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Home Page: https://teachablemachine.withgoogle.com/
License: Apache License 2.0
Using Teachable Machine Models in Node.js
Home Page: https://teachablemachine.withgoogle.com/
License: Apache License 2.0
this is my errors
root@detection-ubuntu-s-8vcpu-16gb-nyc1-01:~/Cattle-detection# pip install -r requirements.txt
Requirement already satisfied: torch in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 1)) (1.5.1+cpu)
ERROR: Could not find a version that satisfies the requirement opecv-python (from -r requirements.txt (line 2)) (from versions: none)
ERROR: No matching distribution found for opecv-python (from -r requirements.txt (line 2))
Using npm pureimage you can remove completely jsdom
, canvas
and even @teachablemachine/image
npm packages dependencies!
Check my Node-RED node node-red-contrib-teachable-machine release v1.2.0
to see what things I've changed.
That was thanks to the advice of @dceejay in this issue.
Hope this can be helpful. ๐
Hi !!, I just following your sample code and using your sample model.
but, when i change the image url. the output always same as before.
Thanks.
the outputs:
Predictions: [
{ className: 'Dog', probability: 0.5297428965568542 },
{ className: 'Not_Dog', probability: 0.47025713324546814 }
]
current imageUrl : https://media-blog.sashido.io/content/images/2020/09/SashiDo_Dog.jpg
Predictions: [
{ className: 'Dog', probability: 0.5297428965568542 },
{ className: 'Not_Dog', probability: 0.47025713324546814 }
]
current imageUrl : https://icatcare.org/app/uploads/2018/07/Thinking-of-getting-a-cat.png
hey @pivanov @IraGR, the code is missing types which makes it difficult to interpret how the code will work and what is it providing to the user, so I think making types for the project can be great help for the developers using this package.
If you guys agree than I will write the types and create a pull request.
I am using ExpressJS example, but I couldn't able to send local file url. If I use same url like imageUrl: "https://media-blog.sashido.io/content/images/2020/09/SashiDo_Dog.jpg", then I can see result. But I want to make it dynamic, so I can browse my own computer and use local images.
is there any way to pass my custom model and metadata instead of passing URL link ??? I tried with the relative path to model but that return error - only absolute URL . I think there should be some way.
git clone https://github.com/SashiDo/teachablemachine-node.git
Cloning into 'teachablemachine-node'...
remote: Enumerating objects: 56, done.
remote: Counting objects: 100% (17/17), done.
remote: Compressing objects: 100% (13/13), done.
remote: Total 56 (delta 6), reused 10 (delta 4), pack-reused 39
Unpacking objects: 100% (56/56), 51.14 KiB | 3.01 MiB/s, done.
cd teachablemachine-node
root@machineteacheble-ubuntu-s-8vcpu-16gb-nyc1-01:~/teachablemachine-node# yarn
yarn install v1.22.5
warning ../package.json: No license field
info No lockfile found.
warning package-lock.json found. Your project contains lock files generated by tools other than Yarn. It is advised not to mix package managers in order to avoid resolution inconsistencies caused by unsynchronized lock files. To clear this warning, remove package-lock.json.
[1/5] Validating package.json...
[2/5] Resolving packages...
[3/5] Fetching packages...
[4/5] Linking dependencies...
warning "@tensorflow/tfjs > @tensorflow/[email protected]" has unmet peer dependency "seedrandom@~2.4.3".
[5/5] Building fresh packages...
success Saved lockfile.
Done in 6.30s.
yarn build
yarn run v1.22.5
warning ../package.json: No license field
error Command "build" not found.
info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command.
yarn run watch
yarn run v1.22.5
warning ../package.json: No license field
error Command "watch" not found.
info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command.
pls help me with this
tnks
When iterating over array of images and classifying each one i get prediction scores like:
[
{ class: 'apple', score: 1 },
{ class: 'banana', score: 5.249882195634825e-10 }
]
is this a know issue?
can provide full code if needed
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