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115 lines
6.5 KiB
Markdown
115 lines
6.5 KiB
Markdown
---
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typora-copy-images-to: images
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comments: true
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hide:
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---
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# Android Demo
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## 1. Introduction
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This document describes the [Android Demo](https://github.com/PaddlePaddle/PaddleOCR/tree/main/deploy/android_demo) for PaddleOCR. The demo currently supports text detection, text direction classification, and text recognition models. It is developed using [PaddleLite v2.10](https://github.com/PaddlePaddle/Paddle-Lite/tree/release/v2.10).
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## 2. Recent Updates
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- **February 27, 2022**
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- Updated the prediction library to PaddleLite v2.10.
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- Added support for six operation modes:
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- Detection + Classification + Recognition
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- Detection + Recognition
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- Classification + Recognition
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- Detection
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- Recognition
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- Classification
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## 3. Quick Start
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### 3.1 Environment Setup
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1. **Install Android Studio:**
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Download and install Android Studio on your development machine. For detailed instructions, please refer to the [Android Studio official website](https://developer.android.com/studio).
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2. **Prepare Your Android Device:**
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Ensure that you have an Android phone and enable USB debugging. To do so, navigate to:
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**Settings → Developer Options → Enable Developer Options and USB Debugging.**
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**Note:** If your Android Studio installation does not have the NDK configured, please follow the [Install and Configure NDK and CMake](https://developer.android.com/studio/projects/install-ndk) guide. You may choose the latest NDK version or use the same version as the PaddleLite prediction library.
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### 3.2 Importing the Project
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1. In Android Studio, select **File → New → Import Project…** and follow the wizard to import the project.
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2. Upon successful import, your project interface should resemble the following:
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[](./images/import_demo.jpg)
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### 3.3 Running the Demo
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1. Connect your Android device to your computer.
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2. Click the **Run** button in the Android Studio toolbar.
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- Your device may prompt you with "Allow installation of software from USB." Click **Allow**.
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3. Once the installation is complete, the app icon will appear on the last page of your home screen.
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4. Tap the app icon to launch the application. The home page will display as shown below:
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On the home screen, you will find the following elements:
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- **Run Model:** Executes the model(s) using the selected operation mode.
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- **Take Photo for Recognition:** Activates the device camera to capture an image. After taking a photo, tap **Run Model** to perform recognition.
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- **Select Image:** Opens the photo gallery to select an image. After selection, tap **Run Model** to perform recognition.
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- **Clear Drawing:** Clears any drawn text boxes from the currently displayed image.
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- **Dropdown List:** Allows you to choose one of the six supported operation modes. The default mode is **Detection + Classification + Recognition**.
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- **Menu Button:** Opens the settings interface for configurations related to the models and built-in images.
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When you tap **Run Model**, the demo executes the corresponding model(s) in your selected mode. For example, in **Detection + Classification + Recognition** mode, the output appears as follows:
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<img src="./images/run_det_cls_rec.jpg" width="400">
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The status display area shows the current model status (e.g., `run model succeeded`), indicating that the model ran successfully. The recognition results are formatted as follows:
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```text
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Serial Number: Det: (x1,y1)(x2,y2)(x3,y3)(x4,y4) Rec: Recognized Text, Confidence Score Cls: Classification Label, Classification Score
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```
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### 3.4 Operation Modes
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The PaddleOCR demo supports six operation modes, shown in the illustration below:
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The expected output for each mode is as follows:
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| **Detection + Classification + Recognition** | **Detection + Recognition** | **Classification + Recognition** |
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|----------------------------------------------------------------------------------|--------------------------------------------------------|--------------------------------------------------------|
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| <img src="./images/run_det_cls_rec-20240806100407184.jpg" width="400"> | <img src="./images/run_det_rec.jpg" width="400"> | <img src="./images/run_cls_rec.jpg" width="400"> |
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| **Detection** | **Recognition** | **Classification** |
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|--------------------------------------------------------------------------------|--------------------------------------------------------|--------------------------------------------------------|
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| <img src="./images/run_det.jpg" width="400"> | <img src="./images/run_rec.jpg" width="400"> | <img src="./images/run_cls.jpg" width="400"> |
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### 3.5 Settings
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The settings interface allows you to customize the following parameters:
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1. **General Settings**
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- **Enable Custom Settings:** Check this box to allow modifications.
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- **Model Path:** The file path to the model (use the default value unless necessary).
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- **Label Path:** The dictionary file for the text recognition model.
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- **Image Path:** The filename of the built-in image used for recognition.
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2. **Model Runtime Settings:** (Changes here trigger an automatic model reload when returning to the main interface.)
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- **CPU Thread Number:** The number of CPU cores allocated for model inference.
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- **CPU Power Mode:** Defines the model’s execution strategy, corresponding to different core configurations.
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3. **Input Settings**
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- **det long size:** The target value for the longer side of the image during DB model preprocessing. If the image's long side exceeds this value, it will be resized proportionally; if it is shorter, no resizing is applied.
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4. **Output Settings**
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- **Score Threshold:** The minimum score threshold for detection boxes in DB model post-processing. Boxes scoring below this threshold are filtered out and not displayed.
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## 4. Further Support
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For additional support and updates:
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1. Refer to the [Paddle-Lite Demo for OCR](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/ocr/android/app/cxx/ppocr_demo) for real-time recognition and prediction library updates.
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2. Visit the [PaddleLite repository](https://github.com/PaddlePaddle/Paddle-Lite) for more development support and community discussions.
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