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Add channel stats option to coco stats CLI #9

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Add channel stats option to coco stats CLI #9

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90 changes: 90 additions & 0 deletions kwcoco/cli/coco_stats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@ class CocoStatsCLI(scfg.DataConfig):
annot_attrs = scfg.Value(False, isflag=True, help='show annotation attribute information')
image_attrs = scfg.Value(False, isflag=True, help='show image attribute information')
video_attrs = scfg.Value(False, isflag=True, help='show video attribute information')
channels = scfg.Value(False, isflag=True, help='show channel and sensor information')
io_workers = scfg.Value(0, help=ub.paragraph(
'''
number of workers when reading multiple kwcoco files
Expand Down Expand Up @@ -195,6 +196,17 @@ def main(cls, cmdline=True, **kw):
if human_readable:
print('hist(annot_attrs) = {}'.format(ub.urepr(attrs, nl=1)))

if config['channels']:
if human_readable:
print('Channel and sensor stats')
stat_types['channels'] = {}
for dset in datasets:
channel_info = _coco_channel_stats(dset)
stat_types['channels'][dset.tag] = channel_info
if human_readable:
rich_print('dset.tag = {!r}'.format(dset.tag))
rich_print(ub.urepr(channel_info, nl=2, sort=0))

if config['boxes']:
if human_readable:
print('Box stats')
Expand Down Expand Up @@ -331,6 +343,84 @@ def main(cls, cmdline=True, **kw):
# print(ub.urepr(dset.boxsize_stats(), nl=-1, precision=2))


def _coco_channel_stats(coco_dset):
"""
Return information about which channels and sensors are available.

This is a streamlined version of the richer geowatch stats, focused on
generic kwcoco datasets.

Example:
>>> import kwcoco
>>> from kwcoco.cli.coco_stats import _coco_channel_stats
>>> dset = kwcoco.CocoDataset()
>>> dset.add_category('a')
>>> gid1 = dset.add_image(file_name='img1.tif', sensor_coarse='S1', width=1, height=1)
>>> gid2 = dset.add_image(file_name='img2.tif', sensor_coarse='S2', width=1, height=1)
>>> dset.add_asset(gid=gid1, file_name='a1.tif', channels='red,green', width=1, height=1)
>>> dset.add_asset(gid=gid1, file_name='a2.tif', channels='blue', width=1, height=1)
>>> dset.add_asset(gid=gid2, file_name='b1.tif', channels='red,green', width=1, height=1)
>>> dset.add_asset(gid=gid2, file_name='b2.tif', channels='nir', width=1, height=1)
>>> info = _coco_channel_stats(dset)
>>> assert info['sensor_hist'] == {'S1': 1, 'S2': 1}
>>> assert info['chan_hist']['blue,red,green,unknown-chan'] == 1
>>> assert info['chan_hist']['nir,red,green,unknown-chan'] == 1
>>> assert info['common_channels'] == '<FusedChannelSpec(red|green|unknown-chan)>'
>>> assert info['all_channels'] == '<FusedChannelSpec(blue|red|green|unknown-chan|nir)>'
"""
import kwcoco
from kwcoco.coco_image import CocoImage

sensor_hist = ub.ddict(int)
chan_hist = ub.ddict(int)
single_chan_hist = ub.ddict(int)
sensorchan_hist = ub.ddict(lambda: ub.ddict(int))
sensorchan_hist2 = ub.ddict(int)
for _gid, img in coco_dset.index.imgs.items():
coco_img: CocoImage = coco_dset.coco_image(_gid)
channels = []
for obj in coco_img.iter_asset_objs():
channels.append(obj.get('channels', 'unknown-chan'))
channels = sorted(channels)
chan = ','.join(channels)
sensor = img.get('sensor_coarse', '*')
chan_hist[chan] += 1
sensor_hist[sensor] += 1
sensorchan_hist[sensor][chan] += 1
sensorchan = f'{sensor}:({chan})'
sensorchan_hist2[sensorchan] += 1

for single_chan in kwcoco.ChannelSpec(chan).unique():
single_chan_hist[single_chan] += 1

CS = kwcoco.ChannelSpec
FS = kwcoco.FusedChannelSpec
osets = [CS.coerce(c).fuse().to_oset() for c in chan_hist]
if len(osets) == 0:
common_channels = FS.coerce([])
all_channels = FS.coerce([])
all_sensorchan = kwcoco.SensorChanSpec.coerce('')
else:
common_channels = FS.coerce(list(ub.oset.intersection(*osets))).concise()
all_channels = FS.coerce(list(ub.oset.union(*osets))).concise()
all_sensorchan = kwcoco.SensorChanSpec.late_fuse(*[
kwcoco.SensorChanSpec.coerce(s)
for s in sensorchan_hist2.keys()]).concise()

info = {
'single_chan_hist': {k: int(v) for k, v in single_chan_hist.items()},
'chan_hist': {k: int(v) for k, v in chan_hist.items()},
'sensor_hist': {k: int(v) for k, v in sensor_hist.items()},
'sensorchan_hist': {k: {k2: int(v2) for k2, v2 in v.items()}
for k, v in sensorchan_hist.items()},
'sensorchan_hist2': {k: int(v) for k, v in sensorchan_hist2.items()},
'common_channels': str(common_channels),
'all_channels': str(all_channels),
'all_sensorchan': str(all_sensorchan),
}
return info


def _dataset_disk_usage(dset):
"""
Compute disk usage of all image assets referenced by this dataset.
Expand Down