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Ok, thanks. I see Pi's have gotten kind of expensive anyway.
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Yup, seems like the only ones available are from "scalpers". Fortunately, I have 2 model 4's I bought early on. They claim that there should be more available later this year.
>64
Some days the dragon wins. Suck it up.
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Right now? Not great, but we're working hard to get speed up significantly.
If you have a Google Coral then I'm getting inference around 2s on large models, but that should come down to sub 100ms with more targeted, and smaller, models.
Raspberry Pi is an important platform for us so we'll be putting in the effort to get speeds up.
cheers
Chris Maunder
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I just ask because I have another application that runs on a Pi 3b, 24x7x365 for the last 3.5 years.
Every so often, I update software, that's all.
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CodeProject.AI version 2.0.8 beta
Windows 10 Version 10.0.19045.2728
Yesterday, CodeProject.AI apparently just stopped analysing images.
CodeProject.AI log:
2023-03-14 16:39:19: Client request 'custom' in the queue (#reqid c57610ee-1ec3-47d4-a2d3-0eff1a2e723b)
2023-03-14 16:39:19: Client request 'custom' in the queue (#reqid 0c405ebe-be78-4fc1-9e81-5485f5c36d66)
2023-03-14 16:39:19: Request 'custom' dequeued for processing (#reqid 0c405ebe-be78-4fc1-9e81-5485f5c36d66)
2023-03-14 16:39:19: Request 'custom' dequeued for processing (#reqid c57610ee-1ec3-47d4-a2d3-0eff1a2e723b)
2023-03-14 16:39:19: Object Detection (Net): Command completed in 173 ms. (command timing) in Object Detection (Net)
2023-03-14 16:39:19: Response received (#reqid c57610ee-1ec3-47d4-a2d3-0eff1a2e723b)
2023-03-14 16:39:19: Response received (#reqid 0c405ebe-be78-4fc1-9e81-5485f5c36d66)
2023-03-14 16:39:19: Object Detection (Net): Command completed in 309 ms. (command timing) in Object Detection (Net)
2023-03-14 16:39:21: Request 'custom' dequeued for processing (#reqid bc0db3c2-7f8c-4d81-b4ec-90eaa3146d1b)
2023-03-14 16:39:21: Client request 'custom' in the queue (#reqid bc0db3c2-7f8c-4d81-b4ec-90eaa3146d1b)
2023-03-14 16:39:21: Response received (#reqid bc0db3c2-7f8c-4d81-b4ec-90eaa3146d1b)
2023-03-14 16:39:21: Object Detection (Net): Command completed in 160 ms. (command timing) in Object Detection (Net)
2023-03-14 16:39:23: Client request 'custom' in the queue (#reqid 0294be77-9ded-4448-a164-0f1300fb37f6)
2023-03-14 16:39:23: Client request 'custom' in the queue (#reqid 25f01346-db50-453a-8738-5023e9734b65)
2023-03-14 16:39:23: Request 'custom' dequeued for processing (#reqid 25f01346-db50-453a-8738-5023e9734b65)
2023-03-14 16:39:23: Request 'custom' dequeued for processing (#reqid 0294be77-9ded-4448-a164-0f1300fb37f6)
2023-03-14 16:39:24: Request 'custom' dequeued for processing (#reqid 72f04d1b-c73c-4497-8850-fefba78d3169)
2023-03-14 16:39:24: Client request 'custom' in the queue (#reqid 72f04d1b-c73c-4497-8850-fefba78d3169)
2023-03-14 16:39:24: Request 'custom' dequeued for processing (#reqid 26a80c58-1c25-4ede-9610-e9fa6dcb35b1)
2023-03-14 16:39:24: Client request 'custom' in the queue (#reqid 26a80c58-1c25-4ede-9610-e9fa6dcb35b1)
2023-03-14 16:39:25: Client request 'custom' in the queue (#reqid 3074e69f-0d10-48be-b455-4e3c109592d1)
2023-03-14 16:39:25: Client request 'custom' in the queue (#reqid 09233bfc-dcbd-4135-8d94-6d95ecaf1b29)
2023-03-14 16:39:26: Client request 'custom' in the queue (#reqid d1ba609c-37ce-465e-b06b-63bd1c10fcfa)
2023-03-14 16:39:26: Client request 'custom' in the queue (#reqid e31cc8bd-ba9e-42b4-81f7-a3b094bbe30f)
2023-03-14 16:39:27: Client request 'custom' in the queue (#reqid e40c6d02-37b7-46a9-b615-db31af23d552)
2023-03-14 16:39:27: Client request 'custom' in the queue (#reqid 1ab39efe-0f46-4ab9-afed-7278dbd51ec9)
2023-03-14 16:39:27: Client request 'custom' in the queue (#reqid 6cef2ab5-deb7-4092-9f6c-b146f6327e93)
2023-03-14 16:39:27: Client request 'custom' in the queue (#reqid 9cb06f64-3e3a-43ed-880f-71815d786de4)
2023-03-14 16:39:27: Client request 'custom' in the queue (#reqid 5305f6c9-1831-4610-aa4d-d42386e72f65)
2023-03-14 16:39:28: Client request 'custom' in the queue (#reqid cae46baf-cadd-49ca-a249-d224dc0d5c91)
2023-03-14 16:39:28: Client request 'custom' in the queue (#reqid 10f9dbc9-955b-47af-9be8-e8638a73e527)
2023-03-14 16:39:29: Client request 'custom' in the queue (#reqid 793a14ce-0676-4183-ae97-9e53babdbe7f)
2023-03-14 16:39:29: Client request 'custom' in the queue (#reqid e977473c-3e05-4c00-b1c0-2b53f21c7ddc)
2023-03-14 16:39:30: Client request 'custom' in the queue (#reqid 4b25c94b-33e6-4b29-9d9e-d6f3d46d50c7)
2023-03-14 16:39:30: Client request 'custom' in the queue (#reqid 9bbd6b64-46b9-47cc-99f7-9d9218c4972b)
2023-03-14 16:39:31: Client request 'custom' in the queue (#reqid 1156ec43-b852-4632-b154-0d752e5e7c73)
2023-03-14 16:39:57: Client request 'custom' in the queue (#reqid 415c17b3-a7ed-4c27-b64c-02289bc93ebe)
2023-03-14 16:39:58: Client request 'custom' in the queue (#reqid 96241bd4-7232-4002-8235-ba60796d8fcd)
2023-03-14 16:39:58: Client request 'custom' in the queue (#reqid f5bdad6a-b883-4f9a-8d8a-17701553a6a4)
2023-03-14 16:39:59: Client request 'custom' in the queue (#reqid ee9daecc-41eb-4310-80ce-7934b0f8ed79)
2023-03-14 16:39:59: Client request 'custom' in the queue (#reqid ed28cfe1-6fd2-42d5-a4a2-7c56ac8ee970)
2023-03-14 16:40:00: Client request 'custom' in the queue (#reqid 679410e6-3e64-4633-ba72-b3878a4995a8)
2023-03-14 16:40:00: Client request 'custom' in the queue (#reqid 46c1a81e-fb4a-48a2-8941-54e3c64ffbf4)
2023-03-14 16:40:00: Client request 'custom' in the queue (#reqid 381995c8-d8ad-45d1-a2e0-2a8e28e61fdc)
2023-03-14 16:40:00: Client request 'custom' in the queue (#reqid eeb4b272-6137-4635-bc5e-f48c115ed25a)
2023-03-14 16:40:01: Client request 'custom' in the queue (#reqid 0c2fa351-438d-4bd9-a26b-2cc7bda93e00)
2023-03-14 16:40:01: Client request 'custom' in the queue (#reqid e21dbf55-57d7-4460-8267-e667a494077a)
2023-03-14 16:40:01: Client request 'custom' in the queue (#reqid 670d55b7-1e7f-4e56-bcfc-6ac7d47202dc)
2023-03-14 16:40:01: Client request 'custom' in the queue (#reqid 591b939b-f30f-49b8-8eb5-df2cc3cb4249)
2023-03-14 16:40:02: Client request 'custom' in the queue (#reqid f3e00adf-c1aa-4a6e-a082-8fa2c9b9280b)
2023-03-14 16:40:02: Client request 'custom' in the queue (#reqid 3c1244cf-c42d-470d-8ed8-df34ee9705ac)
2023-03-14 16:40:03: Client request 'custom' in the queue (#reqid 86b1c61e-699d-4e5c-bb1c-0826367c3be4)
2023-03-14 16:40:03: Client request 'custom' in the queue (#reqid 45a04674-d044-4235-a75f-31b704d7b7ca)
2023-03-14 16:40:04: Client request 'custom' in the queue (#reqid 1fed3cc3-69bd-4b2c-a4ad-446d302e7a59)
2023-03-14 16:40:04: Client request 'custom' in the queue (#reqid f8abdc5e-925a-4417-badf-2d76b959cd67)
2023-03-14 16:40:05: Client request 'custom' in the queue (#reqid c377a9f9-d22c-4a26-9305-16465f91a9cf)
2023-03-14 16:40:05: Client request 'custom' in the queue (#reqid 49614dd4-bc2a-4094-b5e2-be7c79065c19)
2023-03-14 16:40:05: Client request 'custom' in the queue (#reqid 5b514c36-8bca-4f6d-abe8-f13b56092747)
2023-03-14 16:40:05: Client request 'custom' in the queue (#reqid fedb37c4-1a3c-4ebe-8a60-e27da2f37bcb)
2023-03-14 16:40:06: Client request 'custom' in the queue (#reqid 6060b8a3-d9a6-4693-837f-34598e9236c2)
2023-03-14 16:40:06: Client request 'custom' in the queue (#reqid a15b0245-5653-41c6-89f7-0d4070a7f92c)
2023-03-14 16:40:07: Client request 'custom' in the queue (#reqid 35a27570-f3c6-4442-ba14-0bb50a6daf0a)
2023-03-14 16:40:07: Client request 'custom' in the queue (#reqid 87be4356-423d-480a-8a89-e4212d9051e9)
2023-03-14 16:40:08: Client request 'custom' in the queue (#reqid 15cdd431-b52d-4b7d-93cd-97bfec6aca90)
2023-03-14 16:40:08: Client request 'custom' in the queue (#reqid 1ed322d2-f6de-4ea6-9bab-7480cf3eaf51)
2023-03-14 16:40:09: Client request 'custom' in the queue (#reqid 66d12cc6-d8e0-4ba8-a6b0-bda7e4bb52d8)
2023-03-14 16:40:48: Client request 'custom' in the queue (#reqid 0c2e600d-900c-4e0d-a618-f456b23d11c3)
It goes on like this for quite a while, queuing images.
Blue Iris is getting AI timeouts about 25 minutes after this (I can't explain the time difference):
3 3/14/2023 4:39:19.194 PM Prater MOTION_A
0 3/14/2023 4:39:19.525 PM Prater AI: [ipcam-dark] Car:94% [84,48 158,83] 176ms
1 3/14/2023 4:39:20.541 PM Prater_111 Signal: network retry
3 3/14/2023 4:39:20.899 PM Back_Yard MOTION_A
0 3/14/2023 4:39:21.202 PM Back_Yard AI: [ipcam-dark] Car:89% [709,83 829,143] 179ms
0 3/14/2023 4:39:21.202 PM Back_Yard AI: [ipcam-dark] Car:74% [659,64 730,100] 179ms
0 3/14/2023 4:39:21.202 PM Back_Yard AI: [ipcam-dark] Car:56% [808,77 855,144] 179ms
3 3/14/2023 4:39:23.585 PM Front_Yard MOTION_A
3 3/14/2023 4:39:27.067 PM Doorbell MOTION_A
1 3/14/2023 4:39:43.639 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:39:50.463 PM Prater_111 Signal: network retry
2 3/14/2023 4:39:53.790 PM Front_Yard AI: timeout
1 3/14/2023 4:39:53.791 PM Front_Yard AI: Alert cancelled [AI: timeout] 30004ms
2 3/14/2023 4:39:57.277 PM Doorbell AI: timeout
1 3/14/2023 4:39:57.277 PM Doorbell AI: Alert cancelled [AI: timeout] 30005ms
3 3/14/2023 4:40:00.852 PM Prater MOTION_A
3 3/14/2023 4:40:05.045 PM Back_Yard MOTION_A
1 3/14/2023 4:40:13.397 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:40:20.716 PM Prater_111 Signal: network retry
2 3/14/2023 4:40:28.079 PM Front_Yard AI: timeout
1 3/14/2023 4:40:28.079 PM Front_Yard AI: Alert cancelled [AI: timeout] 30005ms
2 3/14/2023 4:40:30.965 PM Prater AI: timeout
1 3/14/2023 4:40:30.966 PM Prater AI: Alert cancelled [AI: timeout] 30001ms
2 3/14/2023 4:40:35.268 PM Back_Yard AI: timeout
1 3/14/2023 4:40:35.269 PM Back_Yard AI: Alert cancelled [AI: timeout] 30103ms
1 3/14/2023 4:40:43.493 PM Prater_111 Signal: Failed to connect
3 3/14/2023 4:40:48.567 PM Front_Yard MOTION_A
1 3/14/2023 4:40:50.865 PM Prater_111 Signal: network retry
3 3/14/2023 4:40:52.760 PM Doorbell MOTION_A
3 3/14/2023 4:40:55.194 PM Prater MOTION_A
3 3/14/2023 4:41:00.365 PM Back_Yard MOTION_A
1 3/14/2023 4:41:13.896 PM Prater_111 Signal: Failed to connect
2 3/14/2023 4:41:18.772 PM Front_Yard AI: not responding
1 3/14/2023 4:41:18.772 PM Front_Yard AI: Alert cancelled [AI: not responding] 30005ms
1 3/14/2023 4:41:20.765 PM Prater_111 Signal: network retry
2 3/14/2023 4:41:22.919 PM Doorbell AI: timeout
1 3/14/2023 4:41:22.920 PM Doorbell AI: Alert cancelled [AI: timeout] 30006ms
2 3/14/2023 4:41:25.302 PM Prater AI: not responding
1 3/14/2023 4:41:25.303 PM Prater AI: Alert cancelled [AI: not responding] 30001ms
2 3/14/2023 4:41:30.475 PM Back_Yard AI: timeout
1 3/14/2023 4:41:30.476 PM Back_Yard AI: Alert cancelled [AI: timeout] 30005ms
1 3/14/2023 4:41:43.641 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:41:51.094 PM Prater_111 Signal: network retry
1 3/14/2023 4:42:14.053 PM Prater_111 Signal: Failed to connect
3 3/14/2023 4:42:14.316 PM Doorbell MOTION_A
3 3/14/2023 4:42:15.986 PM Front_Yard MOTION_A
1 3/14/2023 4:42:21.246 PM Prater_111 Signal: network retry
1 3/14/2023 4:42:44.123 PM Prater_111 Signal: Failed to connect
2 3/14/2023 4:42:44.538 PM Doorbell AI: not responding
1 3/14/2023 4:42:44.538 PM Doorbell AI: Alert cancelled [AI: not responding] 30010ms
2 3/14/2023 4:42:46.189 PM Front_Yard AI: not responding
1 3/14/2023 4:42:46.189 PM Front_Yard AI: Alert cancelled [AI: not responding] 30004ms
1 3/14/2023 4:42:51.199 PM Prater_111 Signal: network retry
3 3/14/2023 4:42:57.738 PM Front_Yard MOTION_A
1 3/14/2023 4:43:14.206 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:43:21.526 PM Prater_111 Signal: network retry
2 3/14/2023 4:43:27.851 PM Front_Yard AI: not responding
1 3/14/2023 4:43:27.853 PM Front_Yard AI: Alert cancelled [AI: not responding] 30004ms
1 3/14/2023 4:43:44.265 PM Prater_111 Signal: Failed to connect
0 3/14/2023 4:43:50.576 PM New Move: nothing to do [39.5G/41.0G, 791.5G free]
0 3/14/2023 4:43:50.576 PM Stored Move: nothing to do [69.2G/70.0G, 791.5G free]
0 3/14/2023 4:43:50.979 PM Alerts Delete: 12 items 23.2M [0/720 hrs, 30.5G/30.0G, 791.5G free] 63646 locked
0 3/14/2023 4:43:50.979 PM AIInput Delete: nothing to do [0/24 hrs, 0B/1.00G, 791.5G free]
1 3/14/2023 4:43:51.647 PM Prater_111 Signal: network retry
1 3/14/2023 4:44:14.665 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:44:21.593 PM Prater_111 Signal: network retry
1 3/14/2023 4:44:44.411 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:44:51.983 PM Prater_111 Signal: network retry
1 3/14/2023 4:45:14.823 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:45:21.921 PM Prater_111 Signal: network retry
1 3/14/2023 4:45:44.913 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:45:52.319 PM Prater_111 Signal: network retry
1 3/14/2023 4:46:15.338 PM Prater_111 Signal: Failed to connect
1 3/14/2023 4:46:22.405 PM Prater_111 Signal: network retry
3 3/14/2023 4:46:41.255 PM Front_Yard MOTION_A
1 3/14/2023 4:46:45.415 PM Prater_111 Signal: Failed to connect
3 3/14/2023 4:46:47.221 PM Prater MOTION_A
3 3/14/2023 4:46:51.828 PM Back_Yard MOTION_A
1 3/14/2023 4:46:52.263 PM Prater_111 Signal: network retry
2 3/14/2023 4:47:11.459 PM Front_Yard AI: not responding
1 3/14/2023 4:47:11.460 PM Front_Yard AI: Alert cancelled [AI: not responding] 30006ms
1 3/14/2023 4:47:15.156 PM Prater_111 Signal: Failed to connect
2 3/14/2023 4:47:17.424 PM Prater AI: timeout
1 3/14/2023 4:47:17.425 PM Prater AI: Alert cancelled [AI: timeout] 30002ms
3 3/14/2023 4:47:18.557 PM Doorbell MOTION_A
3 3/14/2023 4:47:19.102 PM Front_Yard MOTION_A
2 3/14/2023 4:47:22.031 PM Back_Yard AI: not responding
1 3/14/2023 4:47:22.032 PM Back_Yard AI: Alert cancelled [AI: not responding] 30004ms
I initially thought this had something to do with a camera that I added earlier and then powered down, but that camera was powered down about 4 hours earlier.
So, apparently, something began using memory, Blue Iris kept recording until it stopped recording at about 12:30 am the today. The operating system then stopped. At 4:15 am, I had no user interface, I had to manually shut down the machine and restart it.
When I restarted, Code Project apparently was not running yet.
This could be related to Windows "Patch Tuesday"??
I have read some posts in IPCam, that some people are seeing that after a number of images analysed, that Code Project just stops. I'm not sure about this.
So for now, I have rolled Blue Iris back to version 5.6.8.4, which I believe is the last stable version that does not have the tight integration with Code Project. This version allows one to manually specify the location of the custom models. I am back to using the Jetson Nano with Ubuntu version 18.04 and Deepstack ver jetpack.2021.06.01.
I had been keeping Blue Iris on critical or highly stable versions, but the last one apparently ties me to Code Project.
FYI, here is the startup info from the Code Project startup this morning:
(I only have 4 daily logs available as of now. It ran for several days.)
2023-03-15 04:20:53: ** Operating System: Windows (Microsoft Windows 10.0.19045)
2023-03-15 04:20:53: ** CPUs: 1 CPU x 4 cores. 4 logical processors (x64)
2023-03-15 04:20:53: ** GPU: Intel(R) HD Graphics 630 (1,024 MiB) (Intel Corporation)
2023-03-15 04:20:53: ** Driver: 31.0.101.2111
2023-03-15 04:20:53: ** System RAM: 16 GiB
2023-03-15 04:20:53: ** Target: Windows
2023-03-15 04:20:53: ** BuildConfig: Release
2023-03-15 04:20:53: ** Execution Env: Native
2023-03-15 04:20:53: ** Runtime Env: Production
2023-03-15 04:20:53: ** .NET framework: .NET 7.0.3
2023-03-15 04:20:53: ** App DataDir: C:\ProgramData\CodeProject\AI
2023-03-15 04:21:00: System GPU info:
2023-03-15 04:21:00: GPU 3D Usage 2%
2023-03-15 04:21:00: GPU RAM Usage 0
2023-03-15 04:21:00: Video adapter info:
2023-03-15 04:21:00: Intel(R) HD Graphics 630:
2023-03-15 04:21:00: Adapter RAM 1,024 MiB
2023-03-15 04:21:00: Driver Version 31.0.101.2111
2023-03-15 04:21:00: Video Processor Intel(R) HD Graphics Family
2023-03-15 04:21:00: ------------------------------------------------------------------
2023-03-15 04:21:00: ROOT_PATH = C:\Program Files\CodeProject\AI
2023-03-15 04:21:00: MODULES_PATH = C:\Program Files\CodeProject\AI\AnalysisLayer
2023-03-15 04:21:00: DOWNLOADED_MODULES_PATH = C:\Program Files\CodeProject\AI\modules
2023-03-15 04:21:00: PYTHON_BASEPATH = C:\Program Files\CodeProject\AI\AnalysisLayer\bin\windows\%PYTHON_RUNTIME%\venv
2023-03-15 04:21:00: PYTHON_PATH = C:\Program Files\CodeProject\AI\AnalysisLayer\bin\windows\%PYTHON_RUNTIME%\venv\scripts\Python
2023-03-15 04:21:00: Temp Dir: C:\Windows\TEMP\
2023-03-15 04:21:00: Data Dir: C:\ProgramData\CodeProject\AI
2023-03-15 04:21:00: ------------------------------------------------------------------
2023-03-15 04:21:00: ModuleRunner Start
2023-03-15 04:21:00: Starting Background AI Modules
2023-03-15 04:21:01: Client request 'list-custom' in the queue (#reqid 50c3694f-4406-4792-8466-ccbd68d75b52)
2023-03-15 04:21:03: Starting "C:\Program Files...ionNet\ObjectDetectionNet.exe"
2023-03-15 04:21:03:
2023-03-15 04:21:03: ** Module 'Object Detection (YOLOv5 .NET)' (ID: ObjectDetectionNet)
2023-03-15 04:21:03: ** Active: True
2023-03-15 04:21:03: ** GPU: Support enabled
2023-03-15 04:21:03: ** Parallelism: 0
2023-03-15 04:21:03: ** Platforms: windows,linux,linux-arm64,macos,macos-arm64
2023-03-15 04:21:03: ** FilePath: ObjectDetectionNet.exe
2023-03-15 04:21:03: ** ModulePath: ObjectDetectionNet
2023-03-15 04:21:03: ** Install: PreInstalled
2023-03-15 04:21:03: ** Runtime: execute
2023-03-15 04:21:03: ** Queue: objectdetection_queue
2023-03-15 04:21:03: ** Start pause: 1 sec
2023-03-15 04:21:03: ** Valid: True
2023-03-15 04:21:03: ** Environment Variables
2023-03-15 04:21:03: ** CUSTOM_MODELS_DIR = %CURRENT_MODULE_PATH%\custom-models
2023-03-15 04:21:03: ** MODELS_DIR = %CURRENT_MODULE_PATH%\assets
2023-03-15 04:21:03: ** MODEL_SIZE = medium
2023-03-15 04:21:03:
2023-03-15 04:21:03: Started Object Detection (YOLOv5 .NET) module
2023-03-15 04:21:04: ObjectDetectionNet.exe: Application started. Press Ctrl+C to shut down.
2023-03-15 04:21:04: ObjectDetectionNet.exe: Hosting environment: Production
2023-03-15 04:21:04: ObjectDetectionNet.exe: Content root path: C:\Program Files\CodeProject\AI\AnalysisLayer\ObjectDetectionNet
2023-03-15 04:21:04: Installing Initial Modules.
2023-03-15 04:21:05: ObjectDetectionNet.exe: Please ensure you don't enable this module along side any other Object Detection module using the 'vision/detection' route and 'objectdetection_queue' queue (eg. ObjectDetectionYolo). There will be conflicts
2023-03-15 04:21:05: Object Detection (Net): Object Detection (Net) module started. in Object Detection (Net)
2023-03-15 04:21:05: Request 'list-custom' dequeued for processing (#reqid 50c3694f-4406-4792-8466-ccbd68d75b52)
2023-03-15 04:21:06: Object Detection (Net): Command completed in 33 ms. (command timing) in Object Detection (Net)
2023-03-15 04:21:06: Response received (#reqid 50c3694f-4406-4792-8466-ccbd68d75b52)
2023-03-15 04:21:06: Latest version available is 2.0.8-Beta
2023-03-15 04:21:06: Current Version is 2.0.8-Beta
2023-03-15 04:21:06: Server: This is the latest version
2023-03-15 04:21:08: Latest version available is 2.0.8-Beta
2023-03-15 04:21:11: Client request 'custom' in the queue (#reqid 1e92ce5f-9878-4ea7-b73f-a0a19fbafdbc)
2023-03-15 04:21:11: Request 'custom' dequeued for processing (#reqid 1e92ce5f-9878-4ea7-b73f-a0a19fbafdbc)
2023-03-15 04:21:11: Client request 'custom' in the queue (#reqid 05b41913-fb36-4e40-99ac-443d67af8a33)
2023-03-15 04:21:11: Request 'custom' dequeued for processing (#reqid 05b41913-fb36-4e40-99ac-443d67af8a33)
2023-03-15 04:21:11: Client request 'custom' in the queue (#reqid 106d100d-b9b0-424d-9d73-b7d13118a254)
2023-03-15 04:21:11: Request 'custom' dequeued for processing (#reqid 106d100d-b9b0-424d-9d73-b7d13118a254)
2023-03-15 04:21:11: Request 'custom' dequeued for processing (#reqid 2e2d359a-6ae7-4ff9-b0af-6ab55f09f7ca)
2023-03-15 04:21:11: Client request 'custom' in the queue (#reqid 2e2d359a-6ae7-4ff9-b0af-6ab55f09f7ca)
2023-03-15 04:21:11: Client request 'custom' in the queue (#reqid 6eef68f1-0928-4346-9fee-a72826a9c5ad)
2023-03-15 04:21:14: Client request 'custom' in the queue (#reqid 20add6d3-7e6d-487b-b66a-4d85d60c5aba)
2023-03-15 04:23:11: Client request 'custom' in the queue (#reqid abd6c62f-b767-4a7f-b385-d8e92b2e3eb7)
2023-03-15 04:23:11: Client request 'custom' in the queue (#reqid bd6ed854-c9f8-4810-b5e2-dd0ded56086d)
2023-03-15 04:23:12: Client request 'custom' in the queue (#reqid d069e6ec-e1ba-4edd-ba67-bcb874c28cd6)
2023-03-15 04:23:12: Client request 'custom' in the queue (#reqid 058d46da-9b84-4a5f-ba39-9457695ea4fe)
2023-03-15 04:23:12: Client request 'custom' in the queue (#reqid 6b37165e-0618-4916-8e06-f3ba5b883b6f)
2023-03-15 04:23:12: Client request 'custom' in the queue (#reqid d92a671f-1d1e-4d9c-87cc-247612d934bf)
2023-03-15 04:23:34: Object Detection (Net): Command completed in 142798 ms. (command timing) in Object Detection (Net)
Thanks;
Steve
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The logs come from the server, so the server is running. It seems to be the ObjectDetectionNet module that's having issues. It's a .NET module.
Have you tried switching to the ObjectDetectionYolo module? This is a Python module, and your experience may be different. It's worth a shot.
Also: do you have any back or system processes (eg disk defrag) that runs at 4:21AM?
cheers
Chris Maunder
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Thanks Chris;
I had been using the Yolo CPU module for a while. However, I could never get the response time any lower than 150 - 300 ms, so I have been changing modules between the yolo 5.6.2, .net module both CPU and GPU, and I tried my gt710 with the yolo 5.3.1 module as was recommended by Mike Lud. I was never able to get the gt710 to do anything, the Code project server info only shows the Intel on board gpu. That's why I asked whether I had to install cuda and which version to try the gt710.
Fyi, the server actually quit about 2 hours later, about 6:00 pm. Blue Iris kept recording with no response from ai, until it quit at about 12:30 am the next day. As I said, when I woke up and started wondering why I had no alerts in the Blue Iris Android app any later than ~4:30 pm the previous day, I found the machine completely hung.
That clip from the log at 4:30 am is when I manually shut down and rebooted the machine.
I was just surprised, I don't/can't keep checking to see if the ai is working. The notifications depend on it. I've never seen it do this before.
Thanks again.
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First total Nieve Newbee here. I'd like to load about 600 images for facial recognition and have the text for the image to be the file name. Is there a way to do this? I'm using this in Blue Iris and also wondering if I'm going to overwhelm the system trying to scan through that many images?
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I may have used my only advice (READ THE DOCS) on myself!
POST: http: Seems to be what I'm looking for.
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My BI system is fundamentally working but checking the log I can see a lot of connection refusals. The machine is stand alone dedicated to BI. Has anyone else experienced this issue?
Operating System: Windows (Microsoft Windows 11 version 10.0.22621)
CPUs: 1 CPU x 8 cores. 16 logical processors (x64)
GPU: NVIDIA GeForce GTX 1060 6GB (6 GiB) (NVidia)
Driver: 516.94 CUDA: 11.7 Compute: 6.1
System RAM: 32 GiB
Target: Windows
BuildConfig: Release
Execution Env: Native
Runtime Env: Production
.NET framework: .NET 7.0.3
System GPU info:
GPU 3D Usage 10%
GPU RAM Usage 4 GiB
Video adapter info:
Microsoft Remote Display Adapter:
Adapter RAM 0
Driver Version 10.0.22621.608
Video Processor
NVIDIA GeForce GTX 1060 6GB:
Adapter RAM 4 GiB
Driver Version 31.0.15.1694
Video Processor NVIDIA GeForce GTX 1060 6GB
Global Environment variables:
CPAI_APPROOTPATH = C:\Program Files\CodeProject\AI
CPAI_PORT = 32168
2023-03-14 00:25:54: Object Detection (YOLOv5 6.2): Queue and Processing Object Detection (YOLOv5 6.2) command 'custom' (#reqid c459142f-859e-4b42-aebf-2159504140ae) took 17ms (command timing) in Object Detection (YOLOv5 6.2)
2023-03-14 00:25:55: Request 'custom' dequeued for processing (#reqid 168643f4-0f0c-4cd2-9fc3-7a28ea787b6f)
2023-03-14 00:25:55: Client request 'custom' in the queue (#reqid 168643f4-0f0c-4cd2-9fc3-7a28ea787b6f)
2023-03-14 00:25:55: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command in Object Detection (YOLOv5 6.2)
2023-03-14 00:25:55: Object Detection (YOLOv5 6.2): Detecting using ipcam-general in Object Detection (YOLOv5 6.2)
2023-03-14 00:25:55: Response received (#reqid 168643f4-0f0c-4cd2-9fc3-7a28ea787b6f)
2023-03-14 00:25:55: Object Detection (YOLOv5 6.2): Queue and Processing Object Detection (YOLOv5 6.2) command 'custom' (#reqid 168643f4-0f0c-4cd2-9fc3-7a28ea787b6f) took 18ms (command timing) in Object Detection (YOLOv5 6.2)
2023-03-14 00:26:05: ModuleRunner Stop
2023-03-14 00:26:05: Sending shutdown request to python/ObjectDetectionYolo
2023-03-14 00:26:05: Client request 'Quit' in the queue (#reqid 70c1a52c-b34c-43a7-be52-1f0ed2d4d2c5)
2023-03-14 00:26:09: detect_adapter.py: Not using half-precision for the device 'NVIDIA GeForce GTX 1060 6GB'
2023-03-14 00:26:09: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:09: detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1060 6GB'
2023-03-14 00:26:09 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:10: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:10: detect_adapter.py: Pausing on error for 1.0 secs.
2023-03-14 00:26:10 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:11: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:11: detect_adapter.py: Timeout connecting to the server
2023-03-14 00:26:11 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:12: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:12: detect_adapter.py: Timeout connecting to the server
2023-03-14 00:26:12: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:12 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:13: detect_adapter.py: Pausing on error for 1.0 secs.
2023-03-14 00:26:13: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:13: detect_adapter.py: Pausing on error for 1.0 secs.
2023-03-14 00:26:13 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:14: detect_adapter.py: Pausing on error for 2.0 secs.
2023-03-14 00:26:14: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:14: detect_adapter.py: Pausing on error for 2.0 secs.
2023-03-14 00:26:14 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:14: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:15: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:15: detect_adapter.py: Pausing on error for 2.0 secs.
2023-03-14 00:26:15: detect_adapter.py: Timeout connecting to the server
2023-03-14 00:26:15: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:16: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-14 00:26:16: detect_adapter.py: Unable to store log entry: Permission denied
2023-03-14 00:26:16 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
modified 16-Mar-23 3:46am.
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A full re-boot has resolved the issue for now. I fear that it is just a matter of time before the anomaly returns!
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Well that didn't last long!
Chris do you have any ideas?
2023-03-15 05:32:49: Client request 'custom' in the queue (#reqid b4636fc0-b7b0-4709-8b9d-f7fb21f84219)
2023-03-15 05:32:49: Request 'custom' dequeued for processing (#reqid b4636fc0-b7b0-4709-8b9d-f7fb21f84219)
2023-03-15 05:32:49: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command in Object Detection (YOLOv5 6.2)
2023-03-15 05:32:49: Object Detection (YOLOv5 6.2): Retrieved objectdetection_queue command in Object Detection (YOLOv5 6.2)
2023-03-15 05:32:49: Object Detection (YOLOv5 6.2): Detecting using ipcam-general in Object Detection (YOLOv5 6.2)
2023-03-15 05:32:49: Object Detection (YOLOv5 6.2): Detecting using ipcam-general in Object Detection (YOLOv5 6.2)
2023-03-15 05:32:49: Response received (#reqid 2b438aa2-5fd5-41b9-b96e-d6a0c505a5be)
2023-03-15 05:32:49: Object Detection (YOLOv5 6.2): Queue and Processing Object Detection (YOLOv5 6.2) command 'custom' (#reqid 2b438aa2-5fd5-41b9-b96e-d6a0c505a5be) took 102ms (command timing) in Object Detection (YOLOv5 6.2)
2023-03-15 05:32:49: Response received (#reqid b4636fc0-b7b0-4709-8b9d-f7fb21f84219)
2023-03-15 05:32:49: Object Detection (YOLOv5 6.2): Queue and Processing Object Detection (YOLOv5 6.2) command 'custom' (#reqid b4636fc0-b7b0-4709-8b9d-f7fb21f84219) took 100ms (command timing) in Object Detection (YOLOv5 6.2)
2023-03-15 05:32:59: ModuleRunner Stop
2023-03-15 05:32:59: Sending shutdown request to python/ObjectDetectionYolo
2023-03-15 05:32:59: Client request 'Quit' in the queue (#reqid af7985ac-67bb-4a17-bd9b-214801cb0587)
2023-03-15 05:33:01: detect_adapter.py: Not using half-precision for the device 'NVIDIA GeForce GTX 1060 6GB'
2023-03-15 05:33:01: detect_adapter.py: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?objectdetection_queue: [ConnectionRefusedError] : Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
2023-03-15 05:33:01: detect_adapter.py: Inference processing will occur on device 'NVIDIA GeForce GTX 1060 6GB'
2023-03-15 05:33:01: detect_adapter.py: Timeout connecting to the server
2023-03-15 05:33:01 [ConnectionRefusedError]: Unable to check the command queue objectdetection_queue. Is the server running, and can you connect to the server?
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I believe the error is caused by BI blocking access to the AI.Server. After disabling BI from using the Nvidia GPU, I have not had any errors in the last 10 hours.
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cheers
Chris Maunder
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Please share more
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Say What!! I thought cars only went to the Vet!!!!
Essaf
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I wish.
Actually an aftermarket Android powered screen hosting Apple CarPlay. I had to pop out of CarPlay, dive into the android settings, get both my laptop and the screen connected to my Phone's hotspot, track down the IP addresses, get everything running, all while playing whack-a-mole as the head unit kept automatically trying to go back into CarPlay mode. I finally got it and then realised I didn't have any demo images on the head unit with which to play with in the AI Explorer.
cheers
Chris Maunder
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Hello!
I'm very satisfied with the CodeProject AI and I managed to put the CodeProject AI together for off-line use (no internet).
I have two questions here:
1. Is it possible to have the AI search on the recorded video? Meaning, run the AI on the recorded video to look for specific things. I'm using the AI with Agent DVR (I put together Agent DVR and AI for video analytic solely) and now, I'm thinking to look for a specific thing on the recorded video, but instead of viewing it from the beginning to the end, I wanted to see if I can just have the AI search for me. Is it possible?
2. I tried to put ALPR together but I'm running into an error that it is trying to connect to the internet or something. (I'm trying to run it in local network only).
11:07:47:ALPR_adapter.py: Traceback (most recent call last):
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connection.py", line 175, in _new_conn
11:07:47:ALPR_adapter.py: (self._dns_host, self.port), self.timeout, **extra_kw
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\util\connection.py", line 72, in create_connection
11:07:47:ALPR_adapter.py: for res in socket.getaddrinfo(host, port, family, socket.SOCK_STREAM):
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\AnalysisLayer\bin\windows\Python37\lib\socket.py", line 752, in getaddrinfo
11:07:47:ALPR_adapter.py: for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
11:07:47:ALPR_adapter.py: socket.gaierror: [Errno 11002] getaddrinfo failed
11:07:47:ALPR_adapter.py: During handling of the above exception, another exception occurred:
11:07:47:ALPR_adapter.py: Traceback (most recent call last):
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connectionpool.py", line 710, in urlopen
11:07:47:ALPR_adapter.py: chunked=chunked,
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connectionpool.py", line 386, in _make_request
11:07:47:ALPR_adapter.py: self._validate_conn(conn)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connectionpool.py", line 1042, in _validate_conn
11:07:47:ALPR_adapter.py: conn.connect()
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connection.py", line 358, in connect
11:07:47:ALPR_adapter.py: self.sock = conn = self._new_conn()
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connection.py", line 187, in _new_conn
11:07:47:ALPR_adapter.py: self, "Failed to establish a new connection: %s" % e
11:07:47:ALPR_adapter.py: urllib3.exceptions.NewConnectionError: : Failed to establish a new connection: [Errno 11002] getaddrinfo failed
11:07:47:ALPR_adapter.py: During handling of the above exception, another exception occurred:
11:07:47:ALPR_adapter.py: Traceback (most recent call last):
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\requests\adapters.py", line 499, in send
11:07:47:ALPR_adapter.py: timeout=timeout,
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\connectionpool.py", line 788, in urlopen
11:07:47:ALPR_adapter.py: method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\urllib3\util\retry.py", line 592, in increment
11:07:47:ALPR_adapter.py: raise MaxRetryError(_pool, url, error or ResponseError(cause))
11:07:47:ALPR_adapter.py: urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='paddleocr.bj.bcebos.com', port=443): Max retries exceeded with url: /PP-OCRv3/english/en_PP-OCRv3_det_infer.tar (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 11002] getaddrinfo failed'))
11:07:47:ALPR_adapter.py: During handling of the above exception, another exception occurred:
11:07:47:ALPR_adapter.py: Traceback (most recent call last):
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\ALPR_adapter.py", line 19, in
11:07:47:ALPR_adapter.py: from ALPR import detect_platenumber
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\ALPR.py", line 33, in
11:07:47:ALPR_adapter.py: rec_model_dir = opts.rec_model_dir)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\paddleocr\paddleocr.py", line 506, in __init__
11:07:47:ALPR_adapter.py: maybe_download(params.det_model_dir, det_url)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\paddleocr\ppocr\utils\network.py", line 53, in maybe_download
11:07:47:ALPR_adapter.py: download_with_progressbar(url, tmp_path)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\paddleocr\ppocr\utils\network.py", line 26, in download_with_progressbar
11:07:47:ALPR_adapter.py: response = requests.get(url, stream=True)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\requests\api.py", line 73, in get
11:07:47:ALPR_adapter.py: return request("get", url, params=params, **kwargs)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\requests\api.py", line 59, in request
11:07:47:ALPR_adapter.py: return session.request(method=method, url=url, **kwargs)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\requests\sessions.py", line 587, in request
11:07:47:ALPR_adapter.py: resp = self.send(prep, **send_kwargs)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\requests\sessions.py", line 701, in send
11:07:47:ALPR_adapter.py: r = adapter.send(request, **kwargs)
11:07:47:ALPR_adapter.py: File "C:\Program Files\CodeProject\AI\modules\ALPR\bin\windows\python37\venv\lib\site-packages\requests\adapters.py", line 565, in send
11:07:47:ALPR_adapter.py: raise ConnectionError(e, request=request)
11:07:47:ALPR_adapter.py: requests.exceptions.ConnectionError: HTTPSConnectionPool(host='paddleocr.bj.bcebos.com', port=443): Max retries exceeded with url: /PP-OCRv3/english/en_PP-OCRv3_det_infer.tar (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 11002] getaddrinfo failed'))
Based on the last line, it seems like it is either trying to download something or connect to an internet.
Any idea if I need to download something or what can I do with this?
The version I'm using is 2.0.8, running on Win 11. I'm not using any GPU but simply runs the AI on CPU.
Thank you for your help!
ML,
Toby
modified 13-Mar-23 12:16pm.
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Update:
I managed to get it sort of working. (At least the system is not giving an obvious error). I ran the ALPR and tried to recognize a plate but I would not get any result and got the following code:
09:17:26:ALPR_adapter.py: [2023/03/17 09:17:26] ppocr DEBUG: Namespace(alpha=1.0, benchmark=False, beta=1.0, cls_batch_num=6, cls_image_shape='3, 48, 192', cls_model_dir='paddleocr/ch_ppocr_mobile_v2.0_cls_infer', cls_thresh=0.9, cpu_threads=10, crop_res_save_dir='./output', det=True, det_algorithm='DB', det_box_type='quad', det_db_box_thresh=0.4, det_db_score_mode='fast', det_db_thresh=0.3, det_db_unclip_ratio=2.0, det_east_cover_thresh=0.1, det_east_nms_thresh=0.2, det_east_score_thresh=0.8, det_limit_side_len=960, det_limit_type='max', det_model_dir='paddleocr/en_PP-OCRv3_det_infer', det_pse_box_thresh=0.85, det_pse_min_area=16, det_pse_scale=1, det_pse_thresh=0, det_sast_nms_thresh=0.2, det_sast_score_thresh=0.5, draw_img_save_dir='./inference_results', drop_score=0.4, e2e_algorithm='PGNet', e2e_char_dict_path='./ppocr/utils/ic15_dict.txt', e2e_limit_side_len=768, e2e_limit_type='max', e2e_model_dir=None, e2e_pgnet_mode='fast', e2e_pgnet_score_thresh=0.5, e2e_pgnet_valid_set='totaltext', enable_mkldnn=False, fourier_degree=5, gpu_mem=500, help='==SUPPRESS==', image_dir=None, image_orientation=False, ir_optim=True, kie_algorithm='LayoutXLM', label_list=['0', '180'], lang='en', layout=True, layout_dict_path=None, layout_model_dir=None, layout_nms_threshold=0.5, layout_score_threshold=0.5, max_batch_size=10, max_text_length=25, merge_no_span_structure=True, min_subgraph_size=15, mode='structure', ocr=True, ocr_order_method=None, ocr_version='PP-OCRv3', output='./output', page_num=0, precision='fp32', process_id=0, re_model_dir=None, rec=True, rec_algorithm='CRNN', rec_batch_num=6, rec_char_dict_path='C:\\Program Files\\CodeProject\\AI\\modules\\ALPR\\bin\\windows\\python37\\venv\\lib\\site-packages\\paddleocr\\ppocr\\utils\\en_dict.txt', rec_image_inverse=True, rec_image_shape='3, 48, 320', rec_model_dir='paddleocr/en_PP-OCRv3_rec_infer', recovery=False, save_crop_res=False, save_log_path='./log_output/', scales=[8, 16, 32], ser_dict_path='../train_data/XFUND/class_list_xfun.txt', ser_model_dir=None, show_log=True, sr_batch_num=1, sr_image_shape='3, 32, 128', sr_model_dir=None, structure_version='PP-StructureV2', table=True, table_algorithm='TableAttn', table_char_dict_path=None, table_max_len=488, table_model_dir=None, total_process_num=1, type='ocr', use_angle_cls=False, use_dilation=False, use_gpu=False, use_mp=False, use_npu=False, use_onnx=False, use_pdf2docx_api=False, use_pdserving=False, use_space_char=True, use_tensorrt=False, use_visual_backbone=True, use_xpu=False, vis_font_path='./doc/fonts/simfang.ttf', warmup=False)
Any idea what went wrong with it? I'm not quite understand the errors here.
ML,
Toby
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That is normal with the ALPR first starts up. Try testing it using Explorer like below
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Hi Mike,
Thank you for your reply. After seeing your image, I realized that the Yolo was off...
I turned it on and it recognize some test images now. But for some reason, it won't recognize the big plates image. Any idea? (See below).
(I know the process speed is slow, I'm getting a GTX 1070 Ti and hope it will handle it.)
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The ALPR module is designed to read plates on a wider view not zoomed in images of plates.
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Dear Mike,
I see. That means there is nothing wrong with my ALPR than, besides slow on processing.
That answered my question. Thanks a lot!
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