def load_features(cm, _cxs=None, force_recomp=False):
if _cxs is None:
cxs = cm.get_valid_cxs()
elif type(_cxs) is types.ListType:
cxs = np.array(_cxs)
elif type(_cxs) in [types.IntType, types.LongType, np.uint32]:
cxs = np.array([_cxs])
else:
cxs = _cxs
count_feat = 0
is_dirty = np.bitwise_or(cm.cx2_dirty_bit[cxs], force_recomp)
num_samp = cxs.size
num_dirty = np.sum(is_dirty)
# HACKS
if not np.iterable(is_dirty):
is_dirty = np.array([is_dirty])
if not np.iterable(cxs):
cxs = np.array([cxs])
load_cx = cxs[is_dirty]
num_clean = num_samp - num_dirty
#logdbg('Loading Features: Dirty=%d ; #Clean=%d' % (num_dirty, num_clean))
if num_dirty == 0:
return
logio('Loading %d Feature Reps' % num_dirty)
am = cm.hs.am
for cx in iter(load_cx):
cid = cm.cx2_cid[cx]
if cid <= 0:
logwarn('WARNING: IX=' + str(cx) + ' is invalid')
continue
chiprep_fpath = cm.hs.iom.get_chiprep_fpath(cid)
# Ensure that the features exists
if force_recomp or not os.path.exists(chiprep_fpath):
logio('Computing and saving features of cid=' + str(cid))
hotspotter.ChipFunctions.precompute_chipreps(
cm.hs, [cx], num_procs=1, force_recompute=force_recomp)
# Load the features
logdbg('Loading features in ' + chiprep_fpath)
npz = np.load(chiprep_fpath)
fpts = npz['arr_0']
fdsc = npz['arr_1']
npz.close()
cm.cx2_fpts[cx] = fpts
cm.cx2_fdsc[cx] = fdsc
cm.cx2_dirty_bit[cx] = False
count_feat += len(fpts)
logdbg('* Loaded ' + str(count_feat) + ' keypoints and fdscriptors')
return True
def load_features(cm, _cxs=None, force_recomp=False):
if _cxs is None:
cxs = cm.get_valid_cxs()
elif type(_cxs) is types.ListType:
cxs = np.array(_cxs)
elif type(_cxs) in [types.IntType, types.LongType, np.uint32]:
cxs = np.array([_cxs])
else:
cxs = _cxs
count_feat = 0
is_dirty = np.bitwise_or(cm.cx2_dirty_bit[cxs], force_recomp)
num_samp = cxs.size
num_dirty = np.sum(is_dirty)
# HACKS
if not np.iterable(is_dirty):
is_dirty = np.array([is_dirty])
if not np.iterable(cxs):
cxs = np.array([cxs])
load_cx = cxs[is_dirty]
num_clean = num_samp - num_dirty
#logdbg('Loading Features: Dirty=%d ; #Clean=%d' % (num_dirty, num_clean))
if num_dirty == 0:
return
logio('Loading %d Feature Reps' % num_dirty)
am = cm.hs.am
for cx in iter(load_cx):
cid = cm.cx2_cid[cx]
if cid <= 0:
logwarn('WARNING: IX='+str(cx)+' is invalid'); continue
chiprep_fpath = cm.hs.iom.get_chiprep_fpath(cid)
# Ensure that the features exists
if force_recomp or not os.path.exists(chiprep_fpath):
logio('Computing and saving features of cid='+str(cid))
hotspotter.ChipFunctions.precompute_chipreps(cm.hs, [cx], num_procs=1, force_recompute=force_recomp)
# Load the features
logdbg('Loading features in '+chiprep_fpath)
npz = np.load(chiprep_fpath)
fpts = npz['arr_0']
fdsc = npz['arr_1']
npz.close()
cm.cx2_fpts[cx] = fpts
cm.cx2_fdsc[cx] = fdsc
cm.cx2_dirty_bit[cx] = False
count_feat += len(fpts)
logdbg('* Loaded '+str(count_feat)+' keypoints and fdscriptors' )
return True
def save_model(vm):
# See if the model is savable
if not vm.model_prefs.save_load_model:
logdbg('Can NOT save the visual model due to preferences')
return False
if vm.isDirty:
raise Exception('Can NOT save the visual model due to dirty index')
if vm.flann is None:
raise Exception('Can NOT save the visual model without a flann index')
logdbg('Building dictionary to save')
# TODO: This dictionary should just exist and not be
# directly tied to this class.
# Build a dictionary of savable model terms
to_save_dict = {key : vm.__dict__[key] \
for key in vm.savable_model_fields }
# Get the save paths
model_fpath = vm.hs.iom.get_model_fpath()
flann_index_fpath = vm.hs.iom.get_flann_index_fpath()
# Save the Model
logio('Saving model to: '+model_fpath)
np.savez(model_fpath, **to_save_dict)
# Save the Index
logio('Saving index to: '+flann_index_fpath)
vm.flann.save_index(flann_index_fpath)
logio('Model save was sucessfull')
return True
def _load_table(iom, csv_fpath, table_name, alloc_func, csv_func):
"""
Reads csv files. Must pass in a table name a memory allocation function
and a csv_func: function which parses the fields read by _load_table
"""
logio("Loading " + table_name + " Table: " + csv_fpath)
if not exists(csv_fpath):
logio('"' + csv_fpath + '" Does Not Exist')
return False
fid = file(csv_fpath, "r")
csv_headers = None
line = fid.readline()
num_line_prefix = "# NumData"
# Foreach line in the CSV file
while line != "":
line = line.strip()
# NEW LINE: Skip
if line == "":
continue
# COMMENT LINE: Check for metadata
elif line[0] == "#":
# CHECK Preallocation
if line.find(num_line_prefix) > -1:
# Parse out the number of lines to allocate
# and use the given allocation function
num_lines = int(line.replace(num_line_prefix, "").replace(" ", ""))
alloc_func(num_lines)
# CHECK Data Headers: StripeSpotter
elif line.find("#imgindex") > -1:
logmsg("Loading a Legacy StripeSpotter File")
csv_headers = line[1:].split(",")
# CHECK Data Headers: Legacy HotSpotter
elif line.find("#01)") > -1:
logmsg("Loading a Legacy HotSpotter File")
csv_headers = []
while line != "":
line = line[:-1]
if len(line) < 4 or line[3] != ")":
break
parnstr = "#\\d\\d\\) "
head_field = re.sub(parnstr, "", line)
head_field = re.sub(" - .*", "", head_field)
csv_headers += [head_field]
line = fid.readline()
# CHECK Data Headers: Hotspotter
elif any([line.find(field) >= 0 for field in ["ChipID", "NameID", "ImageID"]]):
csv_headers = [field.strip() for field in line[1:].split(",")]
# HACK: Change the fields to the ones it actually expects
import hotspotter.other.AbstractPrintable
_lbl2_header = hotspotter.other.AbstractPrintable._lbl2_header
_header2_lbl = {v: k for k, v in _lbl2_header.iteritems()}
csv_headers = [
_header2_lbl[field] if field in _header2_lbl.keys() else field for field in csv_headers
]
# DATA LINE: Read it
else:
csv_data = [data_field.strip() for data_field in line.split(",")]
csv_func(csv_data, csv_headers)
# Next Line
line = fid.readline()
# Finsh reading table
fid.close()
logio("Loaded " + table_name + " Table")
return True
def _load_table(iom, csv_fpath, table_name, alloc_func, csv_func):
'''
Reads csv files. Must pass in a table name a memory allocation function
and a csv_func: function which parses the fields read by _load_table
'''
logio('Loading '+table_name+' Table: '+csv_fpath)
if not exists(csv_fpath):
logio('\"'+csv_fpath+'\" Does Not Exist')
return False
fid = file(csv_fpath, 'r')
csv_headers = None
line = fid.readline()
num_line_prefix = '# NumData'
# Foreach line in the CSV file
while line != '':
line = line.strip()
# NEW LINE: Skip
if line == '': continue
# COMMENT LINE: Check for metadata
elif line[0] == '#':
# CHECK Preallocation
if line.find(num_line_prefix) > -1:
# Parse out the number of lines to allocate
# and use the given allocation function
num_lines = int(line.replace(num_line_prefix,'').replace(' ',''))
alloc_func(num_lines)
# CHECK Data Headers: StripeSpotter
elif line.find('#imgindex') > -1:
logmsg('Loading a Legacy StripeSpotter File')
csv_headers = line[1:].split(',')
# CHECK Data Headers: Legacy HotSpotter
elif line.find('#01)') > -1:
logmsg('Loading a Legacy HotSpotter File')
csv_headers = []
while line != '':
line = line[:-1]
if len(line) < 4 or line[3] != ')': break
parnstr = '#\\d\\d\\) '
head_field = re.sub(parnstr, '', line)
head_field = re.sub(' - .*','', head_field)
csv_headers += [head_field]
line = fid.readline()
# CHECK Data Headers: Hotspotter
elif any([line.find(field) >=0 for field in ['ChipID', 'NameID', 'ImageID']]):
csv_headers = [field.strip() for field in line[1:].split(',')]
# HACK: Change the fields to the ones it actually expects
import hotspotter.other.AbstractPrintable
_lbl2_header = hotspotter.other.AbstractPrintable._lbl2_header
_header2_lbl = {v:k for k,v in _lbl2_header.iteritems()}
csv_headers = [_header2_lbl[field] if field in _header2_lbl.keys() else field for field in csv_headers]
# DATA LINE: Read it
else:
csv_data = [data_field.strip() for data_field in line.split(',')]
csv_func(csv_data, csv_headers)
# Next Line
line = fid.readline()
# Finsh reading table
fid.close()
logio('Loaded '+table_name+' Table')
return True
