def configure(self):
"""
Configure whole upyHome components
"""
try:
self._load_config()
MODE_DEBUG['value'] = self._get_config_key(self._config, KEY_DEBUG,
True)
_debug('upyhome::configure')
PLATFORM['value'] = self._get_config_key(self._config,
KEY_PLATFORM, True)
self._name = self._config[CONFIG_NAME]
# Re init base cb
self._init_cb(self._get_config_key(self._config, KEY_USER_CB,
True))
#Configure components
suscribes = self._get_config_key(self._config, KEY_SUSCRIBES)
if suscribes is not None and isinstance(suscribes, list):
for scb in suscribes:
self._add_suscribe(self._proxy, scb)
#Components
CONFIG_COMPS = [(CONFIG_NET, self._config_network),
(CONFIG_DIN, self._config_inputs),
(CONFIG_DOUT, self._config_outputs),
(CONFIG_LED, self._config_leds),
(CONFIG_I2C, self._config_i2cs),
(CONFIG_SPI, self._config_spis),
(CONFIG_DRIVER, self._config_drivers)]
for CONF in CONFIG_COMPS:
self._config_comp(*CONF)
except Exception as ex:
log_error('{0}@upyhome::configure'.format(ex))
def _test_error(self):
"""
make an error
"""
try:
raise Exception('Test exception')
except Exception as ex:
log_error('{0}@upyhome::test_error'.format(ex))
def get_action(camera_id):
global action
if camera_id in action:
return action[camera_id]
com.log_error(
'get_action() - No value found for camera_id: {}'.format(camera_id))
def get_known_faces_db_name(camera_id):
global input_file
if camera_id in input_file:
return input_file[camera_id]
com.log_error(
'get_known_faces_db_name() - No value found for camera_id: {}'.format(
camera_id))
def get_output_db_name(camera_id):
global output_file
if camera_id in output_file:
return output_file[camera_id]
com.log_error(
'get_output_db_name() - No value found for camera_id: {}'.format(
camera_id))
def add_faces_encodings(camera_id, face_encoding):
global known_face_encodings
#known_face_encodings.append(face_encoding)
if camera_id in known_face_encodings:
known_face_encodings[camera_id].append(face_encoding)
else:
com.log_error(
'add_faces_encodings() - No value found for camera_id: {}'.format(
camera_id))
def set_action(camera_id, value):
global action_types
if value in action_types:
global action
return action.update({camera_id: action_types[value]})
com.log_error('Unable to set up value:{}, must be one of this: {}'.format(
value, action_types.keys()))
def get_not_applicable_id(camera_id, abort=True):
global not_applicable_id
if camera_id in not_applicable_id:
return not_applicable_id[camera_id]
if abort:
com.log_error(
'get_not_applicable_id() - No value found for camera_id: {}'.
format(camera_id))
else:
return []
def read_pickle(pickle_file, exception=True):
try:
with open(pickle_file, 'rb') as f:
known_face_encodings, known_face_metadata = pickle.load(f)
return len(
known_face_metadata), known_face_encodings, known_face_metadata
except OSError as e:
if exception:
com.log_error(
"Unable to open pickle_file: {}, original exception {}".format(
pickle_file, str(e)))
else:
return 0, [], []
def read_pickle(pickle_file, exception=True):
data = []
try:
with open(pickle_file, 'rb') as f:
while True:
try:
d = pickle.load(f)
data.append(d)
except Exception as e:
break
return data
except OSError as e:
if exception:
com.log_error(
"Unable to open pickle_file: {}, original exception {}".format(
pickle_file, str(e)))
else:
return 0, []
def compare_data(data_file, known_faces_data, tolerated_difference_list):
# load data from binary db of all faces from video
total_visitors, video_face_encodings, video_faces_metadata = read_pickle(
data_file)
# load data from binary db of known faces
total_known_faces, known_face_encodings, known_face_metadata = read_pickle(
known_faces_data)
if total_known_faces == 0 or total_visitors == 0:
com.log_error("One of the db does not contain information {}")
if not isinstance(tolerated_difference_list,
list) and len(tolerated_difference_list) > 0:
com.log_error(
"Paramter range_list must be 'list'. Current type {}".format(
type(range_list)))
for tolerated_difference in tolerated_difference_list:
if tolerated_difference < 1 and tolerated_difference > 0:
print('\n---- Using tolerated difference: {} ----'.format(
tolerated_difference))
#compare_data(face_encoding, known_face_encodings, known_face_metadata, tolerated_difference)
#for known_face_encoding, known_metadata in zip(known_face_encodings, known_face_metadata):
for video_face_encoding, video_metadata in zip(
video_face_encodings, video_faces_metadata):
# check one by one all the images in the video against the known faces
#metadata, best_index, lowest_distances = lookup_known_face(known_face_encoding, video_face_encodings, video_faces_metadata, tolerated_difference)
metadata, best_index, lowest_distances = lookup_known_face(
video_face_encoding, known_face_encodings,
known_face_metadata, tolerated_difference)
if best_index:
#print(metadata)
print('-' * 8)
print('Subject {} found'.format(metadata['name']))
#print('camera_id {}'.format(video_faces_metadata[best_index]['camera_id']))
print('initial {}'.format(
video_faces_metadata[best_index]['first_seen']))
print('last {}'.format(
video_faces_metadata[best_index]['last_seen']))
print('distance: {}'.format(lowest_distances))
#quit()
'''
def exec(self, method, topic=None, data=None):
"""
Execute a comp method, mainly used from the outside world aka REPL
"""
_debug('exec %s %s %s' % (method, topic, data))
try:
if method == 'broadcast':
self._context['topic'] = topic
self._push(data)
else:
comps = None
if topic is None:
comps = self._comps.values()
else:
if topic in self._comps:
comps = [self._comps[topic]]
if comps is not None:
for comp in comps:
self._exec_func(comp, method, data)
return True
except Exception as ex:
log_error('{0}@upyhome::exec'.format(ex))
return False
#!/usr/bin/python3
import sys
import lib.common as com
param_length = len(sys.argv)
msg = 'Usage: ' + sys.argv[
0] + ' loadFaces | readVideo | readSilence | findImg | findVideo | compareData | appendTo'
if param_length < 2:
com.log_error(msg)
if sys.argv[1] == 'loadFaces':
if param_length == 2:
known_faces = 'data/load'
data_file = 'data/encoded_known_faces/knownFaces.dat'
elif param_length == 4 and sys.argv[3] == 'output':
known_faces = sys.argv[2]
pickle_file = sys.argv[4]
else:
com.log_error(msg)
import lib.biblioteca as biblio
biblio.encode_known_faces(known_faces, data_file)
elif sys.argv[1] == 'appendTo':
if param_length == 2:
known_faces = 'data/load'
data_file = 'data/encoded_known_faces/knownFaces.dat'
elif param_length == 4 and sys.argv[3] == 'output':
known_faces = sys.argv[2]
data_file = sys.argv[4]
def main(args):
# Check input arguments
if len(args) < 2:
sys.stderr.write(
"usage: %s <uri1> [uri2] ... [uriN] <folder to save frames>\n" %
args[0])
sys.exit(1)
print("Argumentos :", args)
for i in range(0, len(args) - 2):
fps_streams["stream{0}".format(i)] = GETFPS(i)
number_sources = len(args) - 2
print("Numero de fuentes :", number_sources)
global folder_name
folder_name = args[-1]
print(folder_name)
if path.exists(folder_name):
sys.stderr.write(
"The output folder %s already exists. Please remove it first.\n" %
folder_name)
sys.exit(1)
else:
os.mkdir(folder_name)
print("Frames will be saved in ", folder_name)
# Standard GStreamer initialization
GObject.threads_init()
Gst.init(None)
#Emulate reading the information from the server
'''
En este punto asumimos que ya se cargaron la funente es decir video o rtsp etc y los valorres se cargaron
en un dictionario global o las variables ya se cargaron en dictionarios que corresponden a las fuentes con
sus respectivas configuraciones.
En este caso no hay diferentes solo leer y buscar y comparar se puede hacer directamente llamando a las
funcciones en la biblioteca
De la misma forma los rostros que se quieran cargar puedes cargarse por configuracion indicando explicitamente
los nombres de los archivos
'''
#scfg = biblio.get_server_info()
#print(scfg)
#quit()
camera_id = 'FA:KE:MA:C:AD:DR:ES:S9'
set_action(camera_id, 'read')
set_action(camera_id, 'find')
action = get_action(camera_id)
pwd = os.getcwd()
if action == action_types['read']:
output_db_name = pwd + '/data/video_encoded_faces/test_video_default.data'
total, encodings, metadata = 0, [], []
elif action == action_types['find']:
output_db_name = pwd + '/data/found_faces/found_faces_db.dat'
known_faces_db_name = pwd + '/data/encoded_known_faces/knownFaces.dat'
if com.file_exists(known_faces_db_name):
set_known_faces_db_name(camera_id, known_faces_db_name)
total, encodings, metadata = biblio.read_pickle(
get_known_faces_db_name(camera_id), False)
else:
com.log_error('Unable to open {}'.format(known_faces_db_name))
set_known_faces_db(camera_id, total, encodings, metadata)
set_output_db_name(camera_id, output_db_name)
# Create gstreamer elements */
# Create Pipeline element that will form a connection of other elements
print("Creating Pipeline \n ")
pipeline = Gst.Pipeline()
is_live = False
if not pipeline:
sys.stderr.write(" Unable to create Pipeline \n")
print("Creating streamux \n ")
# Create nvstreammux instance to form batches from one or more sources.
streammux = Gst.ElementFactory.make("nvstreammux", "Stream-muxer")
if not streammux:
sys.stderr.write(" Unable to create NvStreamMux \n")
pipeline.add(streammux)
for i in range(number_sources):
os.mkdir(folder_name + "/stream_" + str(i))
frame_count["stream_" + str(i)] = 0
saved_count["stream_" + str(i)] = 0
print("Creating source_bin ", i, " \n ")
uri_name = args[i + 1]
if uri_name.find("rtsp://") == 0:
is_live = True
source_bin = create_source_bin(i, uri_name)
if not source_bin:
sys.stderr.write("Unable to create source bin \n")
pipeline.add(source_bin)
padname = "sink_%u" % i
sinkpad = streammux.get_request_pad(padname)
if not sinkpad:
sys.stderr.write("Unable to create sink pad bin \n")
srcpad = source_bin.get_static_pad("src")
if not srcpad:
sys.stderr.write("Unable to create src pad bin \n")
srcpad.link(sinkpad)
print("Creating Pgie \n ")
pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
if not pgie:
sys.stderr.write(" Unable to create pgie \n")
# Creation of tracking to follow up the model face
# April 21th
# ERM
tracker = Gst.ElementFactory.make("nvtracker", "tracker")
if not tracker:
sys.stderr.write(" Unable to create tracker \n")
# Add nvvidconv1 and filter1 to convert the frames to RGBA
# which is easier to work with in Python.
print("Creating nvvidconv1 \n ")
nvvidconv1 = Gst.ElementFactory.make("nvvideoconvert", "convertor1")
if not nvvidconv1:
sys.stderr.write(" Unable to create nvvidconv1 \n")
print("Creating filter1 \n ")
caps1 = Gst.Caps.from_string("video/x-raw(memory:NVMM), format=RGBA")
filter1 = Gst.ElementFactory.make("capsfilter", "filter1")
if not filter1:
sys.stderr.write(" Unable to get the caps filter1 \n")
filter1.set_property("caps", caps1)
print("Creating tiler \n ")
tiler = Gst.ElementFactory.make("nvmultistreamtiler", "nvtiler")
if not tiler:
sys.stderr.write(" Unable to create tiler \n")
print("Creating nvvidconv \n ")
nvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")
if not nvvidconv:
sys.stderr.write(" Unable to create nvvidconv \n")
print("Creating nvosd \n ")
nvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")
if not nvosd:
sys.stderr.write(" Unable to create nvosd \n")
if (is_aarch64()):
print("Creating transform \n ")
transform = Gst.ElementFactory.make("nvegltransform",
"nvegl-transform")
if not transform:
sys.stderr.write(" Unable to create transform \n")
print("Creating EGLSink \n")
# edgar: cambio esta linea para no desplegar video -
#sink = Gst.ElementFactory.make("nveglglessink", "nvvideo-renderer")
sink = Gst.ElementFactory.make("fakesink", "fakesink")
if not sink:
sys.stderr.write(" Unable to create egl sink \n")
if is_live:
print("Atleast one of the sources is live")
streammux.set_property('live-source', 1)
# Camaras meraki 720p
#streammux.set_property('width', 1920)
streammux.set_property('width', 1280)
#streammux.set_property('height', 1080)
streammux.set_property('height', 720)
streammux.set_property('batch-size', number_sources)
streammux.set_property('batched-push-timeout', 4000000)
print('CURRENT_DIR', CURRENT_DIR)
pgie.set_property('config-file-path',
CURRENT_DIR + "/configs/pgie_config_facenet.txt")
pgie_batch_size = pgie.get_property("batch-size")
if (pgie_batch_size != number_sources):
print("WARNING: Overriding infer-config batch-size", pgie_batch_size,
" with number of sources ", number_sources, " \n")
pgie.set_property("batch-size", number_sources)
# Set properties of tracker
# April 21th
# ERM
config = configparser.ConfigParser()
config.read('configs/tracker_config.txt')
config.sections()
for key in config['tracker']:
if key == 'tracker-width':
tracker_width = config.getint('tracker', key)
tracker.set_property('tracker-width', tracker_width)
elif key == 'tracker-height':
tracker_height = config.getint('tracker', key)
tracker.set_property('tracker-height', tracker_height)
elif key == 'gpu-id':
tracker_gpu_id = config.getint('tracker', key)
tracker.set_property('gpu_id', tracker_gpu_id)
elif key == 'll-lib-file':
tracker_ll_lib_file = config.get('tracker', key)
tracker.set_property('ll-lib-file', tracker_ll_lib_file)
elif key == 'll-config-file':
tracker_ll_config_file = config.get('tracker', key)
tracker.set_property('ll-config-file', tracker_ll_config_file)
elif key == 'enable-batch-process':
tracker_enable_batch_process = config.getint('tracker', key)
tracker.set_property('enable_batch_process',
tracker_enable_batch_process)
tiler_rows = int(math.sqrt(number_sources))
tiler_columns = int(math.ceil((1.0 * number_sources) / tiler_rows))
tiler.set_property("rows", tiler_rows)
tiler.set_property("columns", tiler_columns)
tiler.set_property("width", TILED_OUTPUT_WIDTH)
tiler.set_property("height", TILED_OUTPUT_HEIGHT)
sink.set_property("sync", 0)
if not is_aarch64():
# Use CUDA unified memory in the pipeline so frames
# can be easily accessed on CPU in Python.
mem_type = int(pyds.NVBUF_MEM_CUDA_UNIFIED)
streammux.set_property("nvbuf-memory-type", mem_type)
nvvidconv.set_property("nvbuf-memory-type", mem_type)
nvvidconv1.set_property("nvbuf-memory-type", mem_type)
tiler.set_property("nvbuf-memory-type", mem_type)
print("Adding elements to Pipeline \n")
# Add tracker in pipeline
# April 21th
# ERM
pipeline.add(pgie)
pipeline.add(tracker) # Tracker
pipeline.add(tiler)
pipeline.add(nvvidconv)
pipeline.add(filter1)
pipeline.add(nvvidconv1)
pipeline.add(nvosd)
if is_aarch64():
pipeline.add(transform)
pipeline.add(sink)
print("Linking elements in the Pipeline \n")
streammux.link(pgie)
pgie.link(tracker) # se añade para tracker
# pgie.link(nvvidconv1) se modifica
tracker.link(
nvvidconv1) # se añade para ligar tracker con los demas elementos
nvvidconv1.link(filter1)
filter1.link(tiler)
tiler.link(nvvidconv)
nvvidconv.link(nvosd)
if is_aarch64():
nvosd.link(transform)
transform.link(sink)
else:
nvosd.link(sink)
# create an event loop and feed gstreamer bus mesages to it
loop = GObject.MainLoop()
bus = pipeline.get_bus()
bus.add_signal_watch()
bus.connect("message", bus_call, loop)
#tiler_sink_pad=tiler.get_static_pad("sink")
#if not tiler_sink_pad:
# sys.stderr.write(" Unable to get src pad \n")
#else:
# tiler_sink_pad.add_probe(Gst.PadProbeType.BUFFER, tiler_sink_pad_buffer_probe, 0)
tiler_src_pad = tiler.get_static_pad("src")
if not tiler_src_pad:
sys.stderr.write(" Unable to get src pad \n")
else:
tiler_src_pad.add_probe(Gst.PadProbeType.BUFFER,
tiler_src_pad_buffer_probe, 0)
# List the sources
print("Now playing...")
for i, source in enumerate(args[:-1]):
if (i != 0):
print(i, ": ", source)
print("Starting pipeline \n")
# start play back and listed to events
pipeline.set_state(Gst.State.PLAYING)
try:
loop.run()
except:
pass
# cleanup
print("Exiting app\n")
pipeline.set_state(Gst.State.NULL)
