def load_gt_roidb(image_set, year, root_path, devkit_path, flip=False):
voc = PascalVOC(image_set, year, root_path, devkit_path)
gt_roidb = voc.gt_roidb()
if flip:
gt_roidb = voc.append_flipped_images(gt_roidb)
prepare_roidb(voc, gt_roidb)
return voc, gt_roidb
def load_gt_roidb_from_list(dataset_name, list_file, dataset_root, outdata_path, flip=False):
voc = DetectionList(dataset_name, list_file, dataset_root, outdata_path)
gt_roidb = voc.gt_roidb()
if flip:
gt_roidb = voc.append_flipped_images(gt_roidb)
prepare_roidb(voc, gt_roidb)
return voc, gt_roidb
def load_ss_roidb(image_set, year, root_path, devkit_path, flip=False):
voc = PascalVOC(image_set, year, root_path, devkit_path)
gt_roidb = voc.gt_roidb()
ss_roidb = voc.selective_search_roidb(gt_roidb)
if flip:
ss_roidb = voc.append_flipped_images(ss_roidb)
prepare_roidb(voc, ss_roidb)
means, stds = add_bbox_regression_targets(ss_roidb)
return voc, ss_roidb, means, stds
import os
from helper.dataset import pascal_voc
from helper.processing import roidb
from rcnn import data_iter
# test flip
devkit_path = os.path.join(os.path.expanduser('~'), 'Dataset', 'VOCdevkit')
voc = pascal_voc.PascalVOC('trainval', '2007', devkit_path)
gt_roidb = voc.gt_roidb()
ss_roidb = voc.selective_search_roidb(gt_roidb)
ss_roidb = voc.append_flipped_images(ss_roidb)
roidb.prepare_roidb(voc, ss_roidb)
means, stds = roidb.add_bbox_regression_targets(ss_roidb)
roi_iter = data_iter.ROIIter(ss_roidb, shuffle=True)
for j in range(0, 20):
print j
for databatch in roi_iter:
i = 0
roi_iter.reset()
def load_test_rpn_roidb(image_set, year, root_path, devkit_path):
voc = PascalVOC(image_set, year, root_path, devkit_path)
gt_roidb = voc.gt_roidb()
rpn_roidb = voc.rpn_roidb(gt_roidb)
prepare_roidb(voc, rpn_roidb)
return voc, rpn_roidb
def load_test_ss_roidb(image_set, year, root_path, devkit_path):
voc = PascalVOC(image_set, year, root_path, devkit_path)
gt_roidb = voc.gt_roidb()
ss_roidb = voc.selective_search_roidb(gt_roidb)
prepare_roidb(voc, ss_roidb)
return voc, ss_roidb
