Update README with images

README.md

@@ -1,10 +1,64 @@
-# [WIP] Deep Feature Interpolation
+# Deep Feature Interpolation
 Implementation of the Deep Feature Interpolation for Image Content Changes [paper](https://arxiv.org/abs/1611.05507) in tensorflow.
 
+## Examples
+In these pictures a setting with the following parameters were used
+
+| option | value |
+| ------ | ----- |
+|optimizer | adam |
+|lr | 0.1 |
+|k | 100 |
+|alpha | 0.4 |
+|beta | 2 |
+|lamb | 0.001 |
+|steps | 2000 |
+
+### Eyeglasses
+![](./outputs/eyeglasses_alpha0.4_k100/Berlusconi.png)
+![](./outputs/eyeglasses_alpha0.4_k100/Trump.png)
+![](./outputs/eyeglasses_alpha0.4_k100/Schroeder.png)
+![](./outputs/eyeglasses_alpha0.4_k100/Bush.png)
+
+### Sunglasses
+![](./outputs/sunglasses_alpha0.4_k100/Berlusconi.png)
+![](./outputs/sunglasses_alpha0.4_k100/Trump.png)
+![](./outputs/sunglasses_alpha0.4_k100/Schroeder.png)
+![](./outputs/sunglasses_alpha0.4_k100/Bush.png)
+
+### Mustache
+![](./outputs/mustache_alpha0.4_k100/Berlusconi.png)
+![](./outputs/mustache_alpha0.4_k100/Trump.png)
+![](./outputs/mustache_alpha0.4_k100/Schroeder.png)
+![](./outputs/mustache_alpha0.4_k100/Bush.png)
+
+### Female
+![](./outputs/female_alpha0.4_k100/Berlusconi.png)
+![](./outputs/female_alpha0.4_k100/Trump.png)
+![](./outputs/female_alpha0.4_k100/Schroeder.png)
+![](./outputs/female_alpha0.4_k100/Bush.png)
+
+### Mouth wide open
+![](./outputs/mouth_open_alpha0.4_k100/Berlusconi.png)
+![](./outputs/mouth_open_alpha0.4_k100/Trump.png)
+![](./outputs/mouth_open_alpha0.4_k100/Schroeder.png)
+![](./outputs/mouth_open_alpha0.4_k100/Bush.png)
+
+### Smiling
+![](./outputs/smiling_alpha0.4_k100/Berlusconi.png)
+![](./outputs/smiling_alpha0.4_k100/Trump.png)
+![](./outputs/smiling_alpha0.4_k100/Schroeder.png)
+![](./outputs/smiling_alpha0.4_k100/Bush.png)
+
+
+
 ## Setup
 ### Model
 Download the VGG19 model from [here](https://mega.nz/#!xZ8glS6J!MAnE91ND_WyfZ_8mvkuSa2YcA7q-1ehfSm-Q1fxOvvs)
 
+### Data
+Download the LFW-Dataset from [here](http://vis-www.cs.umass.edu/lfw/lfw-deepfunneled.tgz)
+
 ### Python environment
 Make sure you have `virtualenv` installed  
 Run:
@@ -13,36 +67,54 @@ $ virtualenv -p /usr/bin/python3 env         # Create virtual python environment
 $ ./env/bin/pip install -r requirements.txt  # Install all necessary requirements
 ```
 
-### GPU
+### Enable GPU usage
 Follow [these instructions](http://www.computervisionbytecnalia.com/es/2016/06/deep-learning-development-setup-for-ubuntu-16-04-xenial/) up to point 4 to install CUDA on your system.
-Use the gpu enabled tensorflow library by installing
-```bash
-$ ./env/bin/pip install tensorflow-gpu
-```
 
 ## Usage
 ```
-./env/bin/python src/main.py -h
-usage: Deep Feature Interpolation [-h] [--data_dir DATA_DIR]
-                                  [--model_path MODEL_PATH] [--gpu]
-                                  [--num_layers NUM_LAYERS]
+$ ./env/bin/python src/main.py -h
+usage: Deep Feature Interpolation [-h] [--data-dir DATA_DIR]
+                                  [--model-path MODEL_PATH] [--gpu]
+                                  [--num-layers NUM_LAYERS]
                                   [--feature FEATURE]
-                                  [--person_index PERSON_INDEX]
-                                  [--list_features] [--tf]
+                                  [--person-index PERSON_INDEX]
+                                  [--person-image PERSON_IMAGE]
+                                  [--list-features] [--optimizer OPTIMIZER]
+                                  [--lr LR] [--steps STEPS] [--eps EPS] [--tk]
+                                  [--k K] [--alpha ALPHA] [--beta BETA]
+                                  [--lamb LAMB] [--rebuild-cache]
+                                  [--random-start] [--verbose] [--invert]
 
 optional arguments:
   -h, --help            show this help message and exit
-  --data_dir DATA_DIR, -d DATA_DIR
+  --data-dir DATA_DIR, -d DATA_DIR
                         Path to data directory containing the images
-  --model_path MODEL_PATH, -m MODEL_PATH
+  --model-path MODEL_PATH, -m MODEL_PATH
                         Path to the model file (*.npy)
   --gpu, -g             Enable gpu computing
-  --num_layers NUM_LAYERS, -n NUM_LAYERS
+  --num-layers NUM_LAYERS, -n NUM_LAYERS
                         Number of layers. One of {1,2,3}
   --feature FEATURE, -f FEATURE
                         Name of the Feature.
-  --person_index PERSON_INDEX, -p PERSON_INDEX
+  --person-index PERSON_INDEX, -p PERSON_INDEX
                         Index of the start image.
-  --list_features, -l   List all available features.
-  --tf                  Use Tensorflow for the optimization step
+  --person-image PERSON_IMAGE
+                        Start image path.
+  --list-features, -l   List all available features.
+  --optimizer OPTIMIZER, -o OPTIMIZER
+                        Optimizer type
+  --lr LR               Learning rate interval in log10
+  --steps STEPS, -s STEPS
+                        Number of steps
+  --eps EPS, -e EPS     Epsilon interval in log10
+  --tk                  Use TkInter
+  --k K, -k K           Number of nearest neighbours
+  --alpha ALPHA, -a ALPHA
+                        Alpha param
+  --beta BETA, -b BETA  Beta param
+  --lamb LAMB           Lambda param
+  --rebuild-cache, -rc  Rebuild the cache
+  --random-start, -rs   Use random start_img
+  --verbose, -v         Set verbose
+  --invert, -i          Invert deep feature difference (No Beard -> Beard)
 ```

requirements-gpu.txt

@@ -1,10 +1,7 @@
-numpy==1.11.3
-pandas==0.19.2
-protobuf==3.1.0.post1
-python-dateutil==2.6.0
-pytz==2016.10
-scikit-learn==0.18.1
+matplotlib==2.0.0
+numpy==1.12.0
 scipy==0.18.1
-six==1.10.0
+pandas==0.19.2
+scikit_learn==0.18.1
 tensorflow-gpu==0.12.1
-pillow==4.0.0
+tqdm==4.11.2

requirements.txt

@@ -1,6 +1,7 @@
-numpy==1.11.3
-pandas==0.19.2
+matplotlib==2.0.0
+numpy==1.12.0
 scipy==0.18.1
+pandas==0.19.2
 scikit_learn==0.18.1
 tensorflow==0.12.1
-pillow==4.0.0
+tqdm==4.11.2