Explore DeepSeek AI's DeepSeek-OCR, a revolutionary approach to compressing long text contexts.

## Case Description This is a text recognition case implemented based on AI basic vision services. It captures photos through the device camera and then recognizes the text content in the images. ## Implementation Steps: ### 1. Module Import // Import functional modules import { camera, cameraPicker } from '@kit.CameraKit'; import { fileIo } from '@kit.CoreFileKit'; import image from '@ohos.multimedia.image'; import { textRecognition } from '@kit.CoreVisionKit'; ### 2. Camera Call and Image Acquisition // Create a camera picker instance const res = await cameraPicker.pick(getContext(), [ cameraPicker.PickerMediaType.PHOTO ], { cameraPosition: camera.CameraPosition.CAMERA_POSITION_BACK }); // Get the URI of the captured image const imageUri = res.resultUri; ### 3. Image Processing Flow // Convert the image to a recognizable pixel map const fileSource = await fileIo.open(imageUri, fileIo.OpenMode.READ_ONLY); const imageSource = image.createImageSource(fileSource.fd); const pixelMap = await imageSource.createPixelMap(); ### 4. Core Implementation of Text Recognition // Configure visual recognition parameters let visionInfo: textRecognition.VisionInfo = { pixelMap: pixelMap }; // Execute text recognition and get the result const recognitionResult = await textRecognition.recognizeText(visionInfo); this.text = recognitionResult.value; ### 5. Interface Construction and Interaction @Entry @Component struct TextRecognition { @State text: string = ''; // Button click event handler async openCamera() { // Integrate the complete call logic of the above steps } build() { Column() { Button('Take Photo and Recognize Text') .onClick(() => this.openCamera()) Text(this.text) .fontSize(20) .margin(10) } .padding(20) } } ### 2. Complete Business Logic Integrate the complete call flow of each functional module. ## Summary: ### Key Points 1. Camera calls require device permissions and hardware support. 2. Image conversion ensures compatibility with different image formats. 3. The text recognition interface returns structured recognition results. ### Complete Code // Keep the original code intact and only add explanatory comments import { camera, cameraPicker } from '@kit.CameraKit'; import { fileIo } from '@kit.CoreFileKit'; import image from '@ohos.multimedia.image'; import { textRecognition } from '@kit.CoreVisionKit'; @Entry @Component struct TextRecognition { @State text: string = ''; // Main function method: integrate camera call and text recognition async openCamera() { // Step 1: Call the camera to take a photo const res = await cameraPicker.pick(getContext(), [cameraPicker.PickerMediaType.PHOTO], { cameraPosition: camera.CameraPosition.CAMERA_POSITION_BACK }) // Step 2: Check the availability of OCR capabilities // Use the canIUse interface to detect whether the device supports text recognition capabilities if (canIUse('SystemCapability.AI.OCR.TextRecognition')) { // Step 3: Process the image file const fileSource = await fileIo.open(res.resultUri, fileIo.OpenMode.READ_ONLY); const imageSource = image.createImageSource(fileSource.fd); const chooseImage = await imageSource.createPixelMap(); // Step 4: Execute text recognition let visionInfo: textRecognition.VisionInfo = { pixelMap: chooseImage }; const data = await textRecognition.recognizeText(visionInfo); // Update the recognition result to the interface this.text = data.value } } // UI layout build() { Column() { Button('Take Photo and Recognize Text') .onClick(() => { this.openCamera() }) Text(this.text) .fontSize(20) .margin(10) } .height('100%') .width('100%') } }