def metadata2eic(bin_lid,parallax,merge=False):
"""Convert bin image metadata to CSV"""
#imagename,lat,lon,head,pitch,roll,alt1,alt2,depth,s,t,o2,cdom,chlorophyll,backscatter,therm
if merge:
(PITCH_COL, ROLL_COL) = (4, 5)
fields = ['imagename', 'alt', 'pitch','roll']
imgdata = resolver['img'].resolve(pid=bin_lid).value
logging.info('reading CSV data from .img file %s' % imgdata)
(pitch,roll) = ({}, {})
for row in read_csv(LocalFileSource(imgdata)):
imagename = remove_extension(row[0])
try:
pitch[imagename] = row[PITCH_COL]
roll[imagename] = row[ROLL_COL]
except KeyError:
pass
logging.info('merging with parallax-based altitude from %s' % parallax)
else:
logging.info('reading parallax-based altitude from %s' % parallax)
for l in open(parallax):
(imagename, _, _, alt) = re.split(r',',l.rstrip())
try:
if merge:
yield [imagename, alt, pitch[imagename], roll[imagename]]
else:
yield [imagename, alt, '0.0', '0.0']
except KeyError:
pass
def alt(bin_lid):
tmp = mkdirs(scratch(bin_lid))
csv_filename = os.path.join(tmp,bin_lid+'_alt.csv')
logging.info('listing images for %s' % bin_lid)
imagenames = [remove_extension(i) for i in list_images(bin_lid)]
logging.info('looking for existing altitude data...')
already_done = []
if os.path.exists(csv_filename):
for row in read_csv(LocalFileSource(csv_filename)):
already_done += [remove_extension(row[0])]
logging.info('found %d existing altitude records' % len(already_done))
if len(already_done) == -1:
logging.info('emptying CSV file ...')
with open(csv_filename,'w') as csv_out:
pass
pids = []
for n in range(NUM_PROCS):
pid = os.fork()
if pid == 0:
for imagename in imagenames[n::NUM_PROCS]:
if imagename not in already_done:
tif = img_as_float(read_image(imagename+'.tif'))
logging.info('[%d] START aligning %s' % (n, imagename))
x,y,m = stereo2altitude(tif)
line = '%s,%d,%d,%.2f' % (imagename,x,y,m)
logging.info('[%d] DONE aligned %s' % (n, line))
with open(csv_filename,'a') as csv_out:
print >>csv_out, line
csv_out.flush()
os._exit(0)
else:
logging.info('spawned process %d' % pid)
pids += [pid]
for pid in pids:
logging.info('waiting for process %d' % pid)
os.waitpid(pid,0)
logging.info('joined alignment process %d' % pid)
# now sort file
logging.info('sorting CSV data...')
rows = list(read_csv(LocalFileSource(csv_filename)))
rows = sorted(rows, key=lambda r: r[0])
csv_out = csv_filename # same as in
with open(csv_out,'w') as co:
for row in rows:
print >>co, ','.join([row[n] for n in range(4)])
logging.info('wrote CSV data to %s' % csv_out)
def get_features_schema(req, features_path=None):
if features_path is None:
# will raise NotFound if not features file is found,
# caller must catch to provide default value in this case
features_path = get_product_file(req.parsed,'features')
features_source = LocalFileSource(features_path)
for row in read_csv(features_source, None, 0, 1):
return row
def read_adc(source, target_no=1, limit=-1, schema_version=SCHEMA_VERSION_1):
"""Convert ADC data in its native format to dictionaries representing each target.
Read starting at the specified target number (default 1)"""
target_number = target_no-1
for row in read_csv(source, ADC_SCHEMA[schema_version], target_no-1, limit):
target_number += 1
# skip 0x0 targets
if row[WIDTH] * row[HEIGHT] > 0:
# add target number
row[TARGET_NUMBER] = target_number
yield row
def read_adc(adc_path, target_no=1, limit=-1, schema=None):
"""Convert ADC data in its native format to dictionaries representing each target.
Read starting at the specified target number (default 1)"""
target_number = target_no-1
adc_source = LocalFileSource(adc_path)
for row in read_csv(adc_source, schema, target_no-1, limit):
target_number += 1
# skip 0x0 targets
if row[WIDTH] * row[HEIGHT] > 0:
# add target number
row[TARGET_NUMBER] = target_number
yield row
def read_features(features_path):
features_source = LocalFileSource(features_path)
for row in read_csv(features_source, None, 1, NO_LIMIT):
yield row