def main_handler():
# set up logging to syslog
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument('-c', '--config', help='config file with path')
ap.add_argument('-e', '--eventid', help='event ID to retrieve')
ap.add_argument('-p',
'--eventpath',
help='path to store object image file',
default='')
ap.add_argument('-m', '--monitorid', help='monitor id - needed for mask')
ap.add_argument('-v',
'--version',
help='print version and quit',
action='store_true')
ap.add_argument('-o', '--output-path',
help='internal testing use only - path for debug images to be written')
ap.add_argument('-f',
'--file',
help='internal testing use only - skips event download')
ap.add_argument('-r', '--reason', help='reason for event (notes field in ZM)')
ap.add_argument('-n', '--notes', help='updates notes field in ZM with detections', action='store_true')
ap.add_argument('-d', '--debug', help='enables debug on console', action='store_true')
args, u = ap.parse_known_args()
args = vars(args)
if args.get('version'):
print('hooks:{} pyzm:{}'.format(hooks_version, pyzm_version))
exit(0)
if not args.get('config'):
print ('--config required')
exit(1)
if not args.get('file')and not args.get('eventid'):
print ('--eventid required')
exit(1)
utils.get_pyzm_config(args)
if args.get('debug'):
g.config['pyzm_overrides']['dump_console'] = True
g.config['pyzm_overrides']['log_debug'] = True
g.config['pyzm_overrides']['log_level_debug'] = 5
g.config['pyzm_overrides']['log_debug_target'] = None
if args.get('monitorid'):
log.init(name='zmesdetect_' + 'm' + args.get('monitorid'), override=g.config['pyzm_overrides'])
else:
log.init(name='zmesdetect',override=g.config['pyzm_overrides'])
g.logger = log
es_version='(?)'
try:
es_version=subprocess.check_output(['/usr/bin/zmeventnotification.pl', '--version']).decode('ascii')
except:
pass
try:
import cv2
except ImportError as e:
g.logger.Fatal (f'{e}: You might not have installed OpenCV as per install instructions. Remember, it is NOT automatically installed')
g.logger.Info('---------| pyzm version:{}, hook version:{}, ES version:{} , OpenCV version:{}|------------'.format(pyzm_version, hooks_version, es_version, cv2.__version__))
# load modules that depend on cv2
try:
import zmes_hook_helpers.image_manip as img
except Exception as e:
g.logger.Error (f'{e}')
exit(1)
g.polygons = []
# process config file
g.ctx = ssl.create_default_context()
utils.process_config(args, g.ctx)
# misc came later, so lets be safe
if not os.path.exists(g.config['base_data_path'] + '/misc/'):
try:
os.makedirs(g.config['base_data_path'] + '/misc/')
except FileExistsError:
pass # if two detects run together with a race here
if not g.config['ml_gateway']:
g.logger.Info('Importing local classes for Object/Face')
import pyzm.ml.object as object_detection
else:
g.logger.Info('Importing remote shim classes for Object/Face')
from zmes_hook_helpers.apigw import ObjectRemote, FaceRemote, AlprRemote
# now download image(s)
start = datetime.datetime.now()
obj_json = []
import pyzm.api as zmapi
api_options = {
'apiurl': g.config['api_portal'],
'portalurl': g.config['portal'],
'user': g.config['user'],
'password': g.config['password'] ,
'logger': g.logger, # use none if you don't want to log to ZM,
#'disable_ssl_cert_check': True
}
g.logger.Info('Connecting with ZM APIs')
zmapi = zmapi.ZMApi(options=api_options)
stream = args.get('eventid') or args.get('file')
ml_options = {}
stream_options={}
secrets = None
if g.config['ml_sequence'] and g.config['use_sequence'] == 'yes':
g.logger.Debug(2,'using ml_sequence')
ml_options = g.config['ml_sequence']
secrets = pyzmutils.read_config(g.config['secrets'])
ml_options = pyzmutils.template_fill(input_str=ml_options, config=None, secrets=secrets._sections.get('secrets'))
ml_options = ast.literal_eval(ml_options)
g.config['ml_sequence'] = ml_options
else:
g.logger.Debug(2,'mapping legacy ml data from config')
ml_options = utils.convert_config_to_ml_sequence()
if g.config['stream_sequence'] and g.config['use_sequence'] == 'yes': # new sequence
g.logger.Debug(2,'using stream_sequence')
stream_options = g.config['stream_sequence']
stream_options = ast.literal_eval(stream_options)
g.config['stream_sequence'] = stream_options
else: # legacy
g.logger.Debug(2,'mapping legacy stream data from config')
if g.config['detection_mode'] == 'all':
g.config['detection_mode'] = 'most_models'
frame_set = g.config['frame_id']
if g.config['frame_id'] == 'bestmatch':
if g.config['bestmatch_order'] == 's,a':
frame_set = 'snapshot,alarm'
else:
frame_set = 'alarm,snapshot'
stream_options['resize'] =int(g.config['resize']) if g.config['resize'] != 'no' else None
stream_options['strategy'] = g.config['detection_mode']
stream_options['frame_set'] = frame_set
# These are stream options that need to be set outside of supplied configs
stream_options['api'] = zmapi
stream_options['polygons'] = g.polygons
'''
stream_options = {
'api': zmapi,
'download': False,
'frame_set': frame_set,
'strategy': g.config['detection_mode'],
'polygons': g.polygons,
'resize': int(g.config['resize']) if g.config['resize'] != 'no' else None
}
'''
m = None
matched_data = None
all_data = None
if not args['file'] and int(g.config['wait']) > 0:
g.logger.Info('Sleeping for {} seconds before inferencing'.format(
g.config['wait']))
time.sleep(g.config['wait'])
if g.config['ml_gateway']:
stream_options['api'] = None
stream_options['monitorid'] = args.get('monitorid')
start = datetime.datetime.now()
try:
matched_data,all_data = remote_detect(stream=stream, options=stream_options, api=zmapi)
diff_time = (datetime.datetime.now() - start)
g.logger.Debug(1,'Total remote detection detection took: {}'.format(diff_time))
except Exception as e:
g.logger.Error ("Error with remote mlapi:{}".format(e))
g.logger.Debug(2,traceback.format_exc())
if g.config['ml_fallback_local'] == 'yes':
g.logger.Debug (1, "Falling back to local detection")
stream_options['api'] = zmapi
from pyzm.ml.detect_sequence import DetectSequence
m = DetectSequence(options=ml_options, logger=g.logger)
matched_data,all_data = m.detect_stream(stream=stream, options=stream_options)
else:
from pyzm.ml.detect_sequence import DetectSequence
m = DetectSequence(options=ml_options, logger=g.logger)
matched_data,all_data = m.detect_stream(stream=stream, options=stream_options)
#print(f'ALL FRAMES: {all_data}\n\n')
#print (f"SELECTED FRAME {matched_data['frame_id']}, size {matched_data['image_dimensions']} with LABELS {matched_data['labels']} {matched_data['boxes']} {matched_data['confidences']}")
#print (matched_data)
'''
matched_data = {
'boxes': matched_b,
'labels': matched_l,
'confidences': matched_c,
'frame_id': matched_frame_id,
'image_dimensions': self.media.image_dimensions(),
'image': matched_frame_img
}
'''
# let's remove past detections first, if enabled
if g.config['match_past_detections'] == 'yes' and args.get('monitorid'):
# point detections to post processed data set
g.logger.Info('Removing matches to past detections')
bbox_t, label_t, conf_t = img.processPastDetection(
matched_data['boxes'], matched_data['labels'], matched_data['confidences'], args.get('monitorid'))
# save current objects for future comparisons
g.logger.Debug(1,
'Saving detections for monitor {} for future match'.format(
args.get('monitorid')))
try:
mon_file = g.config['image_path'] + '/monitor-' + args.get(
'monitorid') + '-data.pkl'
f = open(mon_file, "wb")
pickle.dump(matched_data['boxes'], f)
pickle.dump(matched_data['labels'], f)
pickle.dump(matched_data['confidences'], f)
f.close()
except Exception as e:
g.logger.Error(f'Error writing to {mon_file}, past detections not recorded:{e}')
matched_data['boxes'] = bbox_t
matched_data['labels'] = label_t
matched_data['confidences'] = conf_t
obj_json = {
'labels': matched_data['labels'],
'boxes': matched_data['boxes'],
'frame_id': matched_data['frame_id'],
'confidences': matched_data['confidences'],
'image_dimensions': matched_data['image_dimensions']
}
# 'confidences': ["{:.2f}%".format(item * 100) for item in matched_data['confidences']],
detections = []
seen = {}
pred=''
prefix = ''
if matched_data['frame_id'] == 'snapshot':
prefix = '[s] '
elif matched_data['frame_id'] == 'alarm':
prefix = '[a] '
else:
prefix = '[x] '
#g.logger.Debug (1,'CONFIDENCE ARRAY:{}'.format(conf))
for idx, l in enumerate(matched_data['labels']):
if l not in seen:
if g.config['show_percent'] == 'no':
pred = pred + l + ','
else:
pred = pred + l + ':{:.0%}'.format(matched_data['confidences'][idx]) + ' '
seen[l] = 1
if pred != '':
pred = pred.rstrip(',')
pred = prefix + 'detected:' + pred
g.logger.Info('Prediction string:{}'.format(pred))
jos = json.dumps(obj_json)
g.logger.Debug(1,'Prediction string JSON:{}'.format(jos))
print(pred + '--SPLIT--' + jos)
if (matched_data['image'] is not None) and (g.config['write_image_to_zm'] == 'yes' or g.config['write_debug_image'] == 'yes'):
debug_image = pyzmutils.draw_bbox(image=matched_data['image'],boxes=matched_data['boxes'],
labels=matched_data['labels'], confidences=matched_data['confidences'],
polygons=g.polygons, poly_thickness = g.config['poly_thickness'])
if g.config['write_debug_image'] == 'yes':
for _b in matched_data['error_boxes']:
cv2.rectangle(debug_image, (_b[0], _b[1]), (_b[2], _b[3]),
(0,0,255), 1)
filename_debug = g.config['image_path']+'/'+os.path.basename(append_suffix(stream, '-{}-debug'.format(matched_data['frame_id'])))
g.logger.Debug (1,'Writing bound boxes to debug image: {}'.format(filename_debug))
cv2.imwrite(filename_debug,debug_image)
if g.config['write_image_to_zm'] == 'yes' and args.get('eventpath'):
g.logger.Debug(1,'Writing detected image to {}/objdetect.jpg'.format(
args.get('eventpath')))
cv2.imwrite(args.get('eventpath') + '/objdetect.jpg', debug_image)
jf = args.get('eventpath')+ '/objects.json'
g.logger.Debug(1,'Writing JSON output to {}'.format(jf))
try:
with open(jf, 'w') as jo:
json.dump(obj_json, jo)
jo.close()
except Exception as e:
g.logger.Error(f'Error creating {jf}:{e}')
if args.get('notes'):
url = '{}/events/{}.json'.format(g.config['api_portal'], args['eventid'])
try:
ev = zmapi._make_request(url=url, type='get')
except Exception as e:
g.logger.Error ('Error during event notes retrieval: {}'.format(str(e)))
g.logger.Debug(2,traceback.format_exc())
exit(0) # Let's continue with zmdetect
new_notes = pred
if ev.get('event',{}).get('Event',{}).get('Notes'):
old_notes = ev['event']['Event']['Notes']
old_notes_split = old_notes.split('Motion:')
old_d = old_notes_split[0] # old detection
try:
old_m = old_notes_split[1]
except IndexError:
old_m = ''
new_notes = pred + 'Motion:'+ old_m
g.logger.Debug (1,'Replacing old note:{} with new note:{}'.format(old_notes, new_notes))
payload = {}
payload['Event[Notes]'] = new_notes
try:
ev = zmapi._make_request(url=url, payload=payload, type='put')
except Exception as e:
g.logger.Error ('Error during notes update: {}'.format(str(e)))
g.logger.Debug(2,traceback.format_exc())
if g.config['create_animation'] == 'yes':
if not args.get('eventid'):
g.logger.Error ('Cannot create animation as you did not pass an event ID')
else:
g.logger.Debug(1,'animation: Creating burst...')
try:
img.createAnimation(matched_data['frame_id'], args.get('eventid'), args.get('eventpath')+'/objdetect', g.config['animation_types'])
except Exception as e:
g.logger.Error('Error creating animation:{}'.format(e))
g.logger.Error('animation: Traceback:{}'.format(traceback.format_exc()))
def main_handler():
# set up logging to syslog
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument('-c', '--config', help='config file with path')
ap.add_argument('-e', '--eventid', help='event ID to retrieve')
ap.add_argument('-p',
'--eventpath',
help='path to store object image file',
default='')
ap.add_argument('-m', '--monitorid', help='monitor id - needed for mask')
ap.add_argument('-v',
'--version',
help='print version and quit',
action='store_true')
ap.add_argument(
'-o',
'--output-path',
help='internal testing use only - path for debug images to be written')
ap.add_argument('-f',
'--file',
help='internal testing use only - skips event download')
ap.add_argument('-r',
'--reason',
help='reason for event (notes field in ZM)')
ap.add_argument('-n',
'--notes',
help='updates notes field in ZM with detections',
action='store_true')
ap.add_argument('-d',
'--debug',
help='enables debug on console',
action='store_true')
args, u = ap.parse_known_args()
args = vars(args)
if args.get('version'):
print('hooks:{} pyzm:{}'.format(hooks_version, pyzm_version))
exit(0)
if not args.get('config'):
print('--config required')
exit(1)
if not args.get('file') and not args.get('eventid'):
print('--eventid required')
exit(1)
utils.get_pyzm_config(args)
if args.get('debug'):
g.config['pyzm_overrides']['dump_console'] = True
g.config['pyzm_overrides']['log_debug'] = True
g.config['pyzm_overrides']['log_level_debug'] = 5
g.config['pyzm_overrides']['log_debug_target'] = None
if args.get('monitorid'):
log.init(name='zmesdetect_' + 'm' + args.get('monitorid'),
override=g.config['pyzm_overrides'])
else:
log.init(name='zmesdetect', override=g.config['pyzm_overrides'])
g.logger = log
es_version = '(?)'
try:
es_version = subprocess.check_output(
['/usr/bin/zmeventnotification.pl', '--version']).decode('ascii')
except:
pass
try:
import cv2
except ImportError as e:
g.logger.Fatal(
f'{e}: You might not have installed OpenCV as per install instructions. Remember, it is NOT automatically installed'
)
g.logger.Info(
'---------| pyzm version:{}, hook version:{}, ES version:{} , OpenCV version:{}|------------'
.format(pyzm_version, hooks_version, es_version, cv2.__version__))
# load modules that depend on cv2
try:
import zmes_hook_helpers.image_manip as img
except Exception as e:
g.logger.Error(f'{e}')
exit(1)
g.polygons = []
# process config file
g.ctx = ssl.create_default_context()
utils.process_config(args, g.ctx)
# misc came later, so lets be safe
if not os.path.exists(g.config['base_data_path'] + '/misc/'):
try:
os.makedirs(g.config['base_data_path'] + '/misc/')
except FileExistsError:
pass # if two detects run together with a race here
if not g.config['ml_gateway']:
g.logger.Info('Importing local classes for Object/Face')
import pyzm.ml.object as object_detection
import pyzm.ml.hog as hog
else:
g.logger.Info('Importing remote shim classes for Object/Face')
from zmes_hook_helpers.apigw import ObjectRemote, FaceRemote, AlprRemote
# now download image(s)
start = datetime.datetime.now()
obj_json = []
from pyzm.ml.detect_sequence import DetectSequence
import pyzm.api as zmapi
api_options = {
'apiurl': g.config['api_portal'],
'portalurl': g.config['portal'],
'user': g.config['user'],
'password': g.config['password'],
'logger': g.logger, # use none if you don't want to log to ZM,
#'disable_ssl_cert_check': True
}
zmapi = zmapi.ZMApi(options=api_options)
stream = args.get('eventid') or args.get('file')
ml_options = {
'general': {
'model_sequence': 'object,face,alpr',
#'model_sequence': 'object,face',
},
'object': {
'general': {
'same_model_sequence_strategy':
'first' # 'first' 'most', 'most_unique'
},
'sequence': [
{
#First run on TPU
'max_detection_size': g.config['max_detection_size'],
'object_weights':
'/var/lib/zmeventnotification/models/coral_edgetpu/ssd_mobilenet_v2_coco_quant_postprocess_edgetpu.tflite',
'object_labels':
'/var/lib/zmeventnotification/models/coral_edgetpu/coco_indexed.names',
'object_min_confidence': 0.3,
'object_framework': 'coral_edgetpu'
},
{
# YoloV4 on GPU if TPU fails (because sequence strategy is 'first')
'max_detection_size': g.config['max_detection_size'],
'object_config':
'/var/lib/zmeventnotification/models/yolov4/yolov4.cfg',
'object_weights':
'/var/lib/zmeventnotification/models/yolov4/yolov4.weights',
'object_labels':
'/var/lib/zmeventnotification/models/yolov4/coco.names',
'object_min_confidence': 0.3,
'object_framework': 'opencv',
'object_processor': 'gpu'
}
]
},
'face': {
'general': {
'same_model_sequence_strategy': 'first'
},
'sequence': [{
'face_detection_framework': 'dlib',
'known_images_path':
'/var/lib/zmeventnotification/known_faces',
'face_model': 'cnn',
'face_train_model': 'cnn',
'face_recog_dist_threshold': 0.6,
'face_num_jitters': 1,
'face_upsample_times': 1
}]
},
'alpr': {
'general': {
'same_model_sequence_strategy':
'first',
'pre_existing_labels':
['car', 'motorbike', 'bus', 'truck', 'boat'],
},
'sequence': [{
'alpr_api_type': 'cloud',
'alpr_service': 'plate_recognizer',
'alpr_key': g.config['alpr_key'],
'platrec_stats': 'no',
'platerec_min_dscore': 0.1,
'platerec_min_score': 0.2,
}]
}
} # ml_options
stream_options = {
'api': zmapi,
'download': False,
'frame_set': 'alarm,snapshot',
'strategy': 'most_models',
'polygons': g.polygons,
'resize':
int(g.config['resize']) if g.config['resize'] != 'no' else None
}
m = DetectSequence(options=ml_options, logger=g.logger)
matched_data, all_data = m.detect_stream(stream=stream,
options=stream_options)
#print(f'ALL FRAMES: {all_data}\n\n')
#print (f"SELECTED FRAME {matched_data['frame_id']}, size {matched_data['image_dimensions']} with LABELS {matched_data['labels']} {matched_data['boxes']} {matched_data['confidences']}")
'''
matched_data = {
'boxes': matched_b,
'labels': matched_l,
'confidences': matched_c,
'frame_id': matched_frame_id,
'image_dimensions': self.media.image_dimensions(),
'image': matched_frame_img
}
'''
# let's remove past detections first, if enabled
if g.config['match_past_detections'] == 'yes' and args.get('monitorid'):
# point detections to post processed data set
g.logger.Info('Removing matches to past detections')
bbox_t, label_t, conf_t = img.processPastDetection(
matched_data['boxes'], matched_data['labels'],
matched_data['confidences'], args.get('monitorid'))
# save current objects for future comparisons
g.logger.Debug(
1, 'Saving detections for monitor {} for future match'.format(
args.get('monitorid')))
try:
mon_file = g.config['image_path'] + '/monitor-' + args.get(
'monitorid') + '-data.pkl'
f = open(mon_file, "wb")
pickle.dump(matched_data['boxes'], f)
pickle.dump(matched_data['labels'], f)
pickle.dump(matched_data['confidences'], f)
f.close()
except Exception as e:
g.logger.Error(
f'Error writing to {mon_file}, past detections not recorded:{e}'
)
matched_data['boxes'] = bbox_t
matched_data['labels'] = label_t
matched_data['confidences'] = conf_t
obj_json = {
'labels': matched_data['labels'],
'boxes': matched_data['boxes'],
'frame_id': matched_data['frame_id'],
'confidences': matched_data['confidences'],
'image_dimensions': matched_data['image_dimensions']
}
# 'confidences': ["{:.2f}%".format(item * 100) for item in matched_data['confidences']],
detections = []
seen = {}
pred = ''
prefix = ''
if matched_data['frame_id'] == 'snapshot':
prefix = '[s] '
elif matched_data['frame_id'] == 'alarm':
prefix = '[a] '
else:
prefix = '[x] '
#g.logger.Debug (1,'CONFIDENCE ARRAY:{}'.format(conf))
for idx, l in enumerate(matched_data['labels']):
if l not in seen:
if g.config['show_percent'] == 'no':
pred = pred + l + ','
else:
pred = pred + l + ':{:.0%}'.format(
matched_data['confidences'][idx]) + ' '
seen[l] = 1
if pred != '':
pred = pred.rstrip(',')
pred = prefix + 'detected:' + pred
g.logger.Info('Prediction string:{}'.format(pred))
jos = json.dumps(obj_json)
g.logger.Debug(1, 'Prediction string JSON:{}'.format(jos))
print(pred + '--SPLIT--' + jos)
if g.config['write_image_to_zm'] == 'yes' or g.config[
'write_debug_image'] == 'yes':
debug_image = pyzmutils.draw_bbox(
image=matched_data['image'],
boxes=matched_data['boxes'],
labels=matched_data['labels'],
confidences=matched_data['confidences'],
polygons=g.polygons,
poly_thickness=g.config['poly_thickness'])
if g.config['write_debug_image'] == 'yes':
filename_debug = g.config[
'image_path'] + '/' + os.path.basename(
append_suffix(
stream, '-{}-debug'.format(
matched_data['frame_id'])))
g.logger.Debug(
1, 'Writing bound boxes to debug image: {}'.format(
filename_debug))
cv2.imwrite(filename_debug, debug_image)
if g.config['write_image_to_zm'] == 'yes' and args.get(
'eventpath'):
g.logger.Debug(
1, 'Writing detected image to {}/objdetect.jpg'.format(
args.get('eventpath')))
cv2.imwrite(
args.get('eventpath') + '/objdetect.jpg', debug_image)
jf = args.get('eventpath') + '/objects.json'
g.logger.Debug(1, 'Writing JSON output to {}'.format(jf))
try:
with open(jf, 'w') as jo:
json.dump(obj_json, jo)
jo.close()
except Exception as e:
g.logger.Error(f'Error creating {jf}:{e}')
if args.get('notes'):
url = '{}/events/{}.json'.format(g.config['api_portal'],
args['eventid'])
try:
ev = zmapi._make_request(url=url, type='get')
except Exception as e:
g.logger.Error('Error during event notes retrieval: {}'.format(
str(e)))
g.logger.Debug(2, traceback.format_exc())
exit(0) # Let's continue with zmdetect
new_notes = pred
if ev.get('event', {}).get('Event', {}).get('Notes'):
old_notes = ev['event']['Event']['Notes']
old_notes_split = old_notes.split('Motion:')
old_d = old_notes_split[0] # old detection
try:
old_m = old_notes_split[1]
except IndexError:
old_m = ''
new_notes = pred + 'Motion:' + old_m
g.logger.Debug(
1, 'Replacing old note:{} with new note:{}'.format(
old_notes, new_notes))
payload = {}
payload['Event[Notes]'] = new_notes
try:
ev = zmapi._make_request(url=url, payload=payload, type='put')
except Exception as e:
g.logger.Error('Error during notes update: {}'.format(str(e)))
g.logger.Debug(2, traceback.format_exc())
if g.config['create_animation'] == 'yes':
g.logger.Debug(1, 'animation: Creating burst...')
try:
img.createAnimation(matched_data['frame_id'],
args.get('eventid'),
args.get('eventpath') + '/objdetect',
g.config['animation_types'])
except Exception as e:
g.logger.Error('Error creating animation:{}'.format(e))
g.logger.Error('animation: Traceback:{}'.format(
traceback.format_exc()))
