Yes, I saw that 5.6.2.1 was just released, with the usual rather minimal release notes alluding to custom CodeProject AI settings. Ok, nice to see, but are we expecting any further refinements that will open up any additional tweaking?
Yes, I saw that 5.6.2.1 was just released, with the usual rather minimal release notes alluding to custom CodeProject AI settings. Ok, nice to see, but are we expecting any further refinements that will open up any additional tweaking?
Yes, I'm sure there will be further refinements, but with MikeLud1's help, mine was already working fine. I notice that 5.6.2.1 does not appear to have edited my registry.Yes, I saw that 5.6.2.1 was just released, with the usual rather minimal release notes alluding to custom CodeProject AI settings. Ok, nice to see, but are we expecting any further refinements that will open up any additional tweaking?
Interesting, yes I agree that overall CPAI is working well, and the speed is pretty good even on a CPU only system (I am averaging 160ms times on a i5-8500). I haven't been able to get the yolov5l working yet: I did copy it into the same folder, and changed the model name in the camera AI settings, but it wasn't working for me. I will double check everything and try again tonight.Yes, I'm sure there will be further refinements, but with MikeLud1's help, mine was already working fine. I notice that 5.6.2.1 does not appear to have edited my registry.
Experimenting with object detection models, it seems to me that yolov5 works better than ipcam-general etc. I copied the yolov5l file into the same directory as AI\AnalysisLayer\ObjectDetectionYolo\custom-models and yolov5 finds the objects more reliably and more accurately although CodeProject sometimes does not choose the best image with the highest percentage object confidence. See examples below, including difficult lighting conditions (the cyclist was at dusk):-
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That's been up for a day or two at least, but I haven tried running it: I did try to install 1.6.1 over a fresh install of 1.6.0 and it failed, maybe that is sorted out now. On the other hand, it probably doesn't have any applicable changes for me (CPU only), as much of the last several days of development seem focused on adding support for more (mostly older) Nvidia cards.
The better support for older NVidia GPUs was added with all the help from users that tested my revised process.py. Below is the revised code.
device_name = torch.cuda.get_device_name(self.device)
# https://www.nvidia.com/en-us/design-visualization/previous-quadro-desktop-gpus/
no_half = ["TU102","TU104","TU106","TU116", "TU117",
"GeForce RTX 2060", "GeForce RTX 2070", "GeForce RTX 2080",
"GeForce GTX 1650", "GeForce GTX 1660", "MX550", "MX450",
"Quadro RTX 8000", "Quadro RTX 6000", "Quadro RTX 5000", "Quadro RTX 4000"
"Quadro P1000", "Quadro P620", "Quadro P400",
"T1000", "T600", "T400","T1200","T500","T2000",
"Tesla T4"]
self.half = not any(check_name in device_name for check_name in no_half)
Just do a system reboot, everything will startup fineWith Blue Iris 5.6.2.1 and CPAI 1.6.2-Beta.
I thought this was working before. Doesn't matter much to me but just pointing out what I see because why not . Maybe bc I am on the bleeding edge?
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Just do a system reboot, everything will startup fine
Yes, that's one way obviously.Yep service is running fine. I rebooted and it run fines. The "issue" is only if I hit the stop button in Blue Iris. Simple solution for me, just don't hit the stop button .
Just do a system reboot, everything will startup fine
I just stopped it, waited a minute, got distracted... A few minutes later I got a pushover alert for a cat on our cars. Lol. Meh, I suppose I could set the service to manual just to test this but seems I don't need to use the buttons anyhow lol.The stop/start does work. but you have to allow at least 30-45 seconds before you can hit the start button...give or take
If BI tries to do a detection and the AI server does not respond BI will try to restart the service, if you look through the log you will see the failure and restart.I just stopped it, waited a minute, got distracted... A few minutes later I got a pushover alert for a cat on our cars. Lol. Meh, I suppose I could set the service to manual just to test this but seems I don't need to use the buttons anyhow lol.
For me Yolo is used by default, no need to copy the custom model.I still struggling with getting a YOLO model working, and am looking for suggestions: I have moved a copy of yolov5l-cls.pt into the appropriate folder (CodeProject\AI\AnalysisLayer\ObjectDetectionYolo\custom-models), yet when I try to enable the yolov5l-cls model in the camera, Custom models box, here is my result in the CPAI log:
10:22:02 PM: Object Detection (YOLO): Detecting using yolov5l-cls
10:22:02 PM: Object Detection (YOLO): Unable to load model at C:\Program Files\CodeProject\AI\AnalysisLayer\ObjectDetectionYolo\custom-models\yolov5l-cls.pt (Can't get attribute 'ClassificationModel' on )
10:22:02 PM: Object Detection (YOLO): Unable to create YOLO detector for model yolov5l-cls
What am I doing wrong here?
@MikeLud1, even though I shut down CodeProject.AI services running in the background, I cannot overwrite the edited modulesettings.json file, why?To improve accuracy you can make the below change to the modulesettings.json. Also you should uncheck Use main stream if available, having it check does not improve accuracy it only slows down the detection.
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The file does not allow edit unless you change the file ownership.@MikeLud1, even though I shut down CodeProject.AI services running in the background, I cannot overwrite the edited modulesettings.json file, why?
Yes, this could be another way to solve the problem.The file does not allow edit unless you change the file ownership.
The simple solution is: Copy the file to your desktop, edit it and then Copy over the original file. Alternatively I'm guessing (haven't tried) taking ownership of the file will also work.