Update Readme

README.md

@@ -4,33 +4,37 @@ language:
 - fr
 task_categories:
 - image-to-text
-pretty_name: PyLaia RIMES
-
+pretty_name: RIMES-2011-Lines
+tags:
+- Handwritten Text Recognition
 dataset_info:
   features:
-    - name: image
-      dtype: image
-    - name: text
-      dtype: string
+  - name: image
+    dtype: image
+  - name: text
+    dtype: string
   splits:
-    - name: train
-      num_examples: 10188
-    - name: validation
-      num_examples: 1138
-    - name: test
-      num_examples: 778
+  - name: train
+    num_examples: 10188
+  - name: validation
+    num_examples: 1138
+  - name: test
+    num_examples: 778
   dataset_size: 12104
+size_categories:
+- 10K<n<100K
 ---
 
-# PyLaia RIMES Dataset
+# RIMES-2011-Lines Dataset
 
 ## Table of Contents
-- [PyLaia RIMES Dataset](#pylaia-rimes-dataset)
+- [RIMES-2011-Lines Dataset](#pylaia-rimes-dataset)
   - [Table of Contents](#table-of-contents)
   - [Dataset Description](#dataset-description)
     - [Dataset Summary](#dataset-summary)
     - [Languages](#languages)
   - [Dataset Structure](#dataset-structure)
+    - [Data Loading](#data-loading)
     - [Data Instances](#data-instances)
     - [Data Fields](#data-fields)
     - [Data Splits](#data-splits)
@@ -43,7 +47,13 @@ dataset_info:
 
 ### Dataset Summary
 
-Briefly summarize the dataset, its intended use and the supported tasks. Give an overview of how and why the dataset was created. The summary should explicitly mention the **languages** present in the dataset (possibly in broad terms, e.g. *translations between several pairs of European languages*), and describe the domain, topic, or genre covered.
+The RIMES (Reconnaissance et Indexation de données Manuscrites et de fac similÉS) database has been created to evaluate automatic recognition and indexing systems for handwritten documents. Of particular interest are cases such as those sent by mail or fax from individuals to companies or administrations.
+
+The database was collected by asking volunteers to write handwritten letters in exchange for gift certificates. Volunteers were given a fictitious identity (same gender as the real one) and up to 5 scenarios. Each scenario was chosen from among 9 realistic topics: change of personal data (address, bank account), request for information, opening and closing (customer account), change of contract or order, complaint (poor quality of service...), payment difficulties (request for delay, tax exemption...), reminder, complaint with other circumstances and a target (administrations or service providers (telephone, electricity, bank, insurance). The volunteers wrote a letter with this information in their own words. The layout was free and the only request was to use white paper and write legibly in black ink.
+
+The campaign was a success, with more than 1,300 people contributing to the RIMES database by writing up to 5 letters. The resulting RIMES database contains 12,723 pages, corresponding to 5605 mails of two to three pages each.
+
+Note that all images are resized to a fixed height of 128 pixels.
 
 ### Languages
 
@@ -51,9 +61,19 @@ All the documents in the dataset are written in French.
 
 ## Dataset Structure
 
-### Data Instances
+### Data Loading
+
+The dataset can be loaded using this simple code:
 
+```py
+from datasets import load_dataset
+dataset = load_dataset("Teklia/rimes-2011-lines")
 ```
+
+### Data Instances
+
+Each instance represents an image and its transcription:
+```json
 {
   'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2560x128 at 0x1A800E8E190,
   'text': 'Comme indiqué dans les conditions particulières de mon contrat d'assurance'
@@ -62,19 +82,13 @@ All the documents in the dataset are written in French.
 
 ### Data Fields
 
-
-- `image`: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
+- `image`: A PIL.Image.Image object containing the image. Note that when accessing the image column: `dataset[0]["image"]` the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. `dataset[0]["image"]` should always be preferred over `dataset["image"][0]`.
 - `text`: the label transcription of the image.
 
 ### Data Splits
 
-Describe and name the splits in the dataset if there are more than one.
-
-Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g. if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here.
-
-Provide the sizes of each split. As appropriate, provide any descriptive statistics for the features, such as average length.  For example:
+Three sets are available: train, validation and test.
 
 |                         | train | validation | test |
 |-------------------------|------:|-----------:|-----:|
-| Input Sentences         |       |            |      |
-| Average Sentence Length |       |            |      |
+| Number of Lines         | 10188 |   1138     | 778  |