localdet_VOC07_das.cfg

[GLOBAL]
nn_threads  = 4
det_threads = 2
rank_threads= 8
mode        = detection
setmode     = voc
train_sel   = segment
local       = True
tmp_dir     = /local/vdvelden/det1_VOC07_dsift_segment_sl0_tmp
res_dir     = /local/vdvelden/det1_VOC07_dsift_segment_sl0_res
train_set   = segtrainval
test_set    = segtest

[VOC]
imset_path      = VOCdevkit/VOC2007/ImageSets/Main/%s.txt
image_path      = VOCdevkit/VOC2007/JPEGImages/%s.jpg
annotation_path = VOCdevkit/VOC2007/Annotations/%s.xml
gt_object_path  = VOCdevkit/VOC2007/SegmentationObject/%s.png
gt_class_path   = VOCdevkit/VOC2007/SegmentationClass/%s.png
classes         = aeroplane
                  bicycle
                  bird
                  boat
                  bottle
                  bus
                  car
                  cat
                  chair
                  cow
                  diningtable
                  dog
                  horse
                  motorbike
                  person
                  pottedplant
                  sheep
                  sofa
                  train
                  tvmonitor

[TRAIN-DESCRIPTOR]
dtype       = DescriptorUint8
cache_dir   = descriptors
detector    = densesampling
descriptor  = sift
outputFormat = binary
ds_spacing  = 8
ds_scales   = 2.67+4.0+5.33

[TEST-DESCRIPTOR]
dtype       = DescriptorUint8
cache_dir   = descriptors
detector    = densesampling
descriptor  = sift
outputFormat = binary
ds_spacing  = 8
ds_scales   = 2.67+4.0+5.33

[NBNN]
behmo       = False
checks      = 1000

[TEST]
k               = 1
batch_size      = 100
img_pickle_path = batches/%s.pkl

[DETECTION]
method            = single_link
dist              = overlap
hyp_threshold     = nearest
ignore_threshold  = False
hypothesis_metric = bb_exemp_qh
all_det_metrics   = det_random,hyp_det_random,det_qd_exempfg,hyp_det_qd_exempfg,det_becker,det_qd,det_energy,det_wenergy,det_full_qh,det_exemp_qh,det_full_fg,det_full_bg,det_exemp_mean_fg,det_exemp_sum_fg,det_exemp_bg,qs_density,hyp_det_energy,hyp_det_wenergy,hyp_det_full_qh,hyp_det_exemp_qh,hyp_det_full_fg,hyp_det_full_bg,hyp_det_exemp_mean_fg,hyp_det_exemp_sum_fg,hyp_det_exemp_bg
detection_metric  = det_becker
ranking_path      = %s/comp3_det_%s_%s.txt
distances_path    = distances/%s_%s.pkl
knn_path          = knn/%s_%s.pkl
hypotheses_path   = hypotheses/%s_%s.pkl
exemplar_path     = exemplars/%s.npy
quickshift_tree_path = quickshift/%s_%s.pkl
tau               = 1.20
theta_m           = 0.8
theta_p           = 0.0