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https://github.com/minimaxir/person-blocker

Automatically "block" people in images (like Black Mirror) using a pretrained neural network.
https://github.com/minimaxir/person-blocker

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Automatically "block" people in images (like Black Mirror) using a pretrained neural network.

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README 

        
# Person Blocker



![img4](example_output/img4_blocked.gif)



A script to automatically "block" people in images (like the [Black Mirror](https://en.wikipedia.org/wiki/Black_Mirror) episode [White Christmas](https://en.wikipedia.org/wiki/White_Christmas_(Black_Mirror))) using [Mask R-CNN](https://github.com/matterport/Mask_RCNN) pretrained on the [MS COCO](https://arxiv.org/abs/1405.0312) dataset. No GPU required!



But you can block more than just people: up to [80 different types](https://github.com/minimaxir/person-blocker/blob/master/classes.py) of objects can be blocked, including giraffes and busses!



## Setup



This project relies on a handful of dependencies, use the following command to install your dependencies:



```shell

pip3 install -r requirements.txt

```



_Note_: Depending on your environment, you may need to use `sudo`. You may also want to use virtualenv.



## Usage



Person Blocker is used from the command line:



```shell

python3 person_blocker.py -i images/img3.jpg -c '(128, 128, 128)' -o 'bus' 'truck'

```



* `-i/--image`: specifies the image file.

* `-m/--model`: path to the pretrained COCO model weights (default: current directory): if not specified, it will download them automatically to the current directory if not already present (note: the weights are 258 MB!)

* `-c/--color`: color of the mask, in either quote-wrapped hexidecimal or 3-element RGB tuple format. (default: white)

* `-o/--object`: list of types of objects to block (or object IDs of specific objects). You can see the allowable choices of objects to block in `classes.py` or by using the `-names` flag. (default: person)

* `-l/--labeled`: saves a labeled image annotated with detected objects and their object ID.

* `-n/--names`: prints the class options for objects, then exits.



The script outputs two images: a static (pun intended) image `person_blocked.png` and an animated image `person_blocked.gif` like the one at the beginning of this README.



## Examples



```shell

python3 person_blocker.py -i images/img1.jpg

```



![img1](example_output/img1_blocked.png)



```shell

python3 person_blocker.py -i images/img2.jpg -c '#c0392b' -o 'giraffe'

```



![img2](example_output/img2_blocked.png)



```shell

python3 person_blocker.py -i images/img3.jpg -c '(128, 128, 128)' -o 'bus' 'truck'

```



![img3](example_output/img3_blocked.png)



Blocking specific object(s) requires 2 steps: running in inference mode to get the object IDs for each object, and then blocking those object IDs.



```shell

python3 person_blocker.py -i images/img4.jpg -l

```



![img4 labels](example_output/img4_labels.png)



```shell

python3 person_blocker.py -i images/img4.jpg -o 1

```



![img4](example_output/img4_blocked.png)



## Requirements



The same requirements as Mask R-CNN:

* Python 3.4+

* TensorFlow 1.3+

* Keras 2.0.8+

* Numpy, skimage, scipy, Pillow, cython, h5py



plus matplotlib and imageio



## Maintainer



Max Woolf ([@minimaxir](http://minimaxir.com))



*Max's open-source projects are supported by his [Patreon](https://www.patreon.com/minimaxir). If you found this project helpful, any monetary contributions to the Patreon are appreciated and will be put to good creative use.*



## License



MIT



Code used from Mask R-CNN by Matterport, Inc. (MIT-Licensed), with minor alterations and copyright notices retained.