File size: 3,473 Bytes
5209465 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 |
# ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (Bin.Xiao@microsoft.com)
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from yacs.config import CfgNode as CN
_C = CN()
_C.OUTPUT_DIR = ''
_C.LOG_DIR = ''
_C.DATA_DIR = ''
_C.GPUS = (0,)
_C.WORKERS = 4
_C.PRINT_FREQ = 20
_C.AUTO_RESUME = False
_C.PIN_MEMORY = True
_C.RANK = 0
# Cudnn related params
_C.CUDNN = CN()
_C.CUDNN.BENCHMARK = True
_C.CUDNN.DETERMINISTIC = False
_C.CUDNN.ENABLED = True
# common params for NETWORK
_C.MODEL = CN()
_C.MODEL.NAME = 'pose_hrnet'
_C.MODEL.INIT_WEIGHTS = True
_C.MODEL.PRETRAINED = ''
_C.MODEL.NUM_JOINTS = 17
_C.MODEL.TAG_PER_JOINT = True
_C.MODEL.TARGET_TYPE = 'gaussian'
_C.MODEL.IMAGE_SIZE = [256, 256] # width * height, ex: 192 * 256
_C.MODEL.HEATMAP_SIZE = [64, 64] # width * height, ex: 24 * 32
_C.MODEL.SIGMA = 2
_C.MODEL.EXTRA = CN(new_allowed=True)
_C.LOSS = CN()
_C.LOSS.USE_OHKM = False
_C.LOSS.TOPK = 8
_C.LOSS.USE_TARGET_WEIGHT = True
_C.LOSS.USE_DIFFERENT_JOINTS_WEIGHT = False
# DATASET related params
_C.DATASET = CN()
_C.DATASET.ROOT = ''
_C.DATASET.DATASET = 'mpii'
_C.DATASET.TRAIN_SET = 'train'
_C.DATASET.TEST_SET = 'valid'
_C.DATASET.DATA_FORMAT = 'jpg'
_C.DATASET.HYBRID_JOINTS_TYPE = ''
_C.DATASET.SELECT_DATA = False
# training data augmentation
_C.DATASET.FLIP = True
_C.DATASET.SCALE_FACTOR = 0.25
_C.DATASET.ROT_FACTOR = 30
_C.DATASET.PROB_HALF_BODY = 0.0
_C.DATASET.NUM_JOINTS_HALF_BODY = 8
_C.DATASET.COLOR_RGB = False
# train
_C.TRAIN = CN()
_C.TRAIN.LR_FACTOR = 0.1
_C.TRAIN.LR_STEP = [90, 110]
_C.TRAIN.LR = 0.001
_C.TRAIN.OPTIMIZER = 'adam'
_C.TRAIN.MOMENTUM = 0.9
_C.TRAIN.WD = 0.0001
_C.TRAIN.NESTEROV = False
_C.TRAIN.GAMMA1 = 0.99
_C.TRAIN.GAMMA2 = 0.0
_C.TRAIN.BEGIN_EPOCH = 0
_C.TRAIN.END_EPOCH = 140
_C.TRAIN.RESUME = False
_C.TRAIN.CHECKPOINT = ''
_C.TRAIN.BATCH_SIZE_PER_GPU = 32
_C.TRAIN.SHUFFLE = True
# testing
_C.TEST = CN()
# size of images for each device
_C.TEST.BATCH_SIZE_PER_GPU = 32
# Test Model Epoch
_C.TEST.FLIP_TEST = False
_C.TEST.POST_PROCESS = False
_C.TEST.SHIFT_HEATMAP = False
_C.TEST.USE_GT_BBOX = False
# nms
_C.TEST.IMAGE_THRE = 0.1
_C.TEST.NMS_THRE = 0.6
_C.TEST.SOFT_NMS = False
_C.TEST.OKS_THRE = 0.5
_C.TEST.IN_VIS_THRE = 0.0
_C.TEST.COCO_BBOX_FILE = ''
_C.TEST.BBOX_THRE = 1.0
_C.TEST.MODEL_FILE = ''
# debug
_C.DEBUG = CN()
_C.DEBUG.DEBUG = False
_C.DEBUG.SAVE_BATCH_IMAGES_GT = False
_C.DEBUG.SAVE_BATCH_IMAGES_PRED = False
_C.DEBUG.SAVE_HEATMAPS_GT = False
_C.DEBUG.SAVE_HEATMAPS_PRED = False
def update_config(cfg, args):
cfg.defrost()
cfg.merge_from_file(args.cfg)
cfg.merge_from_list(args.opts)
if args.modelDir:
cfg.OUTPUT_DIR = args.modelDir
if args.logDir:
cfg.LOG_DIR = args.logDir
if args.dataDir:
cfg.DATA_DIR = args.dataDir
cfg.DATASET.ROOT = os.path.join(
cfg.DATA_DIR, cfg.DATASET.ROOT
)
cfg.MODEL.PRETRAINED = os.path.join(
cfg.DATA_DIR, cfg.MODEL.PRETRAINED
)
if cfg.TEST.MODEL_FILE:
cfg.TEST.MODEL_FILE = os.path.join(
cfg.DATA_DIR, cfg.TEST.MODEL_FILE
)
cfg.freeze()
if __name__ == '__main__':
import sys
with open(sys.argv[1], 'w') as f:
print(_C, file=f)
|