#!/usr/bin/env python
import sys
from vdetlib.utils.common import iou, quick_args
import scipy.io as sio
import numpy as np
if __name__ == '__main__':
args = quick_args(['gt_list', 'save_file'])
with open(args.gt_list) as f:
gt_list = [line.strip() for line in f.readlines()]
tot_overlaps = []
for ind, gt_file in enumerate(gt_list, start=1):
gt_boxes = sio.loadmat(gt_file)['boxes']
num_gt = len(gt_boxes)
if ind % 1000 == 0:
print "{:.2%}: Processed {} files.".format(1. * ind / len(gt_list),
ind)
if num_gt <= 1:
continue
o_ind = np.triu_indices(num_gt, 1)
overlaps = iou(gt_boxes, gt_boxes)
valid_overlaps = overlaps[o_ind]
tot_overlaps += valid_overlaps.tolist()
if ind % 1000 != 0:
print "100 %: Processed {} files.".format(ind)
sio.savemat(args.save_file, {'gt_overlaps': np.asarray(tot_overlaps)})
import argparse
import numpy as np
import scipy.io as sio
import os
import sys
sys.path.insert(1, '.')
import h5py
from vdetlib.vdet.dataset import imagenet_vdet_classes
from vdetlib.utils.common import quick_args
from vdetlib.utils.protocol import proto_load, proto_dump, bbox_hash
import gzip
import json
if __name__ == '__main__':
args = quick_args(['vid_file', 'score_root', 'save_det'])
vid_proto = proto_load(args.vid_file)
vid_name = vid_proto['video']
assert vid_name == os.path.basename(os.path.normpath(args.score_root))
print "Processing {}.".format(vid_name)
if os.path.isfile(args.save_det):
print "{} already exists.".format(args.save_det)
sys.exit(0)
det_proto = {}
det_proto['video'] = vid_name
det_proto['detections'] = []
for frame in vid_proto['frames']:
frame_id = frame['frame']
basename = os.path.splitext(frame['path'])[0]
#!/usr/bin/env python
import sys
from vdetlib.utils.common import iou, quick_args
import scipy.io as sio
import numpy as np
if __name__ == '__main__':
args = quick_args(['gt_list', 'save_file'])
with open(args.gt_list) as f:
gt_list = [line.strip() for line in f.readlines()]
tot_overlaps = []
for ind, gt_file in enumerate(gt_list, start=1):
gt_boxes = sio.loadmat(gt_file)['boxes']
num_gt = len(gt_boxes)
if ind % 1000 == 0:
print "{:.2%}: Processed {} files.".format(1. * ind / len(gt_list), ind)
if num_gt <= 1:
continue
o_ind = np.triu_indices(num_gt, 1)
overlaps = iou(gt_boxes, gt_boxes)
valid_overlaps = overlaps[o_ind]
tot_overlaps += valid_overlaps.tolist()
if ind % 1000 != 0:
print "100 %: Processed {} files.".format(ind)
sio.savemat(args.save_file,
{'gt_overlaps': np.asarray(tot_overlaps)})
import argparse
import numpy as np
import scipy.io as sio
import os
import sys
sys.path.insert(1, '.')
import h5py
from vdetlib.vdet.dataset import imagenet_vdet_classes
from vdetlib.utils.common import quick_args
from vdetlib.utils.protocol import proto_load, proto_dump, bbox_hash
import gzip
import json
if __name__ == '__main__':
args = quick_args(['vid_file', 'score_root', 'save_det'])
vid_proto = proto_load(args.vid_file)
vid_name = vid_proto['video']
assert vid_name == os.path.basename(os.path.normpath(args.score_root))
print "Processing {}.".format(vid_name)
if os.path.isfile(args.save_det):
print "{} already exists.".format(args.save_det)
sys.exit(0)
det_proto = {}
det_proto['video'] = vid_name
det_proto['detections'] = []
for frame in vid_proto['frames']:
frame_id = frame['frame']
basename = os.path.splitext(frame['path'])[0]
