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Some success with a coral tpu (m.2) with CPAI and BI
The AItool (when it works) is a great bit if kit Releases · VorlonCD/bi-aidetection (github.com) You can add more control and more servers to send analysis to. -
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Some success with a coral tpu (m.2) with CPAI and BI
This may be of interest in the json ("PreInstall": false for all EfficientDet models). MobileNet is set to true I am changing this to true to see the effect. "DownloadableModels":[ { "Name": "MobileNet Large", "Filename": "objectdetection-mobilenet-large-edgetpu.zip"... -
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Some success with a coral tpu (m.2) with CPAI and BI
Also the Vision detection on the dashboard does not say what size model it is using. This is after I press custome detect several times so it is 'warmed up' I'm assuming this is medium or even large as the same pics only take 40+ms on my cameras # Label Confidence 0 person 79%... -
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Some success with a coral tpu (m.2) with CPAI and BI
I'm sure in future versions it will improve. I've removed my gpu now as I'm happy so far. efficientdet-lite whether it is small or medium But also my 2nd instance with yolov8 large using the AITOOL to my unraid cpai docker works well as a failover and double check So the blue line indicates the... -
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Some success with a coral tpu (m.2) with CPAI and BI
Good catch see what you mean. I had mine set to efficientdet-lite medium. Tested in the dashboard and took 434ms! Then ran trigger on my cameras and got this in the logs (went from 434ms to 79ms with it stating it forced a model reload. Then I tested the same pic in the dashboard and it was... -
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Some success with a coral tpu (m.2) with CPAI and BI
I had to go into the modulesettings.json and update several parameters myself and save it. autostart/model/size etc Thought they had fixed that in 2.8 though C:\Program Files\CodeProject\AI\modules\ObjectDetectionCoral\ -
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Some success with a coral tpu (m.2) with CPAI and BI
So many settings in BI also that maybe we have different set ups. I still don't fully understand what they all do after 3-4 years of using BI. Yes always found CPAI more stable in a docker container, ether on proxmox lxc or on unraid which I have in addition. The AItool on my Blueiris VM is a... -
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Some success with a coral tpu (m.2) with CPAI and BI
I have 2 instances running and the one in docker (unraid app) seems to be much more stable than the cpai service on the windows. Maybe due to it using the M2 coral as opposed to the usb coral on the windows. Plan to get a couple more pcie corals and put them in the m2 wifi slots or pcie adaptor... -
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Pushover snapshots from Frigate via nodered?
Awesome!! You hero! Spent hours and hours trying to get that to work!! Snaphots coming in as expected. -
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Pushover snapshots from Frigate via nodered?
Perfect I'll give this a go later thanks. Yes I had all the keys/mqtt set up etc- but had issues with the payload and buffer encoding part. I'll have have a look at your json and adjust. Many thanks -
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Pushover snapshots from Frigate via nodered?
Can't for the life of me get frigate mqtt topic 'frigate/living/person/snapshot' in nodered to send the snapshot to my pushover api (without using homassistant) I've used telegram in nodered for ages and get snaphots but want to use the same method to send to my pushover. Same flow just sends... -
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8-9ms inference speeds with OpenVino on a cpu 7th gen!!
caught my little cavapoo quite well just now plus a motorbike -
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8-9ms inference speeds with OpenVino on a cpu 7th gen!!
Well after using coral tpu devices (usb and m2) with Frigate, I came across openvino model on Frigate. Decided to give it a try, very simple set up, just a few lines of code in the config. Fire it up on my dell 7th gen intel with no gpu or tpu. Well I'll be dipped! Faster than the coral usb... -
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Which intel cpu's best for codeproject?
I was under the impression that some of the latest gen with quicksync were fast and efficient. -
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BlueIris and CPAI on Proxmox
I've used proxmox to host windows and BI a lot in the past. Just gone back to a dedicated windows for performance really. Just found the windows on a VM was never that good. Even the stripped versions like x-lite and spectre. Dedicated windows just had an edge on it I would use BI on proxmox... -
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Some success with a coral tpu (m.2) with CPAI and BI
Always tweaking the settings tbh - at the moment most exterior cams have this set in cpai. Had it set to 20 post triggers before - but this makes no difference on the gpu objects and % confidence vary a little in each cam. On a busy day it can go for a long time and rarely exit P8 state -
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Some success with a coral tpu (m.2) with CPAI and BI
All of the time 6 of the exterior cameras. Sometimes the interior ones when I'm out. FPS all pretty low but high fps is not really needed for the analysis But 6 of them using the gpu - it flies through the images at less than 50ms 13:28:11:Response rec'd from Object Detection (YOLOv5 3.1)... -
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Some success with a coral tpu (m.2) with CPAI and BI
Most of the time my gpu gtx970 is at idle in P8 state at about 24w the unraid plugin says. Maybe less than that I've read If it runs at 24w over 24 hours - calculated extra electricity cost 3 pesos here (day is split into 3 different costs depending on the hour!) 11 pesos per Kwh for 4 hours 5... -
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Non movemement feature
Same here - Can't get it to send any alerts, mqtt for debugging. Set it to 3 seconds and low sensitivity also. Can't see any triggers using the rectangles while watching but does not alert me for non-detection -
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Which intel cpu's best for codeproject?
I have only got amd cpu's and use a gpu. But I would like to know from users with intel processors which ones that can achieve inference speeds of 40-100ms with yolov5 medium size models. Thanks -
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Some success with a coral tpu (m.2) with CPAI and BI
BlueIris license blocked trying to reapply an old config!! sent email to support. Anyways with my gtx970 I have found YOLOv5 3.1 to be most effective. Tried v8.0 and it did not pickup small animals possibly due to the lack of custom models? Only had general. 3.1 has ipcam-combined which in my... -
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Some success with a coral tpu (m.2) with CPAI and BI
After several days of tweaking and some frustration I may give in and put my gpu back in. Can't fault the tpu speed and low power consumption but the models are just not working as I want them to. Fine if you just want to identify people in good light. My nvidia gpu was spot on 90% of the time. -
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Some success with a coral tpu (m.2) with CPAI and BI
I'm trying out EfficientNet for a couple of days Difference between SSD MobileNet, EfficientNet and Faster R-CNN ResNet 50 | by Elven Kim | Medium -
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Some success with a coral tpu (m.2) with CPAI and BI
Nice! They've made decent improvements as now it appears to work. Still buggy though - not sure what model it is using really as the dashboard always says mobilenet SSD. I switched to yolov5 but all inference speeds seems to be the same for mobilenet, yolov8 and yolov5. I'd like to know how... -
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How to train a custom YOLOv5 model using CodeProject.AI Training for YoloV5 6.2 module
If I find another model .tflite file on git how do I program cpai to use that specific custom model? I'm at the bottom of the learning curve.. -
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How to train a custom YOLOv5 model using CodeProject.AI Training for YoloV5 6.2 module
Can these models be used with your coral tpu or just Nvidia gpu/cpu? -
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Some success with a coral tpu (m.2) with CPAI and BI
very true - sometimes a compromise - a small fluffy dog or cat may be recognised as a sheep or rabbit on the small model but not at all on the medium - large model. I'm trying to understand how to use some customized models from git but do not understand how to implement and use them yet like... -
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Some success with a coral tpu (m.2) with CPAI and BI
Some interesting results testing the tiny, small, medium and large MobileNet SSD with the same picture. The small model found far more objects that all the other models even though some were wrong! -
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Some success with a coral tpu (m.2) with CPAI and BI
One odd observation is using the dashboard. Even if I switch model and under the info it says yolov8 or Efficientdetlite for example - the dashboard only ever gives me the option to test with mobilenet ssd. What do you observe?