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+++ b/README.md
@@ -1,4 +1,18 @@
-OCR for Japanese manga
+# Manga OCR
+
+Optical character recognition for Japanese text, with the main focus being Japanese manga.
+It uses a custom end-to-end model built with Transformers' [Vision Encoder Decoder](https://huggingface.co/docs/transformers/model_doc/visionencoderdecoder) framework. 
+
+Manga OCR can be used as a general purpose printed Japanese OCR, but its main goal was to provide a high quality
+text recognition, robust against various scenarios specific to manga:
+- both vertical and horizontal text
+- text with furigana
+- text overlaid on images
+- wide variety of fonts and font styles
+- low quality images
+
+Unlike many OCR models, Manga OCR supports recognizing multi-line text in a single forward pass,
+so that text bubbles found in manga can be processed at once, without splitting them into lines.
 
 # Installation
 
@@ -9,12 +23,38 @@ otherwise this step can be skipped.
 
 Run:
 
-```
+```commandline
 pip install manga-ocr
 ```
 
 # Usage
 
+## Running in the background
+
+Manga OCR can run in the background, processing new images as they appear.
+
+You might then use a tool like [ShareX](https://getsharex.com/) to manually capture a region of the screen and let the
+OCR read it either from the system clipboard, or a specified directory.
+
+For example:
+
+- To read images from clipboard and write recognized texts to clipboard, run:
+    ```commandline
+    manga_ocr
+    ```
+- To read images from ShareX's screenshot folder, run:
+    ```commandline
+    manga_ocr "/path/to/sharex/screenshot/folder"
+    ```
+- To see other options, run:
+    ```commandline
+    manga_ocr --help
+    ```
+
+If `manga_ocr` doesn't work, you might also try replacing it with `python -m manga_ocr`.
+
+## Python API
+
 ```python
 from manga_ocr import MangaOcr
 
@@ -33,3 +73,39 @@ mocr = MangaOcr()
 img = PIL.Image.open('/path/to/img')
 text = mocr(img)
 ```
+
+## Usage tips
+- OCR supports multi-line text, but the longer the text, the more likely some errors are to occur.
+  If the recognition failed for some part of a longer text, you might try to run it on a smaller portion of the image.
+- The model was trained specifically to handle manga well, but should do a decent job on other types of printed text,
+  such as novels or video games. It probably won't be able to handle handwritten text though. 
+- The model always attempts to recognize some text on the image, even if there is none.
+  Because it uses a transformer decoder (and therefore has some understanding of the Japanese language),
+  it might even "dream up" some realistically looking sentences! This shouldn't be a problem for most use cases,
+  but it might get improved in the next version.
+
+# Examples
+
+Here are some cherry-picked examples showing the capability of the model. 
+
+| image                | Manga OCR result |
+|----------------------|------------------|
+| ![](examples/00.jpg) | 素直にあやまるしか |
+| ![](examples/01.jpg) | 立川で見た〝穴〟の下の巨大な眼は： |
+| ![](examples/02.jpg) | 実戦剣術も一流です |
+| ![](examples/03.jpg) | 第３０話重苦しい闇の奥で静かに呼吸づきながら |
+| ![](examples/04.jpg) | よかったじゃないわよ！何逃げてるのよ！！早くあいつを退治してよ！ |
+| ![](examples/05.jpg) | ぎゃっ |
+| ![](examples/06.jpg) | ピンポーーン |
+| ![](examples/07.jpg) | ＬＩＮＫ！私達７人の力でガノンの塔の結界をやぶります |
+| ![](examples/08.jpg) | ファイアパンチ |
+| ![](examples/09.jpg) | 少し黙っている |
+| ![](examples/10.jpg) | わかるかな〜？ |
+| ![](examples/11.jpg) | 警察にも先生にも町中の人達に！！ |
+
+
+
+
+# Acknowledgments
+
+This project was done with the usage of [Manga109-s](http://www.manga109.org/en/download_s.html) dataset.
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