Frigate+ Model Launch

[blakeblackshear]

I am excited to announce that Frigate+ Models are ready to be rolled out. I can't believe it has been over 2 years since the initial discussion about the idea. Thanks to everyone for your patience and encouragement over that time.

I will be inviting users to sign up for a subscription incrementally to ensure I can address any issues and not overwhelm the system. If you would like to be invited, please send me an email at blake@frigate.video from the email address associated with your Frigate+ account.

After much consideration, I decided on annual subscriptions as a pricing model. You can think of the annual subscription as the initial buy in to cover the costs of Frigate+ and the development and maintenance of the base model. However, I also implemented a credit based system for training that I think everyone will be happy with.

• With your annual subscription of $50, you will get 12 training credits with the idea that you can fine tune a model monthly
• I will also be adding the ability to purchase additional packs of credits for $5 each
• It will take one credit to train a fine tuned model
• Models trained are yours to keep and use forever (under the terms and conditions) since you paid for the resources required to train it

Before subscribing, please read through the documentation on how the models work so you are clear on what you are purchasing.

[T3chArmy]

Very excited for this launch! Can't wait to continue to see this project grow!

So, I have a general follow up question, I feel like I already know the answer to this but would like a definitive answer.

Since the current Frigate+ Model only has a small subset of labels, if I include a label from the default model are those still detectable? or does the Frigate+ model completely override the default model?

[T3chArmy]

Thanks for following up! That's what I was thinking, but just wanted to make sure!

[dopeytree]

Is there a way to merge frigate normal & frigate+?
For example Whosatmyfeeder sends the initial detection to another container to do further analysis using another model and then returns to frigate with a sublabel.

PS I will be signing up and paying but would like to keep some other labels.

[NickM-27]

No, only one model can be used at a time. To use whosatmyfeeder along with a frigate+ model you would need to wait until frigate+ supports the bird label

[dopeytree]

Hmm my solution could be I use 2 instances of frigate. Perhaps run 0.13 beta with frigate+ custom model & then keep frigate 0.12 for sole bird detection on the google model. I have a camera dedicated to it.

[NickM-27]

yeah, if you have a camera dedicated to it that would not be a bad approach, although keep in mind you can only use a coral for a single process so a single coral could not be used for both

[shinyzard123]

What if I don't feel comfortable uploading my own images? Is there any possibility of just paying a one time fee to use the base model? I know the experience won't be as good but I'm sure it would be better than the current one

[blakeblackshear]

Not currently. You could upload and verify just 10 images from your cameras with either a false positive or images that don't have any person or car objects that you are concerned about sharing.

[shinyzard123]

Ok, that's fair, thanks for the answer 👍

[T3chArmy]

Another follow up question,

I've requested a Frigate+ model to be generated, will I receive an email once it has completed?

[NickM-27]

Yes, looks like it

[T3chArmy]

Excellent. Thanks!

[NathanVanCleave]

When annotating uploaded images, how does selecting the "Difficult?" checkbox affect it? Does it simply increase/decrease how it is weighted? Just want to make sure I'm using it correctly. If an object is more than half obscured (I still select the whole object) or relatively small I've been marking it as difficult.

[NathanVanCleave]

Along these lines, how should we go about uploading images of missed objects for annotating that didn't create an event? I know I can upload my own images, but I'm unsure if screenshots are appropriate or if I need to somehow export them from Frigate for standardization. I've been uploading old snapshots Frigate saved from months ago, but those are only of tagged events. As long as the screenshot resolution isn't worse than the saved/uploaded snapshot I'm guessing it's okay?

[NickM-27]

I did this some by downloading the clip on my mac and using the save frame as png option and then uploaded a few of those spaced seconds apart.

Also, technically in 0.13 the api exists to pull a snapshot from a specific time in the recordings

frigate/frigate/http.py

Lines 1238 to 1239 in 0858859

	@bp.route("/<camera_name>/recordings/<frame_time>/snapshot.png")
	def get_snapshot_from_recording(camera_name: str, frame_time: str):

This is something that will be supported directly in the ui in a future version of frigate.

[NathanVanCleave]

Okay, saving the frame as a PNG is something I can do. It sounds like you're at least recommending I do that or use the API instead of a screenshot then? I'm only pressing the question because it's the easiest option in the moment if I happen to catch it missing something, but it's not worth the time saved it's it's not an equally valid/confirmed option as the former.

Happy to hear this feature for the UI is on the roadmap.

[NickM-27]

Personally I don't like screenshot because it is difficult to get the edges right and the resolution will be from your screen not from the original source, plus any other compression that may happen. I don't know that it would actually matter for the training, but to me it's not difficult to use a unix timestamp and pull multiple snapshots via the api

[NathanVanCleave]

That's exactly what I was thinking about the screenshot being different. This is good enough confirmation for me not to do it this way.

I don't know how to use the api, but I'm fine with downloading the clip and saving the frame. Thanks for the replies.

[agrieco]

Probably too early for this, but it would be nice to know how much the underlying training data has changed. For instance- counters on how many images have been uploaded and used to train the new model since a user last built their own model. Maybe even by label?

In the end, I'm trying to better understand when the community aspect of the Frigate+ subscription would warrant a new model build.

[blakeblackshear]

New base models aren't automatic. I will be hand crafting those for the foreseeable future. When the next version is available, I will be making some updates in the UI and notifying users. I can show how many of your verified images were used for each model in the next update.

[mabed-fr]

Great !

Has this functionality been addressed? In which version will this be deployed? I will wait for this version to subscribe.

[mabed-fr]

Is it possible to publish the number of base images and other statistics on the base model of frigate+?

[blakeblackshear]

I am testing a new base model now and it does appear to be an improvement. Just making some changes in the backed to support the roll out. After the first few updates the process will get smoother, and I will be able to update more frequently.

[borgqueenx]

how much percentage would you say it improved? (ofcourse a rough estimate) got my coral today, want to spend my first credit when the new base model is out and start training.

[Fervere]

Ive subscribed. But dont want to request a model.. because I have some cameras with some pictures on them and they dont show up.
And on the main camera I want to test this out on, I had an old camera, and that also have some pictures on that Ive verified earlier.

Is it ok to mix cameras, they stand at exactly the same place but the angle might have changed a bit?
How to remove images? please add, if im blind.

If i request now, is it possible to start from scratch later?
What if I move my camera a few meters should I add a new camera and upload new pictures?
Is it possible to remove some images from the model later?

In 1 of my images now ive marked 1 person, and in the background there is a bike with a person on it. And I cant select bike anymore, what to do?

Why not allow us to add annotations on things we think is relevant so these pictures can be used later?
Id like to add my robot mower, should be simple.

[blakeblackshear]

It's ok to mix images from cameras even if the angle has changed a bit. Your model is a tuned layer from your images on top of the base model trained on a collective set of images, so your images aren't the only training data.

There isn't currently a way to remove images yet, but it's a common request, and I am working on it. Images removed later won't be used in models trained after they are removed.

There is not currently a label type for bike in the Frigate+ model set, but it is in the list for the expanded set of labels. Frigate+ models only detect a specific set of labels currently.

[NeoDuder]

Can I assume a single model covers multiple cameras?

[NickM-27]

a single model is trained on all images that you have submitted, labeled, and verified so that would include multiple cameras assuming you have submitted, labeled, and verified images from multiple cameras.

[NathanVanCleave]

What's the purpose of tagging the images by camera then? I guess I assumed the models would be somewhat specific to cameras, though that would require multiple credits I suppose. Could it be possible/beneficial to request models per camera? I've been aiming for the recommended 100+ images per camera before I request any. Maybe it's more about focussing on the hardest images (e.g., backyard with a far field of view) and not worrying about easier ones as much (e.g., doorbell where subjects are usually very close).

[NickM-27]

I'm not sure what you mean by tagging the images by camera.

But yeah I personally wouldn't expect each camera to have the same number of images as you start to use the model, this is my distribution for example

[NathanVanCleave]

That screenshot is exactly what I mean. Thought it had some special significance. Good to know.

Your distribution is exactly what I'm aiming for.

[tpjanssen]

If a request a Frigate+ plus model, will it be based on the standard model that's been trained additionally with my submitted images? The default model is pretty bad in making a difference between a cat and a dog. Will the downloaded model only become better with my own submitted images, or is it trained with all the images submitted by other users?

[tpjanssen]

Thanks for the reply.

I haven't used the default model at this house / with these camera since I moved a few months ago, but at my old house my dog was labeled as person, cat, and bird by the default model at least a few times a day.

This is what I experience as well. Frigate also identifies people as cats or dogs from time to time.

I can imagine that the base model evolves and gets better the more it's trained. What are the demands to use the extra trained model? Only the submission of 10 images? Or do you I also have to subscribe (which I will certainly do),

[NickM-27]

I think that was answered here but I would definitely personally suggest submitting images as that will make your model better than the frigate+ base model for your cameras.

[tpjanssen]

Thank you Nick. Spent some time on labelling and veryfing all my events which were identified wrong. Did some of these about a year ago, but back then it didn't make much sense. Good to hear that nowadays it does.

[pyrodex]

I submitted a few today of my wife and kid bending over triggering a dog, it was too funny.

[pyrodex]

Here is a weird example showing the steam from my tankless hot water heater this morning being classified as a dog.

[timmyag]

I might be slightly off topic,
Would having sperate models for cameras in black a while/IR mode vs colour worth considering?
I mention it here as mine produce far more confused results in BW mode and im assuming that partly as the images arnt as good but also the training data is mostly in colour. Seems worth it to not train a model for use in the day on BW images and train a model for night time with as many BW images as we can.

[NickM-27]

I have had no problems getting great day and night detection with my cameras and the frigate+ model. The color of the objects may be different but the shapes are the same.

The important part is just submitting examples that are from all different times of the day so the model is tuned on your cameras at these different times.

Here is an example of a cat detected at night

[kirsch33]

i wish it were possible to delete images from Frigate+. i uploaded a bunch of just absolute crap photos that I think are probably confusing the 1st model that i created, and would like to be able to prune these out

[bagobones]

I am about to upgrade a bunch of my cameras and being able to delete out whole camera sets and start replacing them with higher quality images would be very useful.

[ccutrer]

As long as your images are labeled correctly, I wouldn't delete them just because they are lower resolution. Remember that some number of images are taken from all contributors to train the base model, and you'll be helping out everyone.

[bagobones]

As long as your images are labeled correctly, I wouldn't delete them just because they are lower resolution. Remember that some number of images are taken from all contributors to train the base model, and you'll be helping out everyone.

I disagree at least from my experience with training faces with other models. Crap cameras will introduce a lot of blocking / mpeg artifacts to moving snapshots.

I found that if I trained off of certain camera my faces would more often match many people than individuals. My older cameras also tend to ghost more when in IR mode.

Doing some other research it seems recommended to train from a higher quality source when possible.

[NathanVanCleave]

How important is including false positives in annotations? I just got my model last night, trained on ~400 images for four outdoor cameras, and am getting a ton of false positives so far I wasn't getting before. Since the beta is pretty new I only had false positives included in <5% of my images.

If false positives are important for training, I'll hold off tweaking my masks to continue allowing them and continue uploading more images for annotation before requesting another model.

[tpjanssen]

After reading all this I think it is better to switch to the base model, and do some consistent reports next coming months. I'll try to have a good mix of true and false positives, along with a good spread of day/night reports.

@blakeblackshear is it possible to add the boxes of all detected objects to the submit function? Maybe you should not enable them by default on the website, but this will make the verification process a lot easier!

[NickM-27]

You would have to store the location of all of the objects at the moment that each snapshot is taken, that would be a lot of data to store and to keep track of. I believe Blake has already said there are plans to improve this process but there are better ways

[blakeblackshear]

is it possible to add the boxes of all detected objects to the submit function?

It's not possible. All that data is only available in real time. By the time there is an event with a submit button, all that information is long gone. My plan is to scan the image for objects again in the submit to frigate+ dialog. Eventually, the entire annotation tool will be directly in Frigate.

[blakeblackshear]

@tpjanssen

I also have some privacy concerns about that. @blakeblackshear what can you tell about this?

The privacy policy and terms should answer any questions you have. If not, let me know what questions you have.

[didi3r]

Hey I just wanted to give an update on how my detection is doing. After 2 weeks I’m by my 3rd model with a total of 1700 images and the detection has gotten way better to the point that it now detects people I even struggle to see at first glance. Like this one where it detected a person in the dark:

Or this other one where it detected a person far far away in the corner of the block:

And they are not isolated cases the model is now constantly detecting at that level of precision.

I still get some false positives during the day, but definitely way less than the default COCO model. The approach I followed was to submit true positive detections with low scores or with incorrect bounding boxes and submit pretty much all false positive I got no matter if the images were almost identical. I would say that out of the 1700 images I have submitted, almost 500 are false positives.

Next steps for me would be to train the model on very specific areas of my interest so I’m going to be more cautious on which true positives to submit and reduce the
false positive submission a little bit.

[J-Pipe]

Since I record a high-res (main) stream 24/7, but my detect stream is low-res (substream), is there any concern if I manually upload some images from my main stream into frigate+ to tag some objects? i.e., should I only upload images that are the same resolution as the detect stream?

[NickM-27]

No, there is no concern. The model is trained entirely on a single size region (320x320) so resizing and cropping occurs anyway

[T3chArmy]

Now that I've had the new model running for a few days, is it possible to flag sub labels as incorrect? Have seen several things getting flagged as Amazon/UPS/FedEx/License Plates that are not.

[TyzzyT]

You can do it just like regular labels. Upload it to Frigate+ and annotate the image

[blakeblackshear]

You can't specifically submit a false positive for the sublabels because they don't actually get their own detection region. Submitting the primary label and verifying the image will help.

[tpjanssen]

While running new the plus model I've noticed that my interference speed significantly dropped (from around 8-9 ms to 6-7 ms). Why is this? Because the model is not trained with as much labels as the standard model? Or the labels itself are not as "heavy" (trained with less images) as the standard model?

The new model has the tendency to detect perons walking on my driveway based on the lower half of the body. Most of the time I see the bounding box drawn around the legs and feet only, with 90+% scores. As a consequence, this image is also used in the event list. What your advice to do with these cases? A couple of scenario's I can come up with:

1. Leave as is...
2. Submit, confirm it is a person, and draw an extra annation box around the complete body
3. Submit, confirm it is not a person, and draw a new annation box around the complete body

Is it possible to add the area and ratio information when you hover over the bounding box in the snapshot?

[tpjanssen]

Thanks guys. I will do as you suggested. What about my last question, is it possible to add area and ration information in the snapsnot view?

[NickM-27]

not sure I understand the last question, the snapshot is a static image. you can get area and ratio information from the recordings timeline overview. The area is already shown in the bounding box on snapshots (the number next to the % score)

[tpjanssen]

But these are not always the same. I see different bounding boxes for clips and snapshots. That having said, most information is already in the snapshot's the bounding box. It shows "person: 92% 53714". Maybe you can add the ratio there as well?

[jockelandelius]

Sorry for A revisiting an old post and B for stealing someone focus in this post but... "...get area and ratio information from the recordings timeline overview". I must be a total novice but I have never seen this and I am also unable to find it now that I see it does exists... Any pointers?

[NickM-27]

in frigate 0.13 you can click the icons at the top of the event recordings and it will show an overlay of where the object was detected. You can hover over this with your mouse to see information about it

[J-Pipe]

So if I want to rename objects in the labelmap, I assume there is a new map with different numbering than the COCO one? Not seeing where the labelmap is specifically documented.

[NickM-27]

it's not documented but you can find it inside the /model_cache/<id>.json file

{
  "labelMap": {
    "0": "amazon",
    "1": "car",
    "2": "cat",
    "3": "deer",
    "4": "dog",
    "5": "face",
    "6": "fedex",
    "7": "license_plate",
    "8": "package",
    "9": "person",
    "10": "ups"
  }
}

[J-Pipe]

Wonder why the example here renames 3/4/5 as an animal. Like the indexing is 1-based.

[NickM-27]

just an example, but those docs were also added a while ago and the indexes may have changed.

[blakeblackshear]

I believe that renaming the labels will currently break the true/false positive submissions to Frigate+. The image should still upload, but any labels that aren't listed in Frigate+ will fail. I will have to think about how to handle this more gracefully.

[ccutrer]

New labels have been discussed ad nauseam. A simple search of this thread will find at least 10 requests for it. @blakeblackshear is working on it. Do not try and repurpose USPS for DHL, etc. That will just confuse the model for everyone.

[Tyler-2]

I use an email alias for Frigate that I can't send mail from. How can I subscribe?

(Gosh I can't wait to send SO MANY chicken tags when/if that's supported!)

[blakeblackshear]

Doesn't have to come from the email you registered with. Just include the registered email in your request.

[ralphv]

Hello, few questions about Frigate+.

1. Is it possible to pay a one time fee to just get upgraded models without submitting any own images to my own models?

2. If I subscribe to Frigate+ and want to face recognition to train for individual members of my family, what happens to the images we submit? They are personal images of my family and I don't want them to linger somewhere. Is it possible to have Frigate+ and train for face recognition but somehow keep the images private?

Thank you!

[blakeblackshear]

1. The base model is not directly available. That may change in the future.
2. All of this is outlined in the terms and conditions and privacy policy. Basically, I only have the rights to use your images for the purposes of providing you services via Frigate+.

[ralphv]

Thank you,

I did read your terms and conditions, but I could not find anything about retention policy unless I missed it. I did read however that you do use other submissions for fine tuning the model(s). In this case these are private images and private labels. I wouldn't want someone recognizing my family members with this model.

Is it possible to do the training locally? from my own sets? Perhaps with some sort of a proxy docker image, Happy to use my own 3090 GPU for that as long as the files don't leave my machine. Something to think about perhaps for future features. Personally I am not interested in fine tuning cars/pets and so on, my use case to identify my family members and create different notifications. Perhaps there is some third party software that can do that from the MQTT events?

Thanks for all the hard work, I can imagine software like this taking hundreds of hours of work.

[ralphv]

I think I answered my own question, looks like other projects like "Double Take" might cover my needs. Will be spending some time to check those out.

[NickM-27]

to be clear Frigate+ does face detection, not face recognition so there is no "this is bob".

if you are looking for face recognition then you will want to look at something like doubletake and compreface https://github.com/exadel-inc/CompreFace

[ralphv]

Got it. Thanks

[povlhp]

You Can upload 10 images of pure white or pure black if you don’t want to upload images from your camera But images is a requirement. I was surprised I could not download the updated base model without. Sendt fra min iPhoneDen 19. feb. 2024 kl. 04.58 skrev Ralph Varjabedian ***@***.***>: Hello, few questions about Frigate+. Is it possible to pay a one time fee to just get upgraded models without submitting any own images to my own models? If I subscribe to Frigate+ and want to face recognition to train for individual members of my family, what happens to the images we submit? They are personal images of my family and I don't want them to linger somewhere. Is it possible to have Frigate+ and train for face recognition but somehow keep the images private? Thank you! —Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you commented.Message ID: ***@***.***>

[ralphv]

Thanks for the reply

[RemakingEden]

Hi all,

So I just want to give my feedback on the 2024.0 model so far.

My Setup

• 1 Wyze cam V1 @ 4 feet high looking at cat flap
• 1 Wyze cam V2 @ 8 feet high looking at dining room
• Coral TPU
• All cameras are indoors facing

My Trainings

• 1st - 112 images
• 2nd - 400 images
• 3rd - 582 images / 1046 labels

Firstly I want to say thanks for creating Frigate and im happy to support no matter what! I really appreciate it :)

However I have been running into a lot of false positives with my models. I have tried to report these and report lots of true positives to show the model what it should be looking for. Despite this I am getting lots of false positives on coats, sliders, dog toys, dustpan and brush etc.

After nearly 600 images I think im going to resign to going back to the default model until the base model has updated to 2024.1 as my NAS is filling up too fast with false recordings.

I am aware my setup is probably not default and this may be causing the issues, also happy for any prompts on what I may be doing wrong etc.

[blakeblackshear]

This is probably due in part to the vast majority of users having only outdoor cameras. There simply aren't that many indoor images in the base model. At some threshold, I will have enough examples to consider segregating the dataset for multiple base model options for users with similar scenes.

[RemakingEden]

Brilliant, well feel free to use any of my 600 :) Although im not sure how representative they are.

[borgqueenx]

hope that we can then use these seperate models on one tpu at the same time if there are going to be multiple versions to choose from.
Simply select the model in the camera specific settings.

[NickM-27]

One tpu can only run one model

[borgqueenx]

then i hope that one day we can use openvino and the TPU combined, both running seperate models > once and if the models are split into 2 options.

[ehn]

What should we do in cases where an Amazon (etc) logo appears on a car that isn't a delivery truck, such as in this case where there is an ad for Amazon on a taxi?

On the one hand, I guess we should label it because we can't expect the model to be able to discern the two cases, and not labeling it will make it worse at recognizing logos. On the other hand, this will create false positives, in a sense, for people who want to be notified when there is an Amazon delivery but probably not when there is a taxi that happens to have an ad featuring the logo.

Labels for truck and taxi would help distinguish the cases, I guess.

As a side note, my model didn't identify the Amazon logo, but it did think it was a license plate.

[ccutrer]

Definitely label it. It's an Amazon logo. And on a vehicle. Until and unless the model can distinguish between sedan, truck, etc., it's not a false positive for an Amazon logo on a vehicle, even if it is a false positive for "Amazon delivery truck" - which is not strictly what the model is trained for.

[blakeblackshear]

Yea. I think it's appropriate to label it since it is in fact the Amazon logo.

[nshp]

On a related note, should we label amazon/fedex/ups logos on non-cars? E.g. the labeling utility allowed me to put an Amazon sub-label on a package. I could also see labeling the logo on delivery peoples' shirts. All the discussion I see is just of sub-labeling cars/trucks though.

[NickM-27]

I believe the recommendation is if the label is there then to label it. Currently the amazon label can be assigned to person as well as car and that could be expanded to packages or others in the future

[mintjberry]

Have to say I'm pretty disappointed with the accuracy of the custom model after paying the $50. I've submitted hundreds of photos (including many many false positives) and created three models in the last week

Some cropped examples:

[NickM-27]

how many cameras and example have you submitted thus far?

[mintjberry]

10 cameras. 447 verified images. Still getting some false positives on the same objects in images that I've already submitted/verified which is annoying. I'm doing a bunch more currently and will see how they go.

[NickM-27]

that's good, the docs do recommend 100 per camera as a starting point. It might also be worth verifying your motion detection sensitivity. The motion detection values in 0.13 are more sensitive than previously so it is possible that is part of the false positives you are seeing.

[borgqueenx]

i have the same issue as you, and @blakeblackshear said to give up until the new base model arrives. Our trainings we do, only do the end "tweaking" so to say. Blake is using the pictures we submitted as well, and that is the true training being done. I provided hunderds of false positives on specific stubborn spots(i have over 8k images uploaded in total), and even tried to put some true positives at stubborn spots, and retrained around 3 times, but it does not really improve. According to blake, the trainings we do improve the model by 15% max. We'l have to wait and hope the new base model improves a lot on these false positive detections. I noticed that the default coco model is currently better then the frigate+ model i am using. you could consider using that until the new base model arrives.

[NickM-27]

@borgqueenx what you're saying isn't really representative of the overall situation for each user. Like I noted in my comment the user didn't have the recommended number of images per camera for a starting point. There is likely plenty of room to submit images and improve their model.

Also as we discussed on discord the COCO model is better for you in regards to false positives but not necessarily overall because you have to consider false negatives, true positives, etc as well.

[skycryer]

Just found this topic, I registered for frigate+, send some pictures for every camera until I saw I can not pay for the model. Can I get access to the custom model stuff for testing?

[borgqueenx]

you need to write @blakeblackshear a email so he unlocks it for you, so you are able to pay. Frigate+ is still in private beta as of now.

[mintjberry]

Just found this topic, I registered for frigate+, send some pictures for every camera until I saw I can not pay for the model. Can I get access to the custom model stuff for testing?

Read the top post right at the top of this discussion (aka scroll to the top).
As explained above, you need to email blake to get a URL so you can pay for the custom model.

[tamueller]

Hi,
I'm not sure if it has been answered before, but is it helpful to submit false positives to frigate+ when I'm using openvino with the default model? I don't plan going to frigate+ any time soon, but I wouldn't mind improving the model by supplying false positives. I'm not sure though if the false positives from the openvino default model are even helpful/relevant for the frigate+ model.
Also, I can't provide an equal number of false negatives, because a) I don't get many with openvino and b) I don't want to upload pictures of my family to the model for the false negative person events.

Also a question about label set for frigate+: I saw that blake has this in the todo-list, but is there a good way to add "requests"? I might buy into frigate+ if it can detect ducks and kid/children/toddler.

[tamueller]

Yeah, I want to distinguish between adult / small children. But I might look at the bounding box thing, might get a bit messy due to the camera angle though..

[NickM-27]

Yeah, I want to distinguish between adult / small children

sounds like image classification, not object detection

[tamueller]

For me cat has to animal a very similar relation than toddler to person. But that might be the way an object oriented developer looks at this, not the way a machine learning guy would.

[NickM-27]

There is a lot more variation between a cat, dog, bird, rabbit (all animals) compared to a person where a toddler and adult are the sameish shape just different size

[ccutrer]

Yeah, I want to distinguish between adult / small children. But I might look at the bounding box thing, might get a bit messy due to the camera angle though..

Are these specifically known children? Or small children in general? If the former, you could use facial recognition (such as Double Take) to figure out which kid it is, and then it updates Frigate once it has done so. Of course this is dependent on getting a reasonable view of a face.

[IMakeTP]

Wondering does the audio detection that was introduced get changed at all when signing up for frigate+? Does the normal audio detection work as normal? Like to sign up for frigate+ but can not lose the crying audio detection for the camera as a baby monitor.

[NickM-27]

Audio detection is unrelated and unaffected

[nmcrae85]

@blakeblackshear - when is the next model release coming for frigate+. Will it be this year or next?

[NickM-27]

It is currently being worked on, from what I have seen said on Discord it should be within the next month

https://github.com/orgs/frigate-nvr/projects/2/views/1

[nmcrae85]

Cool thanks. Not looked on discord so wasnt aware.

…

On Mon, 15 Apr 2024 at 19:10, Nicolas Mowen ***@***.***> wrote: It is currently being worked on, from what I have seen said on Discord it should be within the next month https://github.com/orgs/frigate-nvr/projects/2/views/1 — Reply to this email directly, view it on GitHub <#7932 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AHUULJEMARNL2525NDBKVPDY5QJXVAVCNFSM6AAAAAA5E37EMCVHI2DSMVQWIX3LMV43SRDJONRXK43TNFXW4Q3PNVWWK3TUHM4TCMRRGY4DA> . You are receiving this because you commented.Message ID: ***@***.*** com>

[miziu]

Hello, is there any way to export roboflow(over 3k images with annotations in .xml)folder or zip to frigate+?. It might be hard to label everything again in frigate plus

[blakeblackshear]

You could write a script against the API using your API key.

[derekcentrico]

Curiously, is email the preferred sign-up method still for the paid version? Just checking as I emailed a few days ago. Not sure if it's an automated process or anything, but radio silence so thought I'd inquire. Loving Frigate (first few days of it have been amazing).

[blakeblackshear]

I was just behind on sending out invites. You should have one now.

[derekcentrico]

Thanks man. Sorry wasn't trying to be pushy just didn't know if processes changed. This stuff is awesome for a novice wanna-be like myself.