https://github.com/palmerabollo/nomorecats
Chrome extension that hides all those annoying kitties
https://github.com/palmerabollo/nomorecats
chrome-extension proof-of-concept tensorflow tensorflow-js
Last synced: 9 months ago
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Chrome extension that hides all those annoying kitties
- Host: GitHub
- URL: https://github.com/palmerabollo/nomorecats
- Owner: palmerabollo
- License: other
- Created: 2018-11-02T22:45:03.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-11-18T18:14:26.000Z (over 7 years ago)
- Last Synced: 2025-04-13T05:12:42.815Z (about 1 year ago)
- Topics: chrome-extension, proof-of-concept, tensorflow, tensorflow-js
- Language: JavaScript
- Size: 7.95 MB
- Stars: 8
- Watchers: 2
- Forks: 4
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
# No more cats
Chrome extension that blocks all those annoying cats online.
## Install
Clone the project:
```sh
git clone git@github.com:palmerabollo/nomorecats.git
cd nomorecats
```
In Google Chrome:
- Open **`chrome://extensions`**
- Enable the `"Developer Mode"` toggle.
- Click `"Load unpacked"` and open the "nomorecats" project you cloned before.
Once the plugin is loaded you'll see a new card. There is an **"Inspect views `background.html`"** link that lets you debug the `background.js` script containing all the tensorflow magic.
Every time you open a page with images, they will be processed and you'll see a log like the following one:
```
Readable prediction for https://images.pexels.com/photos/416160/pexels-photo-416160.jpeg?auto=compress&cs=tinysrgb&h=350
Float32Array(2) [0.43529072403907776, 0.5647093057632446]
````
The Float32Array contains two elements. The first one (`p`) is the probability to be a cat. The second one is `1-p`.
## Train a new model
The extension uses a MobileNet model trained with tensorflow and converted to tensorflowjs to be used in the extension.
### Install prerequisites
- jq
- tensorflow: `pip install --upgrade "tensorflow==1.7.*"`
- tensorflowjs: `pip install tensorflowjs`
### Train a new model:
```sh
git clone https://github.com/googlecodelabs/tensorflow-for-poets-2
cd tensorflow-for-poets
export IMAGE_SIZE=224
export ARCHITECTURE="mobilenet_0.50_$IMAGE_SIZE"
#
# copy the "dataset" folder in the repo to tf_files
#
# Train the model
python -m scripts.retrain \
--bottleneck_dir=tf_files/bottlenecks \
--how_many_training_steps=500 \
--model_dir=tf_files/models/ \
--summaries_dir=tf_files/training_summaries/"$ARCHITECTURE" \
--output_graph=tf_files/retrained_graph.pb \
--output_labels=tf_files/retrained_labels.txt \
--architecture="$ARCHITECTURE" \
--image_dir=tf_files/dataset
# Convert to tensorflowjs
tensorflowjs_converter \
--input_format=tf_frozen_model \
--output_node_names=final_result \
tf_files/retrained_graph.pb \
tf_files/web
#
# Quantize & optimize not mandatory.
# Skip them for now for simplicity.
#
# Generate labels.json from retrained_labels.txt
cat tf_files/retrained_labels.txt | jq -Rsc '. / "\n" - [""]' > tf_files/web/labels.json
```
Now copy everything under tf_files/web to the extension's `"tensorflow"` folder and reload the extension in Google Chrome.
## References
- https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/
- https://index.pocketcluster.io/woudsma-retrain-mobilenet-for-the-web.html
- https://proandroiddev.com/re-training-the-model-with-images-using-tensorflow-7758e9eb8db5
- https://js.tensorflow.org/tutorials/import-saved-model.html
## License
Apache 2.0