update readme

README.md

@@ -1,21 +1,21 @@
 [![Python CI](https://github.com/lfoppiano/grobid-superconductors-tools/actions/workflows/python-app.yml/badge.svg)](https://github.com/lfoppiano/grobid-superconductors-tools/actions/workflows/python-app.yml)
 
+# Material Parsers (and other tools)
 
-# Grobid-superconductors material name tools
+Sister project of [grobid-superconductors](https://github.com/lfoppiano/grobid-superconductors) containing a web service that interfaces with the python libraries (e.g. Spacy).
 
-Sister project of [grobid-superconductors](https://github.com/lfoppiano/grobid-superconductors) containing a webservice that interfaces with the python libraries (e.g. Spacy). 
+The service provides the following functionalities:
 
-The service provides the following functionalities: 
- - [Convert material name to formula](#convert-material-name-to-formula) (e.g. Lead -> Pb, Hydrogen -> H): `/convert/name/formula`
- - [Decompose formula into structured dict of elements](#decompose-formula-into-structured-dict-of-elements) (e.g. La x Fe 1-x O7-> {La: x, Fe: 1-x, O: 7}):  `/convert/formula/composition`
- - Classify material in classes (from the superconductors domain) using a rule-base table (e.g. "La Cu Fe" -> Cuprates): `/classify/formula`
- - Tc classification (Tc, not-Tc): `/classify/tc` **for information please open an issue**
- - Relation extraction given a sentence and two entities: `/process/link` **for information please open an issue**
+- [Convert material name to formula](#convert-material-name-to-formula) (e.g. Lead -> Pb, Hydrogen -> H): `/convert/name/formula`
+- [Decompose formula into structured dict of elements](#decompose-formula-into-structured-dict-of-elements) (e.g. La x Fe 1-x O7-> {La: x, Fe: 1-x, O: 7}):  `/convert/formula/composition`
+- Classify material in classes (from the superconductors domain) using a rule-base table (e.g. "La Cu Fe" -> Cuprates): `/classify/formula`
+- Tc classification (Tc, not-Tc): `/classify/tc` **for information please open an issue**
+- Relation extraction given a sentence and two entities: `/process/link` **for information please open an issue**
+- Material processing using Deep Learning `/process/material`
 
 ## Usage
 
-The service is deployed on huggingface spaces, and [can be used right away](https://lfoppiano-grobid-superconductors-tools.hf.space/version). 
-For installing the service in your own environment see below. 
+The service is deployed on huggingface spaces, and [can be used right away](https://lfoppiano-grobid-superconductors-tools.hf.space/version). For installing the service in your own environment see below.
 
 ### Convert material name to formula
 
@@ -24,41 +24,44 @@ curl --location 'https://lfoppiano-grobid-superconductors-tools.hf.space/convert
 --form 'input="Hydrogen"'
 ```
 
-output: 
+output:
 
 ```
 {"composition": {"H": "1"}, "name": "Hydrogen", "formula": "H"}
 ```
 
 ### Decompose formula in a structured dict of elements
 
-Example: 
+Example:
+
 ```
 curl --location 'https://lfoppiano-grobid-superconductors-tools.hf.space/convert/formula/composition' \
 
 --form 'input="CaBr2-x"'
 ```
 
-output:  
+output:
 
 ```
 {"composition": {"Ca": "1", "Br": "2-x"}}
 ```
 
 ### Classify materials in classes
 
-Example: 
+Example:
+
 ```
 curl --location 'https://lfoppiano-grobid-superconductors-tools.hf.space/classify/formula' \
 --form 'input="(Mo 0.96 Zr 0.04 ) 0.85 B x "'
 ```
 
-output: 
+output:
+
 ```
 ['Alloys']
 ```
 
-## Installing in your environment 
+## Installing in your environment
 
 ```
 docker run -it lfoppiano/grobid-superconductors-tools:2.1
@@ -67,41 +70,37 @@ docker run -it lfoppiano/grobid-superconductors-tools:2.1
 ## References
 
 If you use our work, and write about it, please cite [our paper](https://hal.inria.fr/hal-03776658):
+
 ```bibtex
-	@article{doi:10.1080/27660400.2022.2153633,
-		author = {Luca Foppiano and Pedro Baptista Castro and Pedro Ortiz Suarez and Kensei Terashima and Yoshihiko Takano and Masashi Ishii},
-		title = {Automatic extraction of materials and properties from superconductors scientific literature},
-		journal = {Science and Technology of Advanced Materials: Methods},
-		volume = {3},
-		number = {1},
-		pages = {2153633},
-		year  = {2023},
-		publisher = {Taylor & Francis},
-		doi = {10.1080/27660400.2022.2153633},
-		URL = { 
-			https://doi.org/10.1080/27660400.2022.2153633
-		},
-		eprint = { 
-		https://doi.org/10.1080/27660400.2022.2153633
-		}
-	}
+@article{doi:10.1080/27660400.2022.2153633,
+    author = {Luca Foppiano and Pedro Baptista Castro and Pedro Ortiz Suarez and Kensei Terashima and Yoshihiko Takano and Masashi Ishii},
+    title = {Automatic extraction of materials and properties from superconductors scientific literature},
+    journal = {Science and Technology of Advanced Materials: Methods},
+    volume = {3},
+    number = {1},
+    pages = {2153633},
+    year = {2023},
+    publisher = {Taylor & Francis},
+    doi = {10.1080/27660400.2022.2153633},
+    URL = {
+    https://doi.org/10.1080/27660400.2022.2153633
+    },
+    eprint = {
+    https://doi.org/10.1080/27660400.2022.2153633
+    }
+}
 ```
 
-
-
 ## Overview of the repository
 
- - [Converters](grobid_superconductors/converters) TSV to/from Grobid XML files conversion 
- - [Linking](grobid_superconductors/linking) module: A rule based python algorithm to link entities
- - [Commons libraries](grobid_superconductors/commons): contains common code shared between the various component. The Grobid client was borrowed from [here](https://github.com/kermitt2/grobid-client-python), the tokenizer from [there](https://github.com/kermitt2/delft).
-
-
+- [Converters](grobid_superconductors/converters) TSV to/from Grobid XML files conversion
+- [Linking](grobid_superconductors/linking) module: A rule based python algorithm to link entities
+- [Commons libraries](grobid_superconductors/commons): contains common code shared between the various component. The Grobid client was borrowed from [here](https://github.com/kermitt2/grobid-client-python), the tokenizer from [there](https://github.com/kermitt2/delft).
 
 ## Developer's notes
 
 > python -m spacy download en_core_web_sm
 
-
 ```shell
 conda install -c apple tensorflow-deps
 ```
@@ -114,7 +113,7 @@ pip install -r requirements.txt
 conda install scikit-learn=1.0.1
 ```
 
-We need to remove tensorflow, h5py, scikit-learn from the delft dependencies in setup.py 
+We need to remove tensorflow, h5py, scikit-learn from the delft dependencies in setup.py
 
 ```shell
 pip install -e ../../delft