Commit 4f16b84e authored by holzinger's avatar holzinger
Browse files

Update README.md

parent 86e0e064

README.md

+10 −2
Original line number Diff line number Diff line
@@ -10,12 +10,12 @@ pip install -r requirements.txt 


## Usage



Note: viewing jupyter-notebooks on git may lack some features (not showing output or choosing options from [ipywidget](https://ipywidgets.readthedocs.io/en/stable/examples/Using%20Interact.html)) 



**Note:** viewing jupyter-notebooks on git may lack some features (not showing output or choosing options from [ipywidget](https://ipywidgets.readthedocs.io/en/stable/examples/Using%20Interact.html)) 



### CNN



#### Coco API



We used [https://github.com/cocodataset/cocoapi](https://github.com/cocodataset/cocoapi)  

Installation:  

```
@@ -29,6 +29,7 @@ python setup.py install 
Tensorflow pretrained image classification models available at [https://github.com/tensorflow/models/tree/master/research/slim](https://github.com/tensorflow/models/tree/master/research/slim)



##### Singlelabel Model [PDF](https://arxiv.org/pdf/1512.03385.pdf)



* How to retrain Singlelabel:  

TODO
@@ -46,6 +47,7 @@ TODO 
[Trained model (+Hyperparameters)](/models/resnet_hp/)



##### Multilabel Model



* How to retrain multilabel:  



* **Results:**
@@ -65,6 +67,7 @@ python 100.py 




#### 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))  



* Chosen Visualization style [Activation Grid](https://colab.research.google.com/github/tensorflow/lucid/blob/master/notebooks/building-blocks/ActivationGrid.ipynb)
@@ -101,12 +104,16 @@ See [example notebook](/lucid/Visualization - singlelabel.ipynb) 
## Demo



### CNN



[Demo Notebook](/Demo/CNN.ipynb)



### LSTM



TODO:

[Demo Notebook]()



## References



Vinyals, O., Toshev, A., Bengio, S., & Erhan, D. (2015). **Show and tell: A neural image caption generator**. In *Proceedings of the IEEE conference on computer vision and pattern recognition* (pp. 3156-3164).  

[PDF](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.761.3284&rep=rep1&type=pdf)
@@ -125,4 +132,5 @@ He, K., Zhang, X., Ren, S., & Sun, J. (2016). **Deep residual learning for image 
for even more check the [resources page](https://gitlab.cl.uni-heidelberg.de/jmrs/caption/wikis/organization/resources) from our wiki



## LICENSE



This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details