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authorFreeArtMan <dos21h@gmail.com>2021-04-01 08:46:27 +0100
committerFreeArtMan <dos21h@gmail.com>2021-04-01 08:46:27 +0100
commitcfa037e92da0a34f7919ce4ca9db2bd546995c93 (patch)
tree6e4ab4fb3ae1323b8e1d7ed677ed6dbc76a9bd61
parent7561f774958ea1d495036d9aadf59366bd3320b8 (diff)
downloadmd-content-cfa037e92da0a34f7919ce4ca9db2bd546995c93.tar.gz
md-content-cfa037e92da0a34f7919ce4ca9db2bd546995c93.zip
Swift OCR post
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-rw-r--r--md/writeup/swift_ocr_example.md77
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+++ b/md/writeup.md
@@ -29,6 +29,7 @@ title: Writeup page
[Linux hello world in Swift](writeup/linux_hello_world_in_swift.md)
[Running disk images in QEMU](writeup/running_disk_images_in_qemu.md)
[Mqueue IPC example](writeup/mqueue_ipc_example.md)
+[Swift OCR example](writeup/swift_ocr_example.md)
## Projects
diff --git a/md/writeup/swift_ocr_example.md b/md/writeup/swift_ocr_example.md
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+title:Swift OCR example
+keywords:swift,ocr,macos
+
+# Swift OCR example
+
+## Intro
+
+After getting new M1 whanted to try some fancy machine learning stuff that avaliable.
+Got inspired when seen new post on reddit about OCRImage tool realse. As
+it was written in Object-C https://www.turbozen.com/sourceCode/ocrImage/ ,so I
+decided that is good learning task to read the code and reimplement all in Swift.
+
+## OCR
+
+The whole working prototype can fit just in few lines of code. All you need to create
+is text recognition requester and handle that collect results. There is few example on
+apple doc page.
+
+```siwft
+func recognizeImageUrl(_ url:URL, _ error: Error?) {
+ var pieces:[TextPiece] = []
+ var err:NSError?
+
+ var textRequest = VNRecognizeTextRequest(completionHandler: recognizeTextHandler(request:error:))
+
+ var handler = VNImageRequestHandler(url: url)
+ do {
+ try handler.perform([textRequest])
+ } catch {
+ print("Cannot perform request error:\(error)")
+ }
+ }
+
+ func recognizeTextHandler(request: VNRequest, error: Error?) {
+ print("Start recognize handler")
+ guard let observations =
+ request.results as? [VNRecognizedTextObservation] else {
+ return
+ }
+
+ let recognizedStrings = observations.compactMap { observation in
+ // Return the string of the top VNRecognizedText instance.
+ return observation.topCandidates(1).first?.string
+ }
+ print("\(recognizedStrings)")
+ }
+```
+
+## Source code
+
+Example XCode project is located at http://git.main.lv/cgit.cgi/OCRImage.git/
+clone it and launch with XCode
+```bash
+git clone http://git.main.lv/cgit.cgi/OCRImage.git/
+```
+
+## Future developments
+
+Could be nice to add sorting text, and some option to import location of text to json file with coordinates.
+
+Drawing boxes around original image with detected text is next thing to add.
+
+And there is alot of things that could be added to make it full featured OCR software.
+
+
+
+## Links
+
+http://git.main.lv/cgit.cgi/OCRImage.git/
+https://www.turbozen.com/sourceCode/ocrImage/
+https://turbozen.com/sourceCode/ocrImage/ocrImage_src/
+https://developer.apple.com/documentation/vision/recognizing_text_in_images
+http://git.main.lv/cgit.cgi/OCRImage.git/tree/OCRImage/main.swift?h=main
+
+
+
+