def get(self, request, *args, **kwargs):
result = models.Result.objects.get(pk=kwargs['pk'])
res_id = kwargs['res_id']
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
segment_result = container[res_id]
import tempfile
tmp_dir = tempfile.mkdtemp(suffix=res_id + '_sv')
# Pympi will not overwrite the file
audio_file = os.path.abspath(result.item.file.name)
tmp_sv_file = os.path.splitext(
os.path.basename(audio_file))[0] + '_' + res_id + '.sv'
abs_tmp_sv_file = os.path.join(tmp_dir, tmp_sv_file)
segment_result.data_object.to_sonic_visualiser(
svenv_file=abs_tmp_sv_file, audio_file=audio_file)
file_size = os.path.getsize(abs_tmp_sv_file)
# read file
with open(abs_tmp_sv_file, "rb") as f:
sv_data = f.read()
import shutil
shutil.rmtree(tmp_dir)
response = HttpResponse(sv_data, content_type='application/xml')
response['Content-Disposition'] = 'attachment; filename=' + \
'\"' + tmp_sv_file + '\"'
response['Content-Length'] = file_size
return response
def get(self, request, *args, **kwargs):
result = Result.objects.get(pk=kwargs['pk'])
res_id = kwargs['res_id']
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
segment_result = container[res_id]
import tempfile
tmp_dir = tempfile.mkdtemp(suffix=res_id+'_eaf')
# Pympi will not overwrite the file
audio_file = os.path.basename(segment_result.audio_metadata.uri)
tmp_eaf_file = os.path.splitext(audio_file)[0] + '_' + res_id + '.eaf'
abs_tmp_eaf_file = os.path.join(tmp_dir,tmp_eaf_file)
segment_result.data_object.to_elan(elan_file=abs_tmp_eaf_file,
media_file=audio_file)
file_size = os.path.getsize(abs_tmp_eaf_file)
# read file
with open(abs_tmp_eaf_file, "rb") as f:
eaf_data = f.read()
import shutil
shutil.rmtree(tmp_dir)
response = HttpResponse(eaf_data, content_type='application/xml')
response['Content-Disposition'] = 'attachment; filename=' + '\"' + tmp_eaf_file +'\"'
response['Content-Length'] = file_size
return response
def get(self, request, *args, **kwargs):
result = Result.objects.get(pk=kwargs['pk'])
res_id = kwargs['res_id']
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
segment_result = container[res_id]
import tempfile
tmp_dir = tempfile.mkdtemp(suffix=res_id + '_eaf')
# Pympi will not overwrite the file
audio_file = os.path.basename(segment_result.audio_metadata.uri)
tmp_eaf_file = os.path.splitext(audio_file)[0] + '_' + res_id + '.eaf'
abs_tmp_eaf_file = os.path.join(tmp_dir, tmp_eaf_file)
segment_result.data_object.to_elan(elan_file=abs_tmp_eaf_file,
media_file=audio_file)
file_size = os.path.getsize(abs_tmp_eaf_file)
# read file
with open(abs_tmp_eaf_file, "rb") as f:
eaf_data = f.read()
import shutil
shutil.rmtree(tmp_dir)
response = HttpResponse(eaf_data, content_type='application/xml')
response[
'Content-Disposition'] = 'attachment; filename=' + '\"' + tmp_eaf_file + '\"'
response['Content-Length'] = file_size
return response
def get(self, request, *args, **kwargs):
result = models.Result.objects.get(pk=kwargs['pk'])
res_id = kwargs['res_id']
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
segment_result = container[res_id]
import tempfile
tmp_dir = tempfile.mkdtemp(suffix=res_id + '_sv')
# Pympi will not overwrite the file
audio_file = os.path.abspath(result.item.file.name)
tmp_sv_file = os.path.splitext(os.path.basename(audio_file))[
0] + '_' + res_id + '.sv'
abs_tmp_sv_file = os.path.join(tmp_dir, tmp_sv_file)
segment_result.data_object.to_sonic_visualiser(svenv_file=abs_tmp_sv_file,
audio_file=audio_file)
file_size = os.path.getsize(abs_tmp_sv_file)
# read file
with open(abs_tmp_sv_file, "rb") as f:
sv_data = f.read()
import shutil
shutil.rmtree(tmp_dir)
response = HttpResponse(sv_data, content_type='application/xml')
response['Content-Disposition'] = 'attachment; filename=' + \
'\"' + tmp_sv_file + '\"'
response['Content-Length'] = file_size
return response
def tearDown(self):
results = AnalyzerResultContainer([self.result])
results.to_numpy('/tmp/t.npy')
d_numpy = results.from_numpy('/tmp/t.npy')
if verbose:
print('%15s' % 'from numpy:', d_numpy)
self.assertEqual(d_numpy, results)
def tearDown(self):
results = AnalyzerResultContainer([self.result])
results.to_numpy("/tmp/t.npy")
d_numpy = results.from_numpy("/tmp/t.npy")
if verbose:
print "%15s" % "from numpy:",
print d_numpy
self.assertEqual(d_numpy, results)
def get(self, request, *args, **kwargs):
result = models.Result.objects.get(uuid=kwargs['uuid'])
container = AnalyzerResultContainer()
if result.hdf5:
container.from_hdf5(result.hdf5.path)
else:
return HttpResponse(container.to_json(),
content_type='application/json')
def tearDown(self):
results = AnalyzerResultContainer(self.result)
r_yaml = results.to_yaml()
if verbose:
print "to yaml:"
print r_yaml
from_results = AnalyzerResultContainer()
from_results.from_yaml(r_yaml)
if verbose:
print "%15s" % "from yaml:",
print from_results
self.assertEqual(
type(self.result.data_object.frame_metadata), type(from_results["foo_bar"].data_object.frame_metadata)
)
def tearDown(self):
results = AnalyzerResultContainer([self.result])
r_xml = results.to_xml()
if verbose:
print "to xml:"
print r_xml
from_results = AnalyzerResultContainer()
from_results.from_xml(r_xml)
if verbose:
print "%15s" % "from xml:",
print from_results
# for i in range(len(d_xml)):
self.assertEqual(results, from_results)
def tearDown(self):
results = AnalyzerResultContainer([self.result])
try:
r_json = results.to_json()
except TypeError:
print ("TYPE ERROR IN JSON")
if verbose:
print "to json:"
print r_json
from_results = AnalyzerResultContainer()
from_results.from_json(r_json)
if verbose:
print from_results
print "%15s" % "from json:",
self.assertEqual(results, from_results)
def get_context_data(self, **kwargs):
context = super(ItemDiadems, self).get_context_data(**kwargs)
context['Result'] = 'Result'
Results = {}
for result in self.get_object().results.all():
proc_id = result.preset.processor.pid
Results[proc_id] = {'id': result.id}
if result.hdf5:
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
Results[proc_id]['json'] = True
Results[proc_id]['list'] = {}
elif result.mime_type:
Results[proc_id]['audio'] = ('audio' in result.mime_type) | (
'ogg' in result.mime_type)
Results[proc_id]['image'] = ('image' in result.mime_type)
Results[proc_id]['video'] = ('video' in result.mime_type)
container = {}
for res_id, res in container.items():
if res.time_mode == 'segment':
if res.data_mode == 'label':
Results[proc_id]['list'][res_id] = {
'elan': True,
'sv': True,
'Parameters': res.parameters,
'name': res.name
}
if res.time_mode == 'framewise':
if res.data_mode == 'value':
Results[proc_id]['list'][res_id] = {
'elan': False,
'sv': True,
'Parameters': res.parameters,
'name': res.name
}
context['Results'] = Results
return context
def get_context_data(self, **kwargs):
context = super(ItemDiadems, self).get_context_data(**kwargs)
context['Result'] = 'Result'
Results = {}
for result in self.get_object().results.all():
proc_id = result.preset.processor.pid
Results[proc_id] = {'id': result.id}
if result.hdf5:
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
Results[proc_id]['json'] = True
Results[proc_id]['list']= {}
elif result.mime_type:
Results[proc_id]['audio'] = ('audio' in result.mime_type) | ('ogg' in result.mime_type)
Results[proc_id]['image'] = ('image' in result.mime_type)
Results[proc_id]['video'] = ('video' in result.mime_type)
container = {}
for res_id, res in container.items():
if res.time_mode == 'segment':
if res.data_mode == 'label':
Results[proc_id]['list'][res_id] = {'elan': True,
'sv': True,
'Parameters': res.parameters,
'name': res.name}
if res.time_mode == 'framewise':
if res.data_mode == 'value':
Results[proc_id]['list'][res_id] = {'elan': False,
'sv': True,
'Parameters': res.parameters,
'name': res.name}
context['Results'] = Results
return context
def get_context_data(self, **kwargs):
context = super(ItemDetail, self).get_context_data(**kwargs)
context['Result'] = 'Result'
Results = {}
for result in self.get_object().results.all():
if result.hdf5:
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
else:
container = {}
for name, res in container.items():
if res.time_mode == 'segment':
if res.data_mode == 'label':
Results[result.id] = name
context['Results'] = Results
return context
def get_context_data(self, **kwargs):
context = super(ItemDetail, self).get_context_data(**kwargs)
context['Result'] = 'Result'
Results = {}
for result in self.get_object().results.all():
if result.hdf5:
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
else:
container = {}
for name, res in container.items():
if res.time_mode == 'segment':
if res.data_mode == 'label':
Results[result.id] = name
context['Results'] = Results
return context
def tearDown(self):
results = AnalyzerResultContainer(self.result)
r_yaml = results.to_yaml()
if verbose:
print('to yaml:', r_yaml)
from_results = AnalyzerResultContainer()
from_results.from_yaml(r_yaml)
if verbose:
print('%15s' % 'from yaml:', from_results)
self.assertEqual(type(self.result.data_object.frame_metadata),
type(from_results['foo_bar'].data_object.frame_metadata))
def tearDown(self):
results = AnalyzerResultContainer([self.result])
r_xml = results.to_xml()
if verbose:
print('to xml:', r_xml)
from_results = AnalyzerResultContainer()
from_results.from_xml(r_xml)
if verbose:
print('%15s' % 'from xml:', from_results)
#for i in range(len(d_xml)):
self.assertEqual(results, from_results)
def tearDown(self):
results = AnalyzerResultContainer([self.result])
try:
r_json = results.to_json()
except TypeError:
print('TYPE ERROR IN JSON')
if verbose:
print('to json:', r_json)
from_results = AnalyzerResultContainer()
from_results.from_json(r_json)
if verbose:
print('%15s' % 'from json:', from_results)
self.assertEqual(results, from_results)
def tearDown(self):
if isinstance(self.result, AnalyzerResult):
results = AnalyzerResultContainer([self.result])
elif isinstance(self.result, AnalyzerResultContainer) :
results = self.result
else:
raise(TypeError, "Wrong type for self.result")
import tempfile
h5_file = tempfile.NamedTemporaryFile(suffix='.h5', delete=True)
results.to_hdf5(h5_file.name)
from_results = AnalyzerResultContainer()
from_results.from_hdf5(h5_file.name)
if verbose:
print('%15s' % 'from hdf5:', from_results)
self.assertEqual(results, from_results)
h5_file.close()
def tearDown(self):
if isinstance(self.result, AnalyzerResult):
results = AnalyzerResultContainer([self.result])
elif isinstance(self.result, AnalyzerResultContainer):
results = self.result
else:
raise (TypeError, "Wrong type for self.result")
import tempfile
h5_file = tempfile.NamedTemporaryFile(suffix=".h5", delete=True)
results.to_hdf5(h5_file.name)
from_results = AnalyzerResultContainer()
from_results.from_hdf5(h5_file.name)
if verbose:
print "%15s" % "from hdf5:",
print from_results
self.assertEqual(results, from_results)
h5_file.close()
def get(self, request, *args, **kwargs):
result = models.Result.objects.get(pk=kwargs['pk'])
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
return HttpResponse(container.to_json(),
content_type='application/json')
def get(self, request, *args, **kwargs):
result = Result.objects.get(pk=kwargs['pk'])
container = AnalyzerResultContainer()
container.from_hdf5(result.hdf5.path)
return HttpResponse(container.to_json(),
content_type='application/json')
