Closed turowicz closed 3 years ago
cc @bsekachev
cvat:
2021-01-05 15:01:17,511 DEBG 'rqworker_low' stderr output:
INFO:rq.worker:low: __call__(cleanup=False, function=<cvat.apps.lambda_manager.views.LambdaFunction object at 0x7fe59e760b20>, mapping={'person': 'person'}, quality=None, task=1, threshold=None) (0bf3bbad-515c-42c7-8074-0eae65dc33db)
2021-01-05 15:01:18,585 DEBG 'rqworker_low' stderr output:
DEBUG:rq.worker:Handling successful execution of job 0bf3bbad-515c-42c7-8074-0eae65dc33db
2021-01-05 15:01:18,589 DEBG 'rqworker_low' stderr output:
INFO:rq.worker:low: Job OK (0bf3bbad-515c-42c7-8074-0eae65dc33db)
2021-01-05 15:01:18,590 DEBG 'rqworker_low' stderr output:
INFO:rq.worker:Result is kept for 500 seconds
2021-01-05 15:01:18,598 DEBG 'rqworker_low' stderr output:
DEBUG:rq.worker:Sent heartbeat to prevent worker timeout. Next one should arrive within 480 seconds.
2021-01-05 15:01:18,598 DEBG 'rqworker_low' stderr output:
DEBUG:rq.worker:Sent heartbeat to prevent worker timeout. Next one should arrive within 480 seconds.
2021-01-05 15:01:18,600 DEBG 'rqworker_low' stderr output:
DEBUG:rq.worker:*** Listening on low...
2021-01-05 15:01:18,602 DEBG 'rqworker_low' stderr output:
DEBUG:rq.worker:Sent heartbeat to prevent worker timeout. Next one should arrive within 480 seconds.
nuclio-dashboard:
21.01.05 15:01:17.491 dashboard.server (D) Handled request {"requestMethod": "GET", "requestPath": "/api/functions/tf-faster-rcnn-inception-v2-coco", "requestHeaders": {"Accept":["*/*"],"Accept-Encoding":["gzip, deflate"],"Connection":["close"],"User-Agent":["python-requests/2.24.0"],"X-Nuclio-Function-Namespace":["nuclio"],"X-Nuclio-Project-Name":["cvat"]}, "requestBody": "", "responseStatus": 200, "responseTime": "9.706057ms"}
21.01.05 15:01:17.653 ashboard.platform.invoker (I) Executing function {"method": "POST", "url": "http://nuclio-tf-faster-rcnn-inception-v2-coco.nuclio.svc.cluster.local:8080", "headers": {"Accept":["*/*"],"Accept-Encoding":["gzip, deflate"],"Connection":["close"],"Content-Length":["31613"],"Content-Type":["application/json"],"User-Agent":["python-requests/2.24.0"],"X-Nuclio-Function-Name":["tf-faster-rcnn-inception-v2-coco"],"X-Nuclio-Function-Namespace":["nuclio"],"X-Nuclio-Invoke-Via":["domain-name"],"X-Nuclio-Log-Level":[""],"X-Nuclio-Path":["/"],"X-Nuclio-Project-Name":["cvat"],"X-Nuclio-Target":["tf-faster-rcnn-inception-v2-coco"]}}
21.01.05 15:01:18.580 ashboard.platform.invoker (I) Got response {"status": "200 OK"}
21.01.05 15:01:18.580 dashboard.server (D) Handled request {"requestMethod": "POST", "requestPath": "/api/function_invocations", "requestHeaders": {"Accept":["*/*"],"Accept-Encoding":["gzip, deflate"],"Connection":["close"],"Content-Length":["31613"],"Content-Type":["application/json"],"User-Agent":["python-requests/2.24.0"],"X-Nuclio-Function-Name":["tf-faster-rcnn-inception-v2-coco"],"X-Nuclio-Function-Namespace":["nuclio"],"X-Nuclio-Invoke-Via":["domain-name"],"X-Nuclio-Log-Level":[""],"X-Nuclio-Path":["/"],"X-Nuclio-Project-Name":["cvat"],"X-Nuclio-Target":["tf-faster-rcnn-inception-v2-coco"]}, "requestBody": "{\"image\": 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:01:18.720230166Z 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\"}", "responseStatus": 200, "responseTime": "946.251703ms", "responseBody": "[{\"confidence\": \"0.99921215\", \"label\": \"person\", \"points\": [28.898704051971436, 19.00976598262787, 400.0, 399.08599853515625], \"type\": \"rectangle\"}]"}
Such cvat logs as above are only created for bulk annotation. When using the magic wand the cvat doesn't log anything but Send user activity
. Nuclio-dashboard logs are the same, everything is 200 OK.
cc @dvkruchinin
cc @nmanovic @jahaniam
My actions before raising this issue
Automatic annotation only works when invoked from inside the job on a particular frame using the magic wand. When running a bulk annotation on the entire task, it does complete successfully but the annotations aren't saved.
Expected Behaviour
Persist the annotations after running a bulk automated annotations.
Current Behaviour
Not persisting the annotations after running a bulk automated annotations. No errors are thrown and everything seems to go through OK on Nuclio.
Possible Solution
No idea.
Steps to Reproduce (for bugs)
develop
CVAT to KubernetesContext
I'm trying to annotate entire sets of images.
Your Environment
git log -1
): 266e7ca9b4ceb76077e8e2b54df6a3a208f3e17bdocker version
(e.g. Docker 17.0.05): N/A on AKS, GKE etc.