recognize
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Processing loop
Which version of recognize are you using?
6.1.1
Enabled Modes
Object recognition, Face recognition
TensorFlow mode
Normal mode
Downstream App
Memories App
Which Nextcloud version do you have installed?
28.0.5
Which Operating system do you have installed?
Debian 12
Which database are you running Nextcloud on?
MariaDB
Which Docker container are you using to run Nextcloud? (if applicable)
No response
How much RAM does your server have?
32GB
What processor Architecture does your CPU have?
x86_64
Describe the Bug
I have three files which are processed by the object detector in a loop and not removed from the queue.
Expected Behavior
Files should be removed from the queue once processed
To Reproduce
Well, hard to say. Since this only occured for 3 of my >100k files, it's not clear to me what caused the issue
Debug log
MariaDB [nextcloud]> Select * FROM oc_recognize_queue_imagenet;
+--------+---------+------------+---------+--------+
| id | file_id | storage_id | root_id | update |
+--------+---------+------------+---------+--------+
| 312601 | 822267 | 2 | 666480 | 0 |
| 312603 | 822269 | 2 | 666480 | 0 |
| 312604 | 822270 | 2 | 666480 | 0 |
+--------+---------+------------+---------+--------+
3 rows in set (0.000 sec)
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifying files of storage 2 using imagenet","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"fetching 100 files from imagenet queue","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Running imagenet classifier","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"generating preview of 822267 with dimension 1024 using nextcloud preview manager","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"generating preview of 822269 with dimension 1024 using nextcloud preview manager","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"generating preview of 822270 with dimension 1024 using nextcloud preview manager","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifying array (\n 0 => '/tmp/oc_tmp_48XDyw-.jpg',\n 1 => '/tmp/oc_tmp_NocVac-.jpg',\n 2 => '/tmp/oc_tmp_tkiaC1-.jpg',\n)","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Running array (\n 0 => '/usr/bin/nice',\n 1 => '-0',\n 2 => '/var/www/nextcloud/apps/recognize/bin/node',\n 3 => '/var/www/nextcloud/apps/recognize/src/classifier_imagenet.js',\n 4 => '-',\n)","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:12+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: 2024-05-15 23:20:12.562541: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\nTo enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'bell cote',\n probability: 0.8209066390991211,\n rule: { label: 'tower', threshold: 0.1, categories: [ 'architecture' ] }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'church',\n probability: 0.04315225034952164,\n rule: {\n label: 'church',\n context: 'nature stones',\n threshold: 0.1,\n categories: [ 'building', 'architecture' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'lakeside',\n probability: 0.004793553147464991,\n rule: {\n label: 'lakeside',\n context: 'nature',\n threshold: 0.6,\n categories: [ 'water' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'beacon',\n probability: 0.004151171538978815,\n rule: { threshold: 0.1, categories: [ 'tower', 'architecture' ] }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'vault',\n probability: 0.0038930969312787056,\n rule: { label: 'building', context: 'nature stones', threshold: 0.1 }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'pole',\n probability: 0.0022382489405572414,\n rule: { threshold: 0.1, priority: -2 }\n}\n{\n className: 'nipple',\n probability: 0.002208178164437413,\n rule: { label: 'bottle', threshold: 0.2 }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:15+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Result for /andreas/files/Share/2024/2024-05-10 09.31.19.jpg(oc_tmp_48XDyw-.jpg) = [\"Tower\",\"Architecture\"]","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:16+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'church',\n probability: 0.4917282164096832,\n rule: {\n label: 'church',\n context: 'nature stones',\n threshold: 0.1,\n categories: [ 'building', 'architecture' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:16+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'bell cote',\n probability: 0.33402442932128906,\n rule: { label: 'tower', threshold: 0.1, categories: [ 'architecture' ] }\n}\n{\n className: 'lakeside',\n probability: 0.018104856833815575,\n rule: {\n label: 'lakeside',\n context: 'nature',\n threshold: 0.6,\n categories: [ 'water' ]\n }\n}\n{\n className: 'mosque',\n probability: 0.005985795520246029,\n rule: {\n label: 'tower',\n threshold: 0.1,\n categories: [ 'building', 'architecture' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:16+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'earthstar',\n probability: 0.005197624210268259,\n rule: { label: 'vegetables', threshold: 0.6, categories: [ 'food' ] }\n}\n{\n className: 'vault',\n probability: 0.0040014563128352165,\n rule: { label: 'building', context: 'nature stones', threshold: 0.1 }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:16+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'buckeye',\n probability: 0.003190287621691823,\n rule: { label: 'plant', threshold: 0.1, catgories: [ 'nature' ] }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:16+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Result for /andreas/files/Share/2024/2024-05-10 09.30.29.jpg(oc_tmp_NocVac-.jpg) = [\"Church\",\"Building\",\"Architecture\",\"Tower\"]","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:17+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'church',\n probability: 0.6289583444595337,\n rule: {\n label: 'church',\n context: 'nature stones',\n threshold: 0.1,\n categories: [ 'building', 'architecture' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:17+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'bell cote',\n probability: 0.190898135304451,\n rule: { label: 'tower', threshold: 0.1, categories: [ 'architecture' ] }\n}\n{\n className: 'monastery',\n probability: 0.007419401314109564,\n rule: {\n label: 'historic',\n threshold: 0.25,\n context: 'buildings architecture',\n categories: [ 'architecture' ]\n }\n}\n{\n className: 'lakeside',\n probability: 0.005275358911603689,\n rule: {\n label: 'lakeside',\n context: 'nature',\n threshold: 0.6,\n categories: [ 'water' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:17+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Result for /andreas/files/Share/2024/2024-05-10 09.30.35.jpg(oc_tmp_tkiaC1-.jpg) = [\"Church\",\"Building\",\"Architecture\",\"Tower\"]","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}
{"reqId":"6hT9CpdzAzHZvx1hRr53","level":0,"time":"2024-05-15T23:20:17+02:00","remoteAddr":"","user":"--","app":"recognize","method":"","url":"--","message":"Classifier process output: {\n className: 'earthstar',\n probability: 0.0036971624940633774,\n rule: { label: 'vegetables', threshold: 0.6, categories: [ 'food' ] }\n}\n{\n className: 'vault',\n probability: 0.0036862995475530624,\n rule: { label: 'building', context: 'nature stones', threshold: 0.1 }\n}\n{\n className: 'mosque',\n probability: 0.0026431980077177286,\n rule: {\n label: 'tower',\n threshold: 0.1,\n categories: [ 'building', 'architecture' ]\n }\n}\n","userAgent":"--","version":"28.0.5.1","data":{"app":"recognize"}}