# Node-RED TensorFlow Object Detection with Telegram on macOS
**URL:** https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699
**Category:** Share Your Projects
**Created:** [6 March 2020 10:30 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699 "2020-03-06T10:30:01Z")
**Posts on this page:** 20
**Page:** 1
### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [6 March 2020 10:30 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/1 "2020-03-06T10:30:01Z")
The GitHub README file cautions that their [TF Node-RED Object Detection demo](https://github.com/IBM/node-red-tensorflowjs) only works with the Raspberry PI; but I got it working just fine on macOS today.
This is a fun little project, for sure; which I retooled for Telegram and changed the detection logic:
The details are here, including the flow:
> **[Telegram Object Detection Bot using Node-RED and TensorFlow Object Detection...](https://www.unix.com/programming/283897-telegram-object-detection-bot-using-node-red-tensorflow-object-detection-macos.html)**
>
> Fun project! The GitHub project page for Node-RED node with a TensorFlow.js Object Detection model cautions that there demo code only works with the Raspberry PI. However, today I got it working (quite easily) with macOS. | The UNIX and Linux Forums
Enjoy!
We have some seagulls which sometimes fly into my condo because the window are open most of the time! They go a bit crazy when they fly into the condo and cannot fly out so easily! Maybe we can detect them before they poop on my mac! LOL
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### Author:  [@TotallyInformation](https://discourse.nodered.org/u/TotallyInformation)
#### Post date: [6 March 2020 11:48 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/2 "2020-03-06T11:48:15Z")
What would be really impressive would be a Node-RED controlled drone that chased the seagull's out again! ๐คฃ
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [6 March 2020 12:16 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/3 "2020-03-06T12:16:36Z")
haha.....
I think I need some sexy seagulls to pop on on the window ledge to lure them out! Maybe some sweet seagull love songs too!
The darn things are easy excited so if I sent an army of NR controlled drones their way, they will surely poop all over the place, in wild panic! hahahaha
They are pretty smart too. Normally, if we are in the condo or asleep in the bedroom, they will not fly in.
Crazy Birds!
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### Author:  [@TotallyInformation](https://discourse.nodered.org/u/TotallyInformation)
#### Post date: [6 March 2020 12:18 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/4 "2020-03-06T12:18:58Z")
They are indeed crazy. Maybe a chip firing thing then, they will surely follow the chips out the window. Of course, they'd also be attracted to the chips in the first place - ho hum.
You could try hanging up a silhouette of a bird of prey outside the Window, that might work?
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [6 March 2020 12:37 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/5 "2020-03-06T12:37:06Z")
> [@TotallyInformation](#):
>
> You could try hanging up a silhouette of a bird of prey outside the Window, that might work?
haha..... tried that a few years ago..... they just fall in love with scarecrows, decoys, model birds.... we even have a windmill... that worked for a few days until they started to fall in love with the windmill too!
LOL. Life is tough!
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [7 March 2020 04:23 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/6 "2020-03-07T04:23:35Z")
Installed Node-RED with TensorFlow.js on an older MacBook Air and now testing this "detect the seagulls" TensorFlow app using the built-in MBA web cam (the Logitech wide-angle HD camera on my MacPro trash can is too short to reach the window... LOL).
Come on birds!!! ๐
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### Author:  [@BartButenaers](https://discourse.nodered.org/u/BartButenaers)
#### Post date: [7 March 2020 08:18 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/7 "2020-03-07T08:18:19Z")
Hi @unixneo,
That tutorial uses the node-red-contrib-tfjs-object-detection package. Seems not to be available in npm for some reason. Do you know why (beta phase or ...)?
P.S. lovely view from your window ...
Bart
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [7 March 2020 09:17 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/8 "2020-03-07T09:17:42Z")
> [@BartButenaers](#):
>
> That tutorial uses the node-red-contrib-tfjs-object-detection package. Seems not to be available in npm for some reason. Do you know why (beta phase or ...)?
> P.S. lovely view from your window ...
> Bart
Hi Bart,
I installed `node-red-contrib-tfjs-object-detection` following directions from Git:
> **[GitHub - IBM/node-red-tensorflowjs: Node-RED node with a TensorFlow.js Object...](https://github.com/IBM/node-red-tensorflowjs)**
>
> Node-RED node with a TensorFlow.js Object Detection model - GitHub - IBM/node-red-tensorflowjs: Node-RED node with a TensorFlow.js Object Detection model
There is also `node-red-contrib-tfjs-object-detection` available in the `Node-RED` install palette, but I have had mixed results installing directly inside `Node-RED` and, personally, got the best results just following the Git directions (the manual step by step way), above. (`clone`, then do the `npm install` **thang.**... per the directions in the repo)
Still cyber-tensorflow-stalking seagulls ...... no "hits" yet. LOL
Post back if you have any issues, I have got this "cool TF stuff" running on two macs, one 12-Core MacPro (2013) and one older MacBook Air (both running Catalina).
PS: No idea why it is not directly available in `npm` as I did not go that route and just followed the Git repo install directions.... sorry. My best (bad, stab-in-the-dark guess) is that because the developer of `node-red-contrib-tfjs-object-detection` states it only works for the PI (based, in part I think because of the `usbcamera` and other requirements which the developer believes are currently "PI only", but as I mentioned, this is only a wild guess). As mentioned, I had to do a little "out-of-the-box" thinking and debugging to get it running on macOS, but it does work after "adjustments".
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### Author:  [@BartButenaers](https://discourse.nodered.org/u/BartButenaers)
#### Post date: [7 March 2020 12:59 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/9 "2020-03-07T12:59:05Z")
Thanks! But my brain is a bit too small for this Tensorflow stuff ...
There are a number of tensorflow.js nodes for Node-RED available to offer object detection in images (via the [coco-ssd model](https://github.com/tensorflow/tfjs-models/tree/master/coco-ssd)), but they all differ:
- The [node-red-contrib-tfjs-object-detection](https://github.com/IBM/node-red-tensorflowjs/tree/master/node-red-contrib-tfjs-object-detection) node (from IBM) is not on npm (yet?) but one of the advantages is that it installs both tensorflow and the coco-ssd model _ **automatically** _. See their [package.json](https://github.com/IBM/node-red-tensorflowjs/blob/master/node-red-contrib-tfjs-object-detection/package.json#L5) file:
- The [node-red-contrib-tf-model](https://github.com/yhwang/node-red-contrib-tf-model/blob/master/README.md#prerequisite) on the other hand explicit advises _ **not** _ to install tensorflow.js as a dependency automatically:
- The [node-red-contrib-tensorflowjs](https://github.com/dceejay/tfjs-nodes/blob/master/README.md#node-red-contrib-tensorflowjs) from @dceejay says this:
Any thoughts to have this noob started in the right direction?
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [7 March 2020 13:13 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/10 "2020-03-07T13:13:18Z")
For me, so far, I have had the best success with the IBM demo `node-red-contrib-tfjs-object-detection` as mentioned in my little macOS summary writeup in the unix / linux forums.
I have not used the other repos and nodes you mentioned.
In addition, I have tried `node-red-contrib-machine-learning` because I want to refine and train object detection models; but `node-red-contrib-machine-learning` is a bear due to poor documentation.
I found `node-red-contrib-tfjs-object-detection` a piece of cake on macOS; and freely confess I have not tried it on any other platform, including the PI. It's working flawlessly at the moment, except the model needs to work better (better training).
Hence, from my perspective, I can only comment on `node-red-contrib-tfjs-object-detection` and I installed it from the IBM GitHub repo directions (manually with `npm`) and made a few tweakies for macOS and it's been running great (now on two macs).
I assume you are on the PI.
Have you tried just cleaning thing up and starting from scratch following only the `node-red-contrib-tfjs-object-detection` install directions on their repo?
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### Author:  [@BartButenaers](https://discourse.nodered.org/u/BartButenaers)
#### Post date: [7 March 2020 13:30 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/11 "2020-03-07T13:30:22Z")
> [@unixneo](#):
>
> Have you tried just cleaning thing up and starting from scratch following only the `node-red-contrib-tfjs-object-detection` install directions on their repo?
No, but since you had the least problems with that, that probably will become my starting point.
> [@unixneo](#):
>
> except the model needs to work better (better training).
Can you please explain that a little bit more?
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [7 March 2020 14:52 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/12 "2020-03-07T14:52:20Z")
> [@BartButenaers](#):
>
> Can you please explain that a little bit more?
Sure. Here are some high level concepts.
In this case, we are talking about processing images to detect objects. There are many other detection models; but this particular `node-red-contrib-tfjs-object-detection` gizmo is about object detection.
TensorFlow has created and provides some basic models in their TensorFlow offerings that detect a number of objects classes. When a computer algorithm "detects" an object, it will assign a probability or confidence estimate, for example:
`"person" 0.92323232`
However, the Google TF model in this case, based on my testing so far, only detects `person` and it can, fairly accurately, detect the number of objects in its field of view, in this example `person` objects. But the current model does not attempt to detect `who` that person is. That requires a different model and / or training the current model (with `ML` learning techniques), since we might only want to detect our `family members` to distinguish them from `strangers`, if we were interested, for example, in getting an alarm or message when a `stranger` enters into some space (instead of the coarse object `person`).
I advise you not to worry too much about that yet.
First, you need to get `up and running` and detecting the objects in the `models out-of-the-box` and when you are comfortable with that, then you can decide if you need different models and how `deep` you want to detect (how deep you want your models to `learn`). Of course it is more coarse
to detect a `person` versus detecting `male person` or `female person` etc. So, we have to crawl before we walk and walk before we run.
In my case, I am trying to detect `bird` and that is an object which files and poops on my balcony. At this point, we are not trying to detect if it is a `seagull` or a `pigeon`; just a `bird` which is a less refined object than `seagull` obviously.
In this app we are discussing, `node-red-contrib-tfjs-object-detection`, the focus is on coarse object detection based on the provide model. Or course, the more refined and less coarse an object model is the bigger and slower the detection process.
So, instead of digressing into discussions about `false positives` and `false negatives` and so forth and so on about `detection theory`, it might help you a bit if you review a paper I wrote this topic a number of years ago, regarding computer and network security. It's fairly high level and easy to read:
[https://www.researchgate.net/publication/220420389\_Intrusion\_Detection\_Systems\_and\_Multisensor\_Data\_Fusion](https://www.researchgate.net/publication/220420389_Intrusion_Detection_Systems_and_Multisensor_Data_Fusion)
Back to `node-red-contrib-tfjs-object-detection` ....
I think this is a very well designed basic still image detection module for `Node-RED` and I like it so far.
Frankly, I am not a huge fan of `surveillance capitalism` and commercial applications of `surveillance` like the `huge tech` companies are doing (don't get me started on that `rabbit-hole topic`); but I am interested in `home applications` like stopping birds from pooping on my balcony or detecting `strangers` in the vicinity of my home.
In addition, I don't use any tech from companies which have `surveillance capital` business models; for example `Blynk`, `Alexa / Amazon`, `FB APIs` and the myriad of other tech companies which surveil all online activity and create human behavioral models (for sale to the highest ad bidder) as they offer us `"free"` services.
Node-RED is a great platform to build our own `instrumentation` and this is good, so people do not depend on `third-party` services which are `"free"` in theory but the cost is little privacy. The way to resist this `surveillance capital` business model is to build our own and manage our own data.
That is why I will never use `Alexa` for home automation. I don't use `Blynk` either, after reading their TOS (terms of service) where they have the right to share all your data, even your own messaging data, with third-parties.
This is also why I have become a huge `Node-RED` fan because we, all of us, can build our own `instrumentation` sans the `surveillance capitalism` business models of big tech.
Sorry to digress..... LOL
When you get old and long in the tooth, we start to digress often ... because of all those years of tech experience embedded in our brains... haha ๐
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### Author:  [@dceejay](https://discourse.nodered.org/u/dceejay)
#### Post date: [7 March 2020 15:06 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/13 "2020-03-07T15:06:53Z")
Just to lob one in here - I also have a node that is basically the same but includes the model in the node - so it should work "offline" - [https://flows.nodered.org/node/node-red-contrib-tfjs-coco-ssd](https://flows.nodered.org/node/node-red-contrib-tfjs-coco-ssd)
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### Author:  [@BartButenaers](https://discourse.nodered.org/u/BartButenaers)
#### Post date: [7 March 2020 16:02 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/14 "2020-03-07T16:02:07Z")
> [@unixneo](#):
>
> Here are some high level concepts
I appreciate this great introduction!!
> [@dceejay](#):
>
> a node that is basically the same but includes the model in the node -
Dave, is there any particular reason why you haven't added a Tensorflow dependency to your node?
And about person detection: you support two models (posenet and coco-ssd). Which one would be best for this purpose?
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### Author:  [@dceejay](https://discourse.nodered.org/u/dceejay)
#### Post date: [7 March 2020 16:34 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/15 "2020-03-07T16:34:09Z")
Eh ? The coco-sad node only does objects including people. No posenet. And absolutely does have a tensorflowjs dependency in package.json. Ah the npm point to the wrong master project... will fix.
should be this one - [https://github.com/dceejay/tfjs-coco-ssd](https://github.com/dceejay/tfjs-coco-ssd)
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### Author:  [@BartButenaers](https://discourse.nodered.org/u/BartButenaers)
#### Post date: [7 March 2020 16:40 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/16 "2020-03-07T16:40:52Z")
> [@dceejay](#):
>
> Ah the npm point to the wrong master project
Ah that is why I was confused. Ok I now see indeed your tfjs-node dependency. Thanks! I'm back on track...
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### Author:  [@dceejay](https://discourse.nodered.org/u/dceejay)
#### Post date: [7 March 2020 16:41 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/17 "2020-03-07T16:41:18Z")
(and so am I ๐ - thanks for spotting it !)
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [8 March 2020 07:00 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/18 "2020-03-08T07:00:15Z")
Update:
So far, no luck `detecting birds` in my setup; except `COCO-SSD` seems to `"think"` a bonsai tree moving in the breeze is `"person"` .....and the bright sunlight and / or reflections are `"oven"`..... LOL
Not really encouraged this setup is going to `detect pooping birds` , but let's keep testing.
In the meantime we are going to take a drive in the car today with `Node-RED` running this `TF object detection model` on a `MacBook Air`, and see what kinds of `Telegram detection messages` that brings us.
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [12 March 2020 05:15 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/19 "2020-03-12T05:15:42Z")
Yeaaaa! A First ! Haha!
After running for 4 days (LOL) and detecting the sun as "oven" and moving leaves on a bonsai tree as "airplane" and "keyboard", a small bird flew in and perched itself right on the balcony rail, and my `MuppetBot` detected "bird".... LOL
Little `MuppetBot` is certainly far from perfect {{ I need to install a more robust (large, slower) TF object detection model}}, but have been busy on another project).
Here ya go ๐ - See the most recent entry at the bottom....
It's actually a bit exciting to detect a bird (for the first time) on the balcony with a Node-RED object detection flow.
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### Author:  [@unixneo](https://discourse.nodered.org/u/unixneo)
#### Post date: [13 March 2020 03:02 UTC](https://discourse.nodered.org/t/node-red-tensorflow-object-detection-with-telegram-on-macos/22699/20 "2020-03-13T03:02:28Z")
This is working well, but I need to take a few steps back when I have time (busy with other projects at the moment) and find a different object detection model; or I need to find out if there are more refined COCO models and how to install them without breaking my current setup.
The COCO model in this demo works very well detecting people, but is not very accurate with smaller objects like birds. Detecting people, however, is really fast and impressive.
Doing some quick research into this, the answer was not obvious how to proceed; but I did find an interesting paper by the developers of the COCO model:
# Microsoft COCO: Common Objects in Context
[Tsung-Yi Lin](https://arxiv.org/search/cs?searchtype=author&query=Lin%2C+T), [Michael Maire](https://arxiv.org/search/cs?searchtype=author&query=Maire%2C+M), [Serge Belongie](https://arxiv.org/search/cs?searchtype=author&query=Belongie%2C+S), [Lubomir Bourdev](https://arxiv.org/search/cs?searchtype=author&query=Bourdev%2C+L), [Ross Girshick](https://arxiv.org/search/cs?searchtype=author&query=Girshick%2C+R), [James Hays](https://arxiv.org/search/cs?searchtype=author&query=Hays%2C+J), [Pietro Perona](https://arxiv.org/search/cs?searchtype=author&query=Perona%2C+P), [Deva Ramanan](https://arxiv.org/search/cs?searchtype=author&query=Ramanan%2C+D), [C. Lawrence Zitnick](https://arxiv.org/search/cs?searchtype=author&query=Zitnick%2C+C+L), [Piotr Dollรกr](https://arxiv.org/search/cs?searchtype=author&query=Doll%C3%A1r%2C+P)
(Submitted on 1 May 2014 ([v1](https://arxiv.org/abs/1405.0312v1)), last revised 21 Feb 2015 (this version, v3))
> We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. This is achieved by gathering images of complex everyday scenes containing common objects in their natural context. Objects are labeled using per-instance segmentations to aid in precise object localization. Our dataset contains photos of 91 objects types that would be easily recognizable by a 4 year old. With a total of 2.5 million labeled instances in 328k images, the creation of our dataset drew upon extensive crowd worker involvement via novel user interfaces for category detection, instance spotting and instance segmentation. We present a detailed statistical analysis of the dataset in comparison to PASCAL, ImageNet, and SUN. Finally, we provide baseline performance analysis for bounding box and segmentation detection results using a Deformable Parts Model.
Also, directly available [here in PDF.](https://arxiv.org/pdf/1405.0312)
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