quickstart_en.md

# PaddleOCR Quick Start

**Note:** This tutorial mainly introduces the usage of PP-OCR series models, please refer to [PP-Structure Quick Start](../../ppstructure/docs/quickstart_en.md) for the quick use of document analysis related functions.

- [1. Installation](#1-installation)
    - [1.1 Install PaddlePaddle](#11-install-paddlepaddle)
    - [1.2 Install PaddleOCR Whl Package](#12-install-paddleocr-whl-package)
    - [1.3 Use PaddleOCR with Docker](#13-use-paddleocr-with-docker)
- [2. Easy-to-Use](#2-easy-to-use)
    - [2.1 Use by Command Line](#21-use-by-command-line)
      - [2.1.1 Chinese and English Model](#211-chinese-and-english-model)
      - [2.1.2 Multi-language Model](#212-multi-language-model)
    - [2.2 Use by Code](#22-use-by-code)
      - [2.2.1 Chinese & English Model and Multilingual Model](#221-chinese--english-model-and-multilingual-model)
- [3. Summary](#3-summary)



<a name="1nstallation"></a>

## 1. Installation

<a name="11-install-paddlepaddle"></a>

### 1.1 Install PaddlePaddle

> If you do not have a Python environment, please refer to [Environment Preparation](./environment_en.md).

- If you have CUDA 9 or CUDA 10 installed on your machine, please run the following command to install

  ```bash
  python3 -m pip install paddlepaddle-gpu
  ```

- If you have no available GPU on your machine, please run the following command to install the CPU version

  ```bash
  python3 -m pip install paddlepaddle
  ```

For more software version requirements, please refer to the instructions in [Installation Document](https://www.paddlepaddle.org.cn/install/quick) for operation.

<a name="12-install-paddleocr-whl-package"></a>

### 1.2 Install PaddleOCR Whl Package

```bash
pip install "paddleocr>=2.0.1" # Recommend to use version 2.0.1+
```

- **For windows users:** If you getting this error `OSError: [WinError 126] The specified module could not be found` when you install shapely on windows. Please try to download Shapely whl file [here](http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely).

  Reference: [Solve shapely installation on windows](https://stackoverflow.com/questions/44398265/install-shapely-oserror-winerror-126-the-specified-module-could-not-be-found)

- **For layout analysis users**, run the following command to install **Layout-Parser**

  ```bash
  pip3 install -U https://paddleocr.bj.bcebos.com/whl/layoutparser-0.0.0-py3-none-any.whl
  ```
<a name="13-use-paddleocr-with-docker"></a>

### 1.3 Use PaddleOCR with Docker

> If you  do not have a Docker environment, please refer to [Docker](https://www.docker.com/).

PaddleOCR provides built docker images with latest code. All you have to do is to **pull the docker image **and **run the docker image**. Then you can enjoy PaddleOCR without any extra action.

Get these images and guidance in [docker hub](https://hub.docker.com/repository/docker/paddlecloud/paddleocr), including CPU, GPU, ROCm environment versions. 

If you have some customized requirements about automatic building docker images, you can get it in github repo [PaddlePaddle/PaddleCloud](https://github.com/PaddlePaddle/PaddleCloud/tree/main/tekton).

<a name="2-easy-to-use"></a>

## 2. Easy-to-Use

<a name="21-use-by-command-line"></a>

### 2.1 Use by Command Line

PaddleOCR provides a series of test images, click [here](https://paddleocr.bj.bcebos.com/dygraph_v2.1/ppocr_img.zip) to download, and then switch to the corresponding directory in the terminal

```bash
cd /path/to/ppocr_img
```

If you do not use the provided test image, you can replace the following `--image_dir` parameter with the corresponding test image path

<a name="211-english-and-chinese-model"></a>

#### 2.1.1 Chinese and English Model

* Detection, direction classification and recognition: set the parameter`--use_gpu false` to disable the gpu device

  ```bash
  paddleocr --image_dir ./imgs_en/img_12.jpg --use_angle_cls true --lang en --use_gpu false
  ```

  Output will be a list, each item contains bounding box, text and recognition confidence

  ```bash
  [[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
  [[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
  [[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
  ......
  ```

* Only detection: set `--rec` to `false`

  ```bash
  paddleocr --image_dir ./imgs_en/img_12.jpg --rec false
  ```

  Output will be a list, each item only contains bounding box

  ```bash
  [[397.0, 802.0], [1092.0, 802.0], [1092.0, 841.0], [397.0, 841.0]]
  [[397.0, 750.0], [1211.0, 750.0], [1211.0, 789.0], [397.0, 789.0]]
  [[397.0, 702.0], [1209.0, 698.0], [1209.0, 734.0], [397.0, 738.0]]
  ......
  ```

* Only recognition: set `--det` to `false`

  ```bash
  paddleocr --image_dir ./imgs_words_en/word_10.png --det false --lang en
  ```

  Output will be a list, each item contains text and recognition confidence

  ```bash
  ['PAIN', 0.9934559464454651]
  ```

**Version**
paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). If you want to use other versions, you can set the parameter `--ocr_version`, the specific version description is as follows:
|  version name |  description |
|    ---    |   ---   |
| PP-OCRv3 | support Chinese and English detection and recognition, direction classifier, support multilingual recognition |
| PP-OCRv2 | only supports Chinese and English detection and recognition, direction classifier, multilingual model is not updated |
| PP-OCR   | support Chinese and English detection and recognition, direction classifier, support multilingual recognition |

If you want to add your own trained model, you can add model links and keys in [paddleocr](../../paddleocr.py) and recompile.

More whl package usage can be found in [whl package](./whl_en.md)

<a name="212-multi-language-model"></a>

#### 2.1.2 Multi-language Model

PaddleOCR currently supports 80 languages, which can be switched by modifying the `--lang` parameter.

``` bash
paddleocr --image_dir ./doc/imgs_en/254.jpg --lang=en
```

<div align="center">
    <img src="../imgs_en/254.jpg" width="300" height="600">
    <img src="../imgs_results/multi_lang/img_02.jpg" width="600" height="600">
</div>
The result is a list, each item contains a text box, text and recognition confidence

```text
[[[67.0, 51.0], [327.0, 46.0], [327.0, 74.0], [68.0, 80.0]], ('PHOCAPITAL', 0.9944712519645691)]
[[[72.0, 92.0], [453.0, 84.0], [454.0, 114.0], [73.0, 122.0]], ('107 State Street', 0.9744491577148438)]
[[[69.0, 135.0], [501.0, 125.0], [501.0, 156.0], [70.0, 165.0]], ('Montpelier Vermont', 0.9357033967971802)]
......
```

Commonly used multilingual abbreviations include

| Language            | Abbreviation |      | Language | Abbreviation |      | Language | Abbreviation |
| ------------------- | ------------ | ---- | -------- | ------------ | ---- | -------- | ------------ |
| Chinese & English   | ch           |      | French   | fr           |      | Japanese | japan        |
| English             | en           |      | German   | german       |      | Korean   | korean       |
| Chinese Traditional | chinese_cht  |      | Italian  | it           |      | Russian  | ru           |

A list of all languages and their corresponding abbreviations can be found in [Multi-Language Model Tutorial](./multi_languages_en.md)


<a name="22-use-by-code"></a>

### 2.2 Use by Code
<a name="221-chinese---english-model-and-multilingual-model"></a>

#### 2.2.1 Chinese & English Model and Multilingual Model

* detection, angle classification and recognition:

```python
from paddleocr import PaddleOCR,draw_ocr
# Paddleocr supports Chinese, English, French, German, Korean and Japanese.
# You can set the parameter `lang` as `ch`, `en`, `fr`, `german`, `korean`, `japan`
# to switch the language model in order.
ocr = PaddleOCR(use_angle_cls=True, lang='en') # need to run only once to download and load model into memory
img_path = './imgs_en/img_12.jpg'
result = ocr.ocr(img_path, cls=True)
for line in result:
    print(line)


# draw result
from PIL import Image
image = Image.open(img_path).convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
im_show = draw_ocr(image, boxes, txts, scores, font_path='./fonts/simfang.ttf')
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')
```

Output will be a list, each item contains bounding box, text and recognition confidence

```bash
[[[441.0, 174.0], [1166.0, 176.0], [1165.0, 222.0], [441.0, 221.0]], ('ACKNOWLEDGEMENTS', 0.9971134662628174)]
  [[[403.0, 346.0], [1204.0, 348.0], [1204.0, 384.0], [402.0, 383.0]], ('We would like to thank all the designers and', 0.9761400818824768)]
  [[[403.0, 396.0], [1204.0, 398.0], [1204.0, 434.0], [402.0, 433.0]], ('contributors who have been involved in the', 0.9791957139968872)]
  ......
```

Visualization of results

<div align="center">
    <img src="../imgs_results/whl/12_det_rec.jpg" width="800">
</div>


<a name="3"></a>

## 3. Summary

In this section, you have mastered the use of PaddleOCR whl package.

PaddleOCR is a rich and practical OCR tool library that get through the whole process of data production, model training, compression, inference and deployment, please refer to the [tutorials](../../README.md#tutorials) to start the journey of PaddleOCR.