improve README

README.md

@@ -1,66 +1,225 @@
 
 ![sbb-ner-demo example](.screenshots/sbb_ner_demo.png?raw=true)
 
+How the models have been obtained: http://area.staatsbibliothek-berlin.de/sbb-upload/qurator/sbb_ner/konvens2019.pdf .
+
+***
+#Installation:
+
+Setup virtual environment:
+```
+virtualenv --python=python3.6 venv
+```
+
+Activate virtual environment:
+```
+source venv/bin/activate
+```
+
+Upgrade pip:
+```
+pip install -U pip
+```
+
+Install package together with its dependencies in development mode:
+```
+pip install -e ./
+```
+
+Download required models: http://area.staatsbibliothek-berlin.de/sbb-upload/qurator/sbb_ner/models.tar.gz 
+
+Extract model archive:
+```
+tar -xzf models.tar.gz
+```
+
+Run webapp directly:
+
+```
+env FLASK_APP=qurator/sbb_ner/webapp/app.py env FLASK_ENV=development env USE_CUDA=True flask run --host=0.0.0.0
+```
+
+Set USE_CUDA=False, if you do not have a GPU available/installed.
+
+# Docker
+
+## CPU-only:
+
+```
+docker build --build-arg http_proxy=$http_proxy  -t qurator/webapp-ner-cpu -f Dockerfile.cpu .
+```
+
+```
+docker run -ti --rm=true --mount type=bind,source=data/konvens2019,target=/usr/src/qurator-sbb-ner/data/konvens2019 -p 5000:5000 qurator/webapp-ner-cpu
+```
+
+## GPU:
+
+Make sure that your GPU is correctly set up and that nvidia-docker has been installed.
+
+
+```
+docker build --build-arg http_proxy=$http_proxy  -t qurator/webapp-ner-gpu -f Dockerfile .
+```
+
+```
+docker run -ti --rm=true --mount type=bind,source=data/konvens2019,target=/usr/src/qurator-sbb-ner/data/konvens2019 -p 5000:5000 qurator/webapp-ner-gpu
+```
+
+NER web-interface is availabe at http://localhost:5000 . 
+
+# REST - Interface
+
+Get available models:
+```
+curl http://localhost:5000/models
+```
+
+Output:
+
+```
+[
+  {
+    "default": true, 
+    "id": 1, 
+    "model_dir": "data/konvens2019/build-wd_0.03/bert-all-german-de-finetuned", 
+    "name": "DC-SBB + CONLL + GERMEVAL"
+  }, 
+  {
+    "default": false, 
+    "id": 2, 
+    "model_dir": "data/konvens2019/build-on-all-german-de-finetuned/bert-sbb-de-finetuned", 
+    "name": "DC-SBB + CONLL + GERMEVAL + SBB"
+  }, 
+  {
+    "default": false, 
+    "id": 3, 
+    "model_dir": "data/konvens2019/build-wd_0.03/bert-sbb-de-finetuned", 
+    "name": "DC-SBB + SBB"
+  }, 
+  {
+    "default": false, 
+    "id": 4, 
+    "model_dir": "data/konvens2019/build-wd_0.03/bert-all-german-baseline", 
+    "name": "CONLL + GERMEVAL"
+  }
+]
+```
+
+Perform NER using model 1: 
+
+```
+curl -d '{ "text": "Paris Hilton wohnt im Hilton Paris in Paris." }' -H "Content-Type: application/json" http://localhost:5000/ner/1
+```
+
+Output:
+
+```
+[
+  [
+    {
+      "prediction": "B-PER", 
+      "word": "Paris"
+    }, 
+    {
+      "prediction": "I-PER", 
+      "word": "Hilton"
+    }, 
+    {
+      "prediction": "O", 
+      "word": "wohnt"
+    }, 
+    {
+      "prediction": "O", 
+      "word": "im"
+    }, 
+    {
+      "prediction": "B-ORG", 
+      "word": "Hilton"
+    }, 
+    {
+      "prediction": "I-ORG", 
+      "word": "Paris"
+    }, 
+    {
+      "prediction": "O", 
+      "word": "in"
+    }, 
+    {
+      "prediction": "B-LOC", 
+      "word": "Paris"
+    }, 
+    {
+      "prediction": "O", 
+      "word": "."
+    }
+  ]
+]
+
+```
+
+# Model-Training 
+
 ***
-# Preprocessing of NER ground-truth:
+## Preprocessing of NER ground-truth:
 
 
-## compile_conll
+### compile_conll
 
 Read CONLL 2003 ner ground truth files from directory and
 write the outcome of the data parsing to some pandas DataFrame that is
 stored as pickle.
 
-### Usage
+#### Usage
 
 ```
 compile_conll --help
 ```
 
-## compile_germ_eval
+### compile_germ_eval
 
 Read germ eval .tsv files from directory and write the
 outcome of the data parsing to some pandas DataFrame that is stored as
 pickle.
 
-### Usage
+#### Usage
 
 ```
 compile_germ_eval --help
 ```
 
-## compile_europeana_historic
+### compile_europeana_historic
 
 Read europeana historic ner ground truth .bio files from directory 
 and write the outcome of the data parsing to some pandas
 DataFrame that is stored as pickle.
 
-### Usage
+#### Usage
 
 ```
 compile_europeana_historic --help
 ```
 
 
-## compile_wikiner
+### compile_wikiner
 
 Read wikiner files from directory and write the outcome
 of the data parsing to some pandas DataFrame that is stored as pickle.
 
-### Usage
+#### Usage
 
 ```
 compile_wikiner --help
 ```
 
 ***
-# Train BERT - NER model:
+## Train BERT - NER model:
 
-## bert-ner
+### bert-ner
 
 Perform BERT for NER supervised training and test/cross-validation.
 
-### Usage
+#### Usage
 
 ```
 bert-ner --help