fix README

README.md

@@ -16,7 +16,20 @@ code to work.
 Keras: if you have trouble installing tensorflow for keras backend you can use theano but you need to change keras 
 backend since the default is tensorflow. To change it edit this file ~/.keras/keras.json.
 
-Additionally you need these external programas installed 
+
+To install the requirements.txt file follow these simple steps:
+
+1. Install pip for python 3.5. For example in Ubuntu you can install it like this:
+
+```
+sudo apt-get install python3-pip 
+```
+2. Install the requirements.txt file like this:
+```
+pip install -r requirements.txt
+```
+
+Additionally you need these external programas installed:
 
 -ghostscript
 
@@ -26,6 +39,7 @@ Additionally you need these external programas installed
 
 *these external programs are not used in this version of the prototype but they will possibly be used on future updates so this requirement could change.
 
+
 Required files:
 
 -The pdf file(s)
@@ -36,20 +50,23 @@ Required files:
 
 ### Installing
 
-The program itself doesn't need to be installed just copied to a local path and the script run with python 3.5.
+The program itself needs to be copied to a local path and the script run with python 3.5.
 
 ### Usage
 ```
-Usage: classify_pdf.py [-fp [PATH]|[FILE]] [-conf [FILE]] [-meta [FILE] or [filename=<filename>,folder_name=<folder_name>]] [-mod [FILE]] [-c [INT]] [-b [INT]] [-sp] [-sf] [-pf [FILE]] [-ff [FILE]] [-rf [FILE]] [-preprocess_only] [-features_only] [-t [FLOAT]]\n\n\
+Usage: python classify_pdf.py [-fp [PATH]|[FILE]] [-conf [FILE]] [-meta [FILE] or [filename=<filename>,
+folder_name=<folder_name>]] [-mod [FILE]] [-c [INT]] [-b [INT]] [-sp] [-sf] [-pf [FILE]] [-ff [FILE]] 
+[-rf [FILE]] [-preprocess_only] [-features_only] [-t [FLOAT]]\n\n\
 ```
 Arguments:
 
     -fp: parameter used to specify the path to the pdf file(s). This parameter is always required
 
-    -conf: parameter used to pass the config file. If a config file is passed then the values specified in it
-    will take precedence over the parameters given in the command line. Each parameter must be specified on a new line
-    with the name of the parameter, if the parameter has a value, the name should be followed by an equal sign (=)
-    and then the value of the parameter. Ex. metadata_file=../metadata.csv or save_preprocess. If not config file is specified the default param.conf file will be used 
+    -conf: parameter used to pass the config file. If a config file is passed then the values specified
+    in it will take precedence over the parameters given in the command line. Each parameter must be 
+    specified on a new line with the name of the parameter, if the parameter has a value, the name should 
+    be followed by an equal sign (=) and then the value of the parameter. Ex. metadata_file=../metadata.csv 
+    or save_preprocess. If not config file is specified the default param.conf file will be used 
     Parameters that can be specified on the config file:
         metadata_file: path to metadata csv file
         batch: the quantity of files per batch
@@ -58,28 +75,34 @@ Arguments:
         predict_threshold: the threshold used for classification of the documents
         save_preprocess: use this parameter if the preprocessing data should be saved on your hard disc
         save_features: use this parameter if the features should be saved on your hard disc
-        preprocess_only: use this parameter if only the preprocessing data should be extracted and saved on your hard disc
-        features_only: use this parameter if only the feature data should be calculated and saved on your hard disc
+        preprocess_only: use this parameter if only the preprocessing data should be extracted and saved on
+        your hard disc
+        features_only: use this parameter if only the feature data should be calculated and saved on 
+        your hard disc
         preprocessing_file: specifies an existing file on which to append the preprocessing data.
         features_file: specifies an existing file on which to append the feature data.
         prediction_file: specifies an existing file on which to append the result predicition data.
 
-    -meta: parameter used to specify the path to the metadata csv file. It is also possible to pass the metadata of 
-    a single file directly on the command line by writing filename=<filename>,folder_name=<folder_name> instead of
-    the path to the metadata csv file. Be aware that if the metadata is passed on the command line the -fp parameter should point
-    to one single file and not to a path of a group of files.
+    -meta: parameter used to specify the path to the metadata csv file. It is also possible to pass the 
+    metadata of a single file directly on the command line by writing filename=<filename>,
+    folder_name=<folder_name> instead of the path to the metadata csv file. Be aware that if the metadata 
+    is passed on the command line the -fp parameter should point to one single file and not to a path of 
+    a group of files. If the metadata file is passed as paremeter only the files on it will be processed,
+    any extra pdf files on the path spcified by the agument -fp that are not on the metadata file will
+    be ignored.
 
-    -mod: parameter used to specify the path to the trained model. If no model is specified the default ones will be loaded.
-    The default model with metadata features is NN.model, the default model without metadata features is NN_noMeta.model.
+    -mod: parameter used to specify the path to the trained model. If no model is specified the default 
+    ones will be loaded. The default model with metadata features is NN.model, the default model without 
+    metadata features is NN_noMeta.model.
 
     -c: parameter used to specify the number of cores to be used for parallel processing. 
 
-    -b: parameter used to specify the number of files to be processed per batch. The preprocessing, features and prediction
-    results will be updated after each batch on the saving files.
+    -b: parameter used to specify the number of files to be processed per batch. The preprocessing, 
+    features and prediction results will be updated after each batch on the saving files.
 
-    -sp: parameter used if you want to save the preprocessing data. If it doesn't exist a folder will be created in
-    '../preprocessing data'. Inside this path a 'text_files' folder will be created to store the extracted text 
-    from each file and a 'features' folder will be created to store the features.
+    -sp: parameter used if you want to save the preprocessing data. If it doesn't exist a folder will be 
+    created in '../preprocessing data'. Inside this path a 'text_files' folder will be created to store 
+    the extracted text from each file and a 'features' folder will be created to store the features.
 
     -sf: parameter used if you want to save the features data.
 
@@ -91,9 +114,9 @@ Arguments:
     The default file is 'preprocessing_data/features/features.json'. If you don't use this argument
     the existing default file will be ovewritten.
 
-    -rf: parameter used to specify the result predictions file. If the file doesn't exist it will be created. The default
-    file if this parameter is not specified is '../predictions/prediction.json'. If you don't use this argument
-    the existing default file will be ovewritten.
+    -rf: parameter used to specify the result predictions file. If the file doesn't exist it will be created. 
+    The default file if this parameter is not specified is '../predictions/prediction.json'. If you don't 
+    use this argument the existing default file will be ovewritten.
 
     -preprocess_only: parameter used if you want to extract and save preprocessing data only.