Merge branch 'master' of gitlab.cl.uni-heidelberg.de:jmrs/caption

[Trained model (default)](/models/multilabel_default/)  

[Trained model (+Hyperparameters)](/models/multilabel_hp/)

#### Extraction

* Restriction:  

  Because extracting all vectors from images took too long we limited the dataset to 100 pictures per category, resulting in 8000 vectors total (which are used as input for the LSTM). We expect that this decision will get us inferior end results, but had to be done to stay within time limits.

* to create an equal distribution without intersecting pictures we used the following [script](cnn/preprocessing/100.py):

    ```

    python 100.py

    ```

* The final distribution can be seen in the following chart:

  ![distribution of categories](/Diagrams/sb_category_frequencies.png)

#### Visualization (Lucid)

* We used [https://github.com/tensorflow/lucid](https://github.com/tensorflow/lucid) (for creating own model have a look at this [colab-notebook](https://colab.research.google.com/drive/1PPzeZi5sBN2YRlBmKsdvZPbfYtZI-pHl#scrollTo=06q00d8zvwqc))