Hoping somebody can point me in the right direction, having issues with facial recognition. I've tried everything I can think of and google isn't being very helpful. Object Detection seems to working fine. Debug log below. Any help much appreciated.
The Error seems to be: ERR detect_sequence.py:713 [Error running model: compute_face_descriptor(): incompatible function arguments. The following argument types are supported:
Then some arguments. I can't find anything to amend in detect_sequence.py, though admittedly very much outside of my comfort zone.
Nick
Code: Select all
sudo -u www-data /var/lib/zmeventnotification/bin/zm_detect.py --config /etc/zm/objectconfig.ini --debug --eventid 1292 --monitorid 1 --eventpath=/tmp
06/11/23 13:09:52 zmesdetect_m1[79485] INF ZMLog.py:292 [Setting up signal handler for logs]
06/11/23 13:09:52 zmesdetect_m1[79485] INF ZMLog.py:301 [Switching global logger to ZMLog]
06/11/23 13:09:52 zmesdetect_m1[79485] INF zm_detect.py:284 [---------| app:6.1.28, pyzm:0.3.59, ES:6.1.28
, OpenCV:4.7.0-dev|------------]
06/11/23 13:09:52 zmesdetect_m1[79485] INF utils.py:405 [Reading config from: /etc/zm/objectconfig.ini]
06/11/23 13:09:52 zmesdetect_m1[79485] INF utils.py:410 [Reading secrets from: /etc/zm/secrets.ini]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !ZM_PORTAL]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !ZM_USER]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !ZM_PASSWORD]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !ZM_API_PORTAL]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !ML_USER]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !ML_PASSWORD]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:382 [Secret token found in config: !PLATEREC_ALPR_KEY]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG1 utils.py:445 [allowing self-signed certs to work...]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG2 utils.py:455 [Now checking for monitor overrides]
06/11/23 13:09:52 zmesdetect_m1[79485] DBG3 utils.py:522 [Finally, doing parameter substitution]
06/11/23 13:09:52 zmesdetect_m1[79485] INF zm_detect.py:309 [Importing local classes for Object/Face]
06/11/23 13:09:53 zmesdetect_m1[79485] INF zm_detect.py:334 [Connecting with ZM APIs]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 api.py:69 [API SSL certificate check has been disbled]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 api.py:173 [using username/password for login]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 api.py:202 [Using new token API]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 zm_detect.py:342 [using ml_sequence]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 zm_detect.py:354 [using stream_sequence]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 detect_sequence.py:160 [Resetting models, will be loaded on next run]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG3 detect_sequence.py:634 [Using automatic locking as we are switching between models]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 Media.py:51 [Media get SSL certificate check has been disbled]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 Media.py:99 [Using URL 1292 for stream]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 Media.py:114 [We will only process frames: ['snapshot', 'alarm']]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 Media.py:137 [No need to start streams, we are picking images from http://zmserver/zm/index.php?view=image&eid=1292]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG3 Media.py:271 [Reading http://zmserver/zm/index.php?view=image&eid=1292&fid=snapshot]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG3 api.py:263 [make_request called with url=http://zmserver/zm/index.php?view=image&eid=1292&fid=snapshot payload={} type=get query={'token': None}]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 detect_sequence.py:654 [perf: Starting for frame:snapshot]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 detect_sequence.py:664 [Sequence of detection types to execute: ['object', 'face', 'alpr']]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 detect_sequence.py:669 [============ Frame: snapshot Running object detection type in sequence ==================]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 detect_sequence.py:174 [Skipping TPU object detection as it is disabled]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 detect_sequence.py:178 [Loading sequence: YoloV4 GPU/CPU]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 detect_sequence.py:179 [Initializing model type:object with options:{'name': 'YoloV4 GPU/CPU', 'enabled': 'yes', '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', 'gpu_max_processes': 1, 'gpu_max_lock_wait': 100, 'cpu_max_processes': 3, 'cpu_max_lock_wait': 100, 'max_detection_size': '70%', 'disable_locks': 'no'}]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 yolo.py:54 [portalock: max:1, name:pyzm_uid33_gpu_lock, timeout:100]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG3 detect_sequence.py:689 [object has a same_model_sequence strategy of first]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 detect_sequence.py:701 [--------- Frame:snapshot Running variation: #1 -------------]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 yolo.py:152 [detect extracted image dimensions as: 800wx450h]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 yolo.py:68 [Waiting for pyzm_uid33_gpu_lock portalock...]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 yolo.py:70 [Got pyzm_uid33_gpu_lock portalock]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 yolo.py:102 [|--------- Loading "YoloV4 GPU/CPU" model from disk -------------|]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 yolo.py:113 [You are using OpenCV >= 4.5.4, making sure we fix getUnconnectedOutLayers() API]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 yolo.py:115 [perf: processor:gpu Yolo initialization (loading /var/lib/zmeventnotification/models/yolov4/yolov4.weights model from disk) took: 131.00 ms]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG2 yolo.py:130 [Setting CUDA backend for OpenCV]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG3 yolo.py:131 [If you did not set your CUDA_ARCH_BIN correctly during OpenCV compilation, you will get errors during detection related to invalid device/make_policy]
06/11/23 13:09:53 zmesdetect_m1[79485] DBG1 yolo.py:175 [|---------- YOLO (input image: 800w*450h, model resize dimensions: 416w*416h) ----------|]
[ WARN:0@1.779] global net_impl.cpp:174 setUpNet DNN module was not built with CUDA backend; switching to CPU
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 yolo.py:86 [Released pyzm_uid33_gpu_lock portalock]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG1 yolo.py:199 [perf: processor:gpu Yolo detection took: 2879.99 ms]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 yolo.py:233 [perf: processor:gpu Yolo NMS filtering took: 1.54 ms]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 object.py:72 [core model detection over, got 2 objects. Now filtering]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 object.py:76 [Max object size found to be: 70%]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 object.py:84 [Converted 70% to 251999.99999999997]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 object.py:109 [Returning filtered list of 2 objects.]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:711 [This model iteration inside object found: labels: ['person', 'car'],conf:[0.8788268566131592, 0.4906500279903412]]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:424 [Max object size found to be: 70%]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:432 [Converted 70% to 251999.99999999997]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:448 [No polygons, adding full image polygon: {'name': 'full_image', 'value': [(0, 0), (1280, 0), (1280, 720), (0, 720)], 'pattern': None}]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG3 detect_sequence.py:228 [resized polygons x=0.625/y=0.625: [{'name': 'full_image', 'value': [(0, 0), (800, 0), (800, 450), (0, 450)], 'pattern': None}]]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:502 [intersection: object:person,POLYGON ((516 299, 778 299, 778 449, 516 449, 516 299)) intersects polygon:full_image,POLYGON ((0 0, 800 0, 800 450, 0 450, 0 0))]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:518 [Using global match pattern: (person|car|motorbike|bus|truck|boat|dog|cat|sheep|motorcycle|bird)]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:526 [full_image intersects object:person[[(516, 299), (778, 299), (778, 449), (516, 449)]]]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:502 [intersection: object:car,POLYGON ((2 192, 674 192, 674 452, 2 452, 2 192)) intersects polygon:full_image,POLYGON ((0 0, 800 0, 800 450, 0 450, 0 0))]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:518 [Using global match pattern: (person|car|motorbike|bus|truck|boat|dog|cat|sheep|motorcycle|bird)]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:526 [full_image intersects object:car[[(2, 192), (674, 192), (674, 452), (2, 452)]]]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:753 [breaking out of same model loop, as matches found and strategy is "first"]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG1 detect_sequence.py:669 [============ Frame: snapshot Running face detection type in sequence ==================]
06/11/23 13:09:56 zmesdetect_m1[79485] DBG2 detect_sequence.py:190 [Skipping TPU face detection as it is disabled]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:42 [perf: processor:cpu Face Recognition library load time took: 0.00 ms ]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:50 [Initializing face recognition with model:hog upsample:1, jitters:0]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 face_dlib.py:73 [portalock: max:3, name:pyzm_uid33_cpu_lock, timeout:100]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:89 [pre-trained faces found, using that. If you want to add new images, remove: /var/lib/zmeventnotification/known_faces/faces.dat]
06/11/23 13:09:59 zmesdetect_m1[79485] ERR face_dlib.py:110 [Error loading KNN model: Ran out of input]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG3 detect_sequence.py:689 [face has a same_model_sequence strategy of union]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 detect_sequence.py:701 [--------- Frame:snapshot Running variation: #1 -------------]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:164 [|---------- Dlib Face recognition (input image: 800w*450h) ----------|]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG3 face_dlib.py:174 [Face options={'name': 'DLIB based face recognition', 'enabled': 'yes', 'save_unknown_faces': 'yes', 'save_unknown_faces_leeway_pixels': 100, 'face_detection_framework': 'dlib', 'known_images_path': '/var/lib/zmeventnotification/known_faces', 'unknown_images_path': '/var/lib/zmeventnotification/unknown_faces', 'face_model': 'hog', 'face_train_model': 'cnn', 'face_recog_dist_threshold': '0.6', 'face_num_jitters': '1', 'face_upsample_times': '1', 'gpu_max_processes': 1, 'gpu_max_lock_wait': 100, 'cpu_max_processes': 3, 'cpu_max_lock_wait': 100, 'max_size': 800, 'disable_locks': 'no'}]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 face_dlib.py:123 [Waiting for pyzm_uid33_cpu_lock portalock...]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 face_dlib.py:125 [Got pyzm_uid33_cpu_lock lock...]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:206 [perf: processor:cpu Finding faces took 250.10 ms]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:141 [Released pyzm_uid33_cpu_lock portalock]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 face_dlib.py:218 [perf: processor:cpu Computing face recognition distances took 0.71 ms]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 detect_sequence.py:711 [This model iteration inside face found: labels: [],conf:[]]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 detect_sequence.py:424 [Max object size found to be: 70%]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 detect_sequence.py:432 [Converted 70% to 251999.99999999997]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 detect_sequence.py:770 [We did not find any face matches in frame: snapshot]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 detect_sequence.py:669 [============ Frame: snapshot Running alpr detection type in sequence ==================]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 detect_sequence.py:672 [Making sure we have matched one of ['car', 'motorbike', 'bus', 'truck', 'boat'] in ['person', 'car'] before we proceed]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 alpr.py:24 [Initializing ALPR:Platerecognizer cloud with options:{'name': 'Platerecognizer cloud', 'enabled': 'yes', 'alpr_api_type': 'cloud', 'alpr_service': 'plate_recognizer', 'alpr_key': 'your_plate_recognizer_api_key', 'platrec_stats': 'yes', 'platerec_min_dscore': 0.1, 'platerec_min_score': 0.2, 'max_size': 1600, 'disable_locks': 'no'}]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 alpr.py:24 [Initializing ALPR:Platerecognizer cloud with options:{'name': 'Platerecognizer cloud', 'enabled': 'yes', 'alpr_api_type': 'cloud', 'alpr_service': 'plate_recognizer', 'alpr_key': 'your_plate_recognizer_api_key', 'platrec_stats': 'yes', 'platerec_min_dscore': 0.1, 'platerec_min_score': 0.2, 'max_size': 1600, 'disable_locks': 'no'}]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 alpr.py:137 [PlateRecognizer ALPR initialized with url: https://api.platerecognizer.com/v1]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG3 detect_sequence.py:689 [alpr has a same_model_sequence strategy of first]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 detect_sequence.py:701 [--------- Frame:snapshot Running variation: #1 -------------]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG1 alpr.py:50 [Supplied object is not a file, assuming blob and creating file]
06/11/23 13:09:59 zmesdetect_m1[79485] DBG2 alpr.py:54 [resizing image blob to 1600]
06/11/23 13:10:01 zmesdetect_m1[79485] ERR alpr.py:212 [Plate recognizer rejected the upload with 403 Client Error: Forbidden for url: https://api.platerecognizer.com/v1/plate-reader and body:b'{"detail":"Invalid token.","status_code":403}']
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 alpr.py:244 [Exiting ALPR with labels:[]]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 detect_sequence.py:711 [This model iteration inside alpr found: labels: [],conf:[]]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 detect_sequence.py:424 [Max object size found to be: 70%]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 detect_sequence.py:432 [Converted 70% to 251999.99999999997]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 detect_sequence.py:770 [We did not find any alpr matches in frame: snapshot]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG3 Media.py:271 [Reading http://zmserver/zm/index.php?view=image&eid=1292&fid=alarm]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG3 api.py:263 [make_request called with url=http://zmserver/zm/index.php?view=image&eid=1292&fid=alarm payload={} type=get query={'token': None}]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG1 detect_sequence.py:654 [perf: Starting for frame:alarm]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG1 detect_sequence.py:664 [Sequence of detection types to execute: ['object', 'face', 'alpr']]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG1 detect_sequence.py:669 [============ Frame: alarm Running object detection type in sequence ==================]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG3 detect_sequence.py:689 [object has a same_model_sequence strategy of first]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG1 detect_sequence.py:701 [--------- Frame:alarm Running variation: #1 -------------]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 yolo.py:152 [detect extracted image dimensions as: 800wx450h]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 yolo.py:68 [Waiting for pyzm_uid33_gpu_lock portalock...]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG2 yolo.py:70 [Got pyzm_uid33_gpu_lock portalock]
06/11/23 13:10:01 zmesdetect_m1[79485] DBG1 yolo.py:175 [|---------- YOLO (input image: 800w*450h, model resize dimensions: 416w*416h) ----------|]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 yolo.py:86 [Released pyzm_uid33_gpu_lock portalock]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 yolo.py:199 [perf: processor:gpu Yolo detection took: 2472.84 ms]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 yolo.py:233 [perf: processor:gpu Yolo NMS filtering took: 2.10 ms]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 object.py:72 [core model detection over, got 2 objects. Now filtering]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 object.py:76 [Max object size found to be: 70%]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 object.py:84 [Converted 70% to 251999.99999999997]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 object.py:109 [Returning filtered list of 2 objects.]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:711 [This model iteration inside object found: labels: ['person', 'car'],conf:[0.9895306825637817, 0.6602707505226135]]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:424 [Max object size found to be: 70%]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:432 [Converted 70% to 251999.99999999997]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:502 [intersection: object:person,POLYGON ((636 291, 802 291, 802 449, 636 449, 636 291)) intersects polygon:full_image,POLYGON ((0 0, 800 0, 800 450, 0 450, 0 0))]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:518 [Using global match pattern: (person|car|motorbike|bus|truck|boat|dog|cat|sheep|motorcycle|bird)]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:526 [full_image intersects object:person[[(636, 291), (802, 291), (802, 449), (636, 449)]]]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:502 [intersection: object:car,POLYGON ((7 190, 677 190, 677 454, 7 454, 7 190)) intersects polygon:full_image,POLYGON ((0 0, 800 0, 800 450, 0 450, 0 0))]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:518 [Using global match pattern: (person|car|motorbike|bus|truck|boat|dog|cat|sheep|motorcycle|bird)]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:526 [full_image intersects object:car[[(7, 190), (677, 190), (677, 454), (7, 454)]]]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:753 [breaking out of same model loop, as matches found and strategy is "first"]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 detect_sequence.py:669 [============ Frame: alarm Running face detection type in sequence ==================]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG3 detect_sequence.py:689 [face has a same_model_sequence strategy of union]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 detect_sequence.py:701 [--------- Frame:alarm Running variation: #1 -------------]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 face_dlib.py:164 [|---------- Dlib Face recognition (input image: 800w*450h) ----------|]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG3 face_dlib.py:174 [Face options={'name': 'DLIB based face recognition', 'enabled': 'yes', 'save_unknown_faces': 'yes', 'save_unknown_faces_leeway_pixels': 100, 'face_detection_framework': 'dlib', 'known_images_path': '/var/lib/zmeventnotification/known_faces', 'unknown_images_path': '/var/lib/zmeventnotification/unknown_faces', 'face_model': 'hog', 'face_train_model': 'cnn', 'face_recog_dist_threshold': '0.6', 'face_num_jitters': '1', 'face_upsample_times': '1', 'gpu_max_processes': 1, 'gpu_max_lock_wait': 100, 'cpu_max_processes': 3, 'cpu_max_lock_wait': 100, 'max_size': 800, 'disable_locks': 'no'}]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 face_dlib.py:123 [Waiting for pyzm_uid33_cpu_lock portalock...]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 face_dlib.py:125 [Got pyzm_uid33_cpu_lock lock...]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 face_dlib.py:206 [perf: processor:cpu Finding faces took 228.85 ms]
06/11/23 13:10:04 zmesdetect_m1[79485] ERR detect_sequence.py:713 [Error running model: compute_face_descriptor(): incompatible function arguments. The following argument types are supported:
1. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], face: _dlib_pybind11.full_object_detection, num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vector
2. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], num_jitters: int = 0) -> _dlib_pybind11.vector
3. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], faces: _dlib_pybind11.full_object_detections, num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vectors
4. (self: _dlib_pybind11.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),numpy.uint8]], batch_faces: List[_dlib_pybind11.full_object_detections], num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vectorss
5. (self: _dlib_pybind11.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),numpy.uint8]], num_jitters: int = 0) -> _dlib_pybind11.vectors
Invoked with: <_dlib_pybind11.face_recognition_model_v1 object at 0x7fa9009c65b0>, array([[[ 4, 4, 4],
[ 5, 5, 5],
[ 0, 0, 0],
...,
[154, 159, 197],
[152, 157, 196],
[151, 156, 196]],
[[ 71, 71, 71],
[191, 191, 191],
[190, 190, 190],
...,
[155, 160, 198],
[154, 159, 198],
[153, 158, 198]],
[[ 96, 96, 96],
[234, 234, 234],
[126, 126, 126],
...,
[157, 162, 200],
[157, 162, 200],
[156, 161, 201]],
...,
[[ 79, 85, 97],
[ 77, 83, 95],
[ 76, 82, 96],
...,
[ 4, 1, 4],
[ 4, 0, 4],
[ 6, 0, 5]],
[[ 80, 86, 98],
[ 77, 83, 95],
[ 77, 83, 96],
...,
[ 3, 0, 3],
[ 5, 0, 4],
[ 6, 0, 5]],
[[ 82, 88, 100],
[ 78, 84, 96],
[ 77, 83, 96],
...,
[ 3, 0, 4],
[ 5, 0, 5],
[ 7, 0, 5]]], dtype=uint8), <_dlib_pybind11.full_object_detection object at 0x7fa8f5e08270>, 0]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:714 [Traceback (most recent call last):
File "/usr/local/lib/python3.8/dist-packages/pyzm/ml/detect_sequence.py", line 710, in detect_stream
_b,_l,_c,_m = m.detect(image=frame)
File "/usr/local/lib/python3.8/dist-packages/pyzm/ml/face.py", line 23, in detect
return self.model.detect(image)
File "/usr/local/lib/python3.8/dist-packages/pyzm/ml/face_dlib.py", line 209, in detect
face_encodings = face_recognition.face_encodings(
File "/usr/local/lib/python3.8/dist-packages/face_recognition/api.py", line 214, in face_encodings
return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]
File "/usr/local/lib/python3.8/dist-packages/face_recognition/api.py", line 214, in <listcomp>
return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]
TypeError: compute_face_descriptor(): incompatible function arguments. The following argument types are supported:
1. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], face: _dlib_pybind11.full_object_detection, num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vector
2. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], num_jitters: int = 0) -> _dlib_pybind11.vector
3. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], faces: _dlib_pybind11.full_object_detections, num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vectors
4. (self: _dlib_pybind11.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),numpy.uint8]], batch_faces: List[_dlib_pybind11.full_object_detections], num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vectorss
5. (self: _dlib_pybind11.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),numpy.uint8]], num_jitters: int = 0) -> _dlib_pybind11.vectors
Invoked with: <_dlib_pybind11.face_recognition_model_v1 object at 0x7fa9009c65b0>, array([[[ 4, 4, 4],
[ 5, 5, 5],
[ 0, 0, 0],
...,
[154, 159, 197],
[152, 157, 196],
[151, 156, 196]],
[[ 71, 71, 71],
[191, 191, 191],
[190, 190, 190],
...,
[155, 160, 198],
[154, 159, 198],
[153, 158, 198]],
[[ 96, 96, 96],
[234, 234, 234],
[126, 126, 126],
...,
[157, 162, 200],
[157, 162, 200],
[156, 161, 201]],
...,
[[ 79, 85, 97],
[ 77, 83, 95],
[ 76, 82, 96],
...,
[ 4, 1, 4],
[ 4, 0, 4],
[ 6, 0, 5]],
[[ 80, 86, 98],
[ 77, 83, 95],
[ 77, 83, 96],
...,
[ 3, 0, 3],
[ 5, 0, 4],
[ 6, 0, 5]],
[[ 82, 88, 100],
[ 78, 84, 96],
[ 77, 83, 96],
...,
[ 3, 0, 4],
[ 5, 0, 5],
[ 7, 0, 5]]], dtype=uint8), <_dlib_pybind11.full_object_detection object at 0x7fa8f5e08270>, 0
]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:770 [We did not find any face matches in frame: alarm]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 detect_sequence.py:669 [============ Frame: alarm Running alpr detection type in sequence ==================]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 detect_sequence.py:672 [Making sure we have matched one of ['car', 'motorbike', 'bus', 'truck', 'boat'] in ['person', 'car'] before we proceed]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG3 detect_sequence.py:689 [alpr has a same_model_sequence strategy of first]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 detect_sequence.py:701 [--------- Frame:alarm Running variation: #1 -------------]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG1 alpr.py:50 [Supplied object is not a file, assuming blob and creating file]
06/11/23 13:10:04 zmesdetect_m1[79485] DBG2 alpr.py:54 [resizing image blob to 1600]
06/11/23 13:10:07 zmesdetect_m1[79485] ERR alpr.py:212 [Plate recognizer rejected the upload with 403 Client Error: Forbidden for url: https://api.platerecognizer.com/v1/plate-reader and body:b'{"detail":"Invalid token.","status_code":403}']
06/11/23 13:10:07 zmesdetect_m1[79485] DBG2 alpr.py:244 [Exiting ALPR with labels:[]]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG2 detect_sequence.py:711 [This model iteration inside alpr found: labels: [],conf:[]]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG2 detect_sequence.py:424 [Max object size found to be: 70%]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG2 detect_sequence.py:432 [Converted 70% to 251999.99999999997]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG2 detect_sequence.py:770 [We did not find any alpr matches in frame: alarm]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG1 detect_sequence.py:830 [perf: TOTAL detection sequence (with image loads) took: 13722.35 ms to process 1292]
06/11/23 13:10:07 zmesdetect_m1[79485] INF zm_detect.py:479 [Prediction string:[s] detected:person:88% car:49% ]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG1 zm_detect.py:481 [Prediction string JSON:{"labels": ["person", "car"], "boxes": [[516, 299, 778, 449], [2, 192, 674, 452]], "frame_id": "snapshot", "confidences": [0.8788268566131592, 0.4906500279903412], "image_dimensions": {"original": [720, 1280], "resized": [450, 800]}}]
[s] detected:person:88% car:49% --SPLIT--{"labels": ["person", "car"], "boxes": [[516, 299, 778, 449], [2, 192, 674, 452]], "frame_id": "snapshot", "confidences": [0.8788268566131592, 0.4906500279903412], "image_dimensions": {"original": [720, 1280], "resized": [450, 800]}}
06/11/23 13:10:07 zmesdetect_m1[79485] DBG1 zm_detect.py:499 [Writing detected image to /tmp/objdetect.jpg]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG1 zm_detect.py:503 [Writing JSON output to /tmp/objects.json]
06/11/23 13:10:07 zmesdetect_m1[79485] DBG1 zm_detect.py:557 [Closing logs]