-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathsldet1beckerTUD_VLFsift_das.cfg
50 lines (44 loc) · 1.18 KB
/
sldet1beckerTUD_VLFsift_das.cfg
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
[GLOBAL]
nn_threads = 4
det_threads = 8
mode = detection
setmode = becker
tmp_dir = /local/vdvelden/sldet1beckerTUD_VLFsift_tmp_1
res_dir = scratchdisk/sldet1beckerTUD_VLFsift_res_1
train_set = tudtrain
val_set = tudbval
test_set = tudtest
[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 = None
gt_class_path = VOCdevkit/VOC2007/SegmentationClass/%s.png
classes = motorbike
[TRAIN-DESCRIPTOR]
dtype = VL_DSift
cache_dir = descriptors
ds_spacing = 8
ds_scales = 2.67+4.0+5.33
[TEST-DESCRIPTOR]
dtype = VL_DSift
cache_dir = descriptors
ds_spacing = 8
ds_scales = 2.67+4.0+5.33
[NBNN]
behmo = False
checks = 80
[TEST]
batch_size = 50
img_pickle_path = batches/%d.pkl
[DETECTION]
method = single_link
dist = overlap
hyp_threshold = becker
hypothesis_metric = bb_qh
detection_metric = det_becker
distances_path = distances/%s_%s.pkl
hypotheses_path = hypotheses/%s_%s.pkl
exemplar_path = exemplars/%s.npy
theta_m = 0.8
theta_p = 0.0