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deep pomf 2018-02-09 22:19:30 -05:00
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@ -22,25 +22,30 @@ The decensorship process is fairly involved. A user interface will eventually be
Using image editing software like Photoshop or GIMP, crop 128 x 128 size images containing the censored regions from your images and save them as new ".png" images. For each 128 x 128 cropped image, color the censored regions [tbd]. Using image editing software like Photoshop or GIMP, crop 128 x 128 size images containing the censored regions from your images and save them as new ".png" images. For each 128 x 128 cropped image, color the censored regions [tbd].
Move the cropped images to []. Run the command Move the cropped images to []. Decensor the images by running
``` ```
$ python decensor.py $ python decensor.py
``` ```
Decensored images will be saved to the "output" directory. Decensored images will be saved to the "output" directory. Paste the decensored images back into the original image.
Paste the decensored images back into the original image. ## II. Train the pretrained model
## II. Prepare the training data Put the your custom dataset for training the "data/images" directory and convert images to npy format.
Put the images for training the "data/images" directory and convert images to npy format.
``` ```
$ cd data $ cd data
$ python to_npy.py $ python to_npy.py
``` ```
Train pretrained model on your custom dataset.
```
$ cd src
$ python train.py
```
The dataset will not be released. I do not want to risk trouble for distributing copyrighted pornographic material. The dataset will not be released. I do not want to risk trouble for distributing copyrighted pornographic material.
# To do # To do