def __init__(self, pipeline, version="2"):
super(RunVA, self).__init__()
self._pipeline = pipeline
self._version = version
self._db = DBIngest(host=dbhost, index="algorithms", office=office)
self._maincontext = GLib.MainLoop().get_context()
self._stop = None
ModelManager.load_config("/home/models", {})
PipelineManager.load_config("/home/pipelines", 1)
def main(options):
PipelineManager.load_config(
os.path.join(CONFIG_PATH, options.pipeline_dir), MAX_RUNNING_PIPELINES)
ModelManager.load_config(os.path.join(CONFIG_PATH, options.model_dir))
asyncio.set_event_loop(asyncio.new_event_loop())
app = connexion.App(__name__, specification_dir='./openapi/')
app.app.json_encoder = encoder.JSONEncoder
app.add_api('openapi.yaml', arguments={'title': 'Video Analytics API'})
logger.info("Starting Tornado Server on port: {p}".format(p=options.port))
app.run(server='tornado', port=options.port)
def main(options):
PipelineManager.load_config(
os.path.join(options.config_path, options.pipeline_dir),
options.max_running_pipelines)
ModelManager.load_config(
os.path.join(options.config_path, options.model_dir),
parse_network_preference(options))
app = connexion.App(__name__, specification_dir='./openapi/')
app.app.json_encoder = encoder.JSONEncoder
app.add_api('openapi.yaml',
arguments={'title': 'Video Analytics Serving API'})
logger.info("Starting Tornado Server on port: {p}".format(p=options.port))
app.run(server='tornado', port=options.port)
def test_get_loaded_models_empty(self):
ModelManager.models = None
expected_result = []
result = ModelManager.get_loaded_models()
self.assertEqual(result, expected_result)
def models_get(): # noqa: E501
"""models_get
Return supported models # noqa: E501
:rtype: List[ModelVersion]
"""
logger.debug("GET on /models")
return ModelManager.get_loaded_models()
def _add_default_models(self):
gva_elements = [
e for e in self.pipeline.iterate_elements()
if (e.__gtype__.name in self.GVA_INFERENCE_ELEMENT_TYPES)
]
for e in gva_elements:
network = ModelManager.get_default_network_for_device(
e.get_property("device"), e.get_property("model"))
logger.debug("Setting model to {} for element {}".format(
network, e.get_name()))
e.set_property("model", network)
def models_get(): # noqa: E501
"""models_get
Return supported models # noqa: E501
:rtype: List[ModelVersion]
"""
try:
logger.debug("GET on /models")
return ModelManager.get_loaded_models()
except Exception as e:
logger.error('pipelines_name_version_get '+e)
return ('Unexpected error', HTTPStatus.INTERNAL_SERVER_ERROR)
def _add_default_models(self,args):
vf_index = args.index('-vf') if ('-vf' in args) else None
if (vf_index==None):
return
filters = args[vf_index+1].split(',')
new_filters=[]
for _filter in filters:
filter_params = self._get_filter_params(_filter)
if ( (filter_params['type'] in FFmpegPipeline.GVA_INFERENCE_FILTER_TYPES)):
device='CPU'
if ('device' in filter_params):
device = FFmpegPipeline.DEVICEID_MAP[int(filter_params['device'])]
filter_params['model'] = ModelManager.get_default_network_for_device(device,filter_params['model'])
new_filters.append(self._join_filter_params(filter_params))
else:
new_filters.append(_filter)
args[vf_index+1] =','.join(new_filters)
def _add_default_models(self, args):
vf_index = args.index('-vf') if ('-vf' in args) else None
if (vf_index == None):
return
filters = args[vf_index + 1].split(',')
new_filters = []
for _filter in filters:
filter_params = self._get_filter_params(_filter)
if ((filter_params['type']
in FFmpegPipeline.GVA_INFERENCE_FILTER_TYPES)
and ("VA_DEVICE_DEFAULT" in filter_params['model'])):
device = "CPU"
if ("device" in filter_params):
device = filter_params["device"]
if isinstance(filter_params['device'], int):
device = FFmpegPipeline.DEVICEID_MAP[int(
filter_params['device'])]
filter_params[
"model"] = ModelManager.get_default_network_for_device(
device, filter_params["model"])
new_filters.append(self._join_filter_params(filter_params))
elif (filter_params['type'] == "metaconvert"):
# use the file to send the tags info to ffmpeg
tmp_file = "/tmp/timestamp"
if "tags" in self.request:
try:
tmp_tags = ""
for key in self.request["tags"]:
#filter_params["tags"] = "{\"%s\":%s}" % (key, self.request["tags"][key])
tmp_tags = "{\"%s\":%s}" % (
key, self.request["tags"][key])
with open(tmp_file, 'w') as f:
f.write(tmp_tags)
except Exception:
logger.error("Error adding tags")
source_uri = "source=" + "'" + self.request["source"][
"uri"].replace(":", "\\:") + "'"
filter_params_str = self._join_filter_params(
filter_params).replace("source=NULL", source_uri)
filter_params_str = filter_params_str.replace(
"tags=NULL", "tags=file|" + tmp_file)
new_filters.append(filter_params_str)
else:
new_filters.append(_filter)
args[vf_index + 1] = ','.join(new_filters)
def test_load_config(self):
ModelManager.load_config("../models")
print(ModelManager.models)
def __init__(self):
super(RunVA, self).__init__()
ModelManager.load_config("/home/models", {})
PipelineManager.load_config("/home/pipelines", 1)
self._maincontext = GLib.MainLoop().get_context()
GLib.timeout_add(1000, self._noop)