Recent content by Pentagano

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

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

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...

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.

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

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...

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..

So coming soon then possibly?

Can these models be used with your coral tpu or just Nvidia gpu/cpu?

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...

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!

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?

Just tried the yolov8 large model which takes significantly longer and it does not detect this bird clearly shown in the snapshot. I would have expected it to pick this up.. maybe contrast issues? My gpu on yolov3.1 picked up anything and everything

My My son is approaching 15 and starting to get invites to the quinceneras. 15yr old latin celebrations here. Formal parties until 5am!! So us poor parents during the whole year end up either staying up all hours waiting to collect them at 430am or go to bed early and set the alarm clock. Can...

Thanks but I have limited fibre each month, need to conserve it for working remotely. If I start working on anything in the cloud then it consumes my monthly GB quota and I'm close to the edge each month as it is. I try to keep everything local