpoint_max = 10
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