The inside box is poorly located because they can't overlap in this model. In this case it would be better to just have one detection box, and say 'pet is at door'
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Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
41–50 of 84 posts
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#42The inside box is poorly located because they can't overlap in this model. In this case it would be better to just have one detection box, and say 'pet is at door'
You're right. In this model it does not matter as in both cases the door gets opened. It would only make sense to make a difference if after a given time you may only want entries and not exits (like after some predetermined time).
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#43What if you're not home? It is for such occasions that cat flaps were invented. However, today's cat flaps either open for any cat, or they're RFID-based, and for that to work, you implant a chip into your cat, which I find utterly barbaric. Now what could be a great improvement is a cat flap identifying your cat(s) and letting them in based on computer vision, instead of relying on implants. I'd pay good money for i…
Sorry if this sounds idiot, but can't you put the RFID chip into the leash or something like that? Why it needs to be "inside" the animal?
Yes. The this is the alternate way of doing it with the RFID flaps if for some reason your pet doesn't have a chip or there are issues reading it. Cats can lose collars though, many have a release mechanism so that if the collar gets caught the cat doesn't get stuck forever too.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#44Url changed from https://hackaday.com/2018/12/21/neural-network-knows-when-ca... to the source it links to. This is a good example of how titles dominate threads. Because of the title "Neural network knows when cat wants to go outside", we got cat quips. "Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio" primes a different sort of discussion.
Cat quips are a sign of a healthy community atmosphere.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#45As human intervention is required anyway to open the door, why have inside box and outside box? There can be just one big box with pet detection and an SMS that says 'Pet at door'.
Nevertheless, this is a cool project, and the explanation in the YouTube video is even nicer, informative, and succinct.
One addition could be to have a motion sensor outside the door to turn on the light outside, so that this project can work even during late evenings/nights.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#46Url changed from https://hackaday.com/2018/12/21/neural-network-knows-when-ca... to the source it links to. This is a good example of how titles dominate threads. Because of the title "Neural network knows when cat wants to go outside", we got cat quips. "Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio" primes a different sort of discussion.
sorry guys, that was not the intention. I just send the link for the hackaday news. next time I will try a better approach.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#47Does it also know when the cat is just going to stand in the window frame for 2 minutes until it goes back inside?
I bet the cat soon learns that sitting in front of the door magically summons a human to let it out.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#48Url changed from https://hackaday.com/2018/12/21/neural-network-knows-when-ca... to the source it links to. This is a good example of how titles dominate threads. Because of the title "Neural network knows when cat wants to go outside", we got cat quips. "Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio" primes a different sort of discussion.
sorry guys, that was not the intention. I just send the link for the hackaday news. next time I will try a better approach.
Don't worry about it! As minimaxir pointed out, the story probably wouldn't have gotten much attention otherwise, and readers are clearly interested.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#49Url changed from https://hackaday.com/2018/12/21/neural-network-knows-when-ca... to the source it links to. This is a good example of how titles dominate threads. Because of the title "Neural network knows when cat wants to go outside", we got cat quips. "Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio" primes a different sort of discussion.
Cat quips are a sign of a healthy community atmosphere.
Up to a point, yes. But alas that point is unstable.
Re: Raspberry Pi Pet Detector Camera Using Python, TensorFlow, and Twilio [video]
#50Very cool. The Raspberry Pi is turning out to be a nice platform for little AI driven projects like this.
It's not using machine learning, but I'm just now finishing up a Christmas present; a web accessible treat dispense with live video. I know those exist commercially, but it has been a fun project to build one anyway.
Terrible quality pictures:
Raspberry Pi Zero W for the brains; Pimoroni speaker hat; cheap stepper motor and bridge; IR emitter and transistor create an IR break beam to detect when treats are dispensed; Raspberry Pi camera for live video feed; all controlled by a custom AppEngine deployment which provides a nice web interface for dispensing treats, viewing the video, and even uploading their own sounds which get played before the treats come out.
The most difficult thing has been the mechanical engineering; something I have little to no experience with. The whole CAD process took me a few weeks of working on and off. Then another two weeks of printing and iterating the parts. The main body itself is a 14 hour print even at high speed. I ended up using FreeCAD for the whole design. Not sure if that was a mistake or not. I like supporting open source software, but ... I have this terrible notion that something like Fusion360 would have made the whole process 10x faster... But it's all printed and working!
Since this is going as a gift to someone else, I also had to take a lot of time to make it easy to use; it couldn't just be a fiddly hack. So, for example, I got a nice setup procedure built into it for setting up wifi. You just hold the button on the back to put it into setup mode, and then show it a QR code on your phone with your Wifi network's details. And since there's a speaker, I'm using some text-to-speech to walk them through the setup. It turned out nice.
And using the magic of ffmpeg, I was able to get the Raspberry's camera feed into an HLS stream, which gets securely uploaded to the AppEngine server. So it's a live video, rather than still pictures or delayed video uploads. Was really happy when that got working. (I use hls.js to handle desktop browser compatibility. Works a treat. Also, FFMpeg is supposed to be able to upload the HLS stream itself to a server, but that was broken or something; had to use some Python to pipe it manually.)
Just putting the finishing touches on the frontend now. 4 days to go... wish me luck!