https://github.com/jcrodriguez1989/weeddream
A cannabis-trained DeepDream.
https://github.com/jcrodriguez1989/weeddream
cannabis cannabis-data deep-learning deepdream deeplearning imagenet imagenet-classifier weedmaps
Last synced: 3 months ago
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A cannabis-trained DeepDream.
- Host: GitHub
- URL: https://github.com/jcrodriguez1989/weeddream
- Owner: jcrodriguez1989
- Created: 2021-01-12T14:29:01.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-03-30T16:10:02.000Z (about 4 years ago)
- Last Synced: 2025-01-03T21:16:02.099Z (5 months ago)
- Topics: cannabis, cannabis-data, deep-learning, deepdream, deeplearning, imagenet, imagenet-classifier, weedmaps
- Language: Python
- Homepage:
- Size: 29.6 MB
- Stars: 4
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
README
---
output: github_document
---
# WeedDream - A cannabis-trained [DeepDream](https://en.wikipedia.org/wiki/DeepDream) approach
Code to reproduce the findings presented at the [_"Can Artificial Intelligence Dream of Cannabis?"_ blog post](https://medium.com/cannabis-explorations/can-artificial-intelligence-dream-of-cannabis-3ed9b34948bf).
## Usage
### Adding Images for Training
The images used to train Weedception_v1 are not my property, and therefore I cannot share them. To retrain the model you must provide your own images. To do this, in the `TrainingImages/` folder there should be a sub-folder for each category to be used, and within each sub-folder its corresponding images. As an example, in each `TrainingImages/` sub-folder, there is included one example image.
### Training the Weedception_v1 Model
To retrain inception, file `01_retrain_inception.py` should be executed, for this, run the following from a bash console:
```{bash, eval=FALSE}
weeddream$ mkdir Models # Create the folder to save the trained model.
weeddream$ python Script/01_retrain_inception.py
```
### Analyze Individual Layer Effects
To create dreams using only one layer and one weight run the following:
```{bash, eval=FALSE}
# Let's say we want to train layer 10 with weight 3, we should type:
weeddream$ python Script/02_analyze_individual_layers.py 10 3
# If we want to train each individual layer for each weight from 1 to 10, we should type:
weeddream$ for layer in {1..10}; do
> for weight in {1..10}; do
> python Script/02_analyze_individual_layers.py $layer $weight
> done
> done
```
### Using WeedDream to Dream With the Selected Setting
To use WeedDream to dream on a image, with the selected settings (layers 2 with weight `2`, 6 with `5`, and 9 with `4`), run the following:
```{bash, eval=FALSE}
weeddream$ python Script/03_weeddream.py
```