example-apps/PDD/pcb-defect-detection/libs/configs/cfgs_res101_fpn_v1.py

   1 # -*- coding: utf-8 -*-
   2 from __future__ import division, print_function, absolute_import
   3 import os
   4 import tensorflow as tf
   5 '''
   6
   7 '''
   8
   9 # ------------------------------------------------
  10 VERSION = 'FPN_Res101_20181201_v1'
  11 NET_NAME = 'resnet_v1_101'
  12 ADD_BOX_IN_TENSORBOARD = True
  13
  14 # ---------------------------------------- System_config
  15 ROOT_PATH = os.path.abspath('../')
  16 print (20*"++--")
  17 print (ROOT_PATH)
  18 GPU_GROUP = "2"
  19 SHOW_TRAIN_INFO_INTE = 10
  20 SMRY_ITER = 100
  21 SAVE_WEIGHTS_INTE = 10000
  22
  23 SUMMARY_PATH = ROOT_PATH + '/output/summary'
  24 TEST_SAVE_PATH = ROOT_PATH + '/tools/test_result'
  25 INFERENCE_IMAGE_PATH = ROOT_PATH + '/tools/inference_image'
  26 INFERENCE_SAVE_PATH = ROOT_PATH + '/tools/inference_results'
  27
  28 if NET_NAME.startswith("resnet"):
  29     weights_name = NET_NAME
  30 elif NET_NAME.startswith("MobilenetV2"):
  31     weights_name = "mobilenet/mobilenet_v2_1.0_224"
  32 else:
  33     raise NotImplementedError
  34
  35 PRETRAINED_CKPT = ROOT_PATH + '/data/pretrained_weights/' + weights_name + '.ckpt'
  36 TRAINED_CKPT = os.path.join(ROOT_PATH, 'output/trained_weights')
  37
  38 EVALUATE_DIR = ROOT_PATH + '/output/evaluate_result_pickle/'
  39 test_annotate_path = '/home/yjr/DataSet/VOC/VOC_test/VOC2007/Annotations'
  40
  41 # ------------------------------------------ Train config
  42 RESTORE_FROM_RPN = False
  43 IS_FILTER_OUTSIDE_BOXES = False
  44 FIXED_BLOCKS = 0  # allow 0~3
  45 USE_07_METRIC = False
  46
  47 RPN_LOCATION_LOSS_WEIGHT = 1.
  48 RPN_CLASSIFICATION_LOSS_WEIGHT = 1.0
  49
  50 FAST_RCNN_LOCATION_LOSS_WEIGHT = 1.0
  51 FAST_RCNN_CLASSIFICATION_LOSS_WEIGHT = 1.0
  52 RPN_SIGMA = 3.0
  53 FASTRCNN_SIGMA = 1.0
  54
  55 MUTILPY_BIAS_GRADIENT = None   # 2.0  # if None, will not multipy
  56 GRADIENT_CLIPPING_BY_NORM = None   # 10.0  if None, will not clip
  57
  58 EPSILON = 1e-5
  59 MOMENTUM = 0.9
  60 LR = 0.001  # 0.001  # 0.0003
  61 DECAY_STEP = [60000, 80000]  # 50000, 70000
  62 MAX_ITERATION = 150000
  63
  64 # -------------------------------------------- Data_preprocess_config
  65 DATASET_NAME = 'pascal'  # 'ship', 'spacenet', 'pascal', 'coco'
  66 PIXEL_MEAN = [123.68, 116.779, 103.939]  # R, G, B. In tf, channel is RGB. In openCV, channel is BGR
  67 IMG_SHORT_SIDE_LEN = 800  # 600  # 600
  68 IMG_MAX_LENGTH = 1200  # 1000  # 1000
  69 CLASS_NUM = 20
  70
  71 # --------------------------------------------- Network_config
  72 BATCH_SIZE = 1
  73 INITIALIZER = tf.random_normal_initializer(mean=0.0, stddev=0.01)
  74 BBOX_INITIALIZER = tf.random_normal_initializer(mean=0.0, stddev=0.001)
  75 WEIGHT_DECAY = 0.00004 if NET_NAME.startswith('Mobilenet') else 0.0001
  76
  77 # ---------------------------------------------Anchor config
  78 USE_CENTER_OFFSET = False
  79
  80 LEVLES = ['P2', 'P3', 'P4', 'P5', 'P6']
  81 BASE_ANCHOR_SIZE_LIST = [32, 64, 128, 256, 512]  # addjust the base anchor size for voc.
  82 ANCHOR_STRIDE_LIST = [4, 8, 16, 32, 64]
  83 ANCHOR_SCALES = [1.0]
  84 ANCHOR_RATIOS = [0.5, 1., 2.0]
  85 ROI_SCALE_FACTORS = [10., 10., 5.0, 5.0]
  86 ANCHOR_SCALE_FACTORS = None
  87
  88 # --------------------------------------------FPN config
  89 SHARE_HEADS = True
  90 KERNEL_SIZE = 3
  91 RPN_IOU_POSITIVE_THRESHOLD = 0.7
  92 RPN_IOU_NEGATIVE_THRESHOLD = 0.3
  93 TRAIN_RPN_CLOOBER_POSITIVES = False
  94
  95 RPN_MINIBATCH_SIZE = 256
  96 RPN_POSITIVE_RATE = 0.5
  97 RPN_NMS_IOU_THRESHOLD = 0.7
  98 RPN_TOP_K_NMS_TRAIN = 12000
  99 RPN_MAXIMUM_PROPOSAL_TARIN = 2000
 100
 101 RPN_TOP_K_NMS_TEST = 6000
 102 RPN_MAXIMUM_PROPOSAL_TEST = 1000
 103
 104 # specific settings for FPN
 105 # FPN_TOP_K_PER_LEVEL_TRAIN = 2000
 106 # FPN_TOP_K_PER_LEVEL_TEST = 1000
 107
 108 # -------------------------------------------Fast-RCNN config
 109 ROI_SIZE = 14
 110 ROI_POOL_KERNEL_SIZE = 2
 111 USE_DROPOUT = False
 112 KEEP_PROB = 1.0
 113 SHOW_SCORE_THRSHOLD = 0.5  # only show in tensorboard
 114
 115 FAST_RCNN_NMS_IOU_THRESHOLD = 0.3  # 0.6
 116 FAST_RCNN_NMS_MAX_BOXES_PER_CLASS = 100
 117 FAST_RCNN_IOU_POSITIVE_THRESHOLD = 0.5
 118 FAST_RCNN_IOU_NEGATIVE_THRESHOLD = 0.0   # 0.1 < IOU < 0.5 is negative
 119 FAST_RCNN_MINIBATCH_SIZE = 512  # if is -1, that is train with OHEM
 120 FAST_RCNN_POSITIVE_RATE = 0.25
 121
 122 ADD_GTBOXES_TO_TRAIN = False
 123
 124
 125