WeChat QRCode includes two CNN-based models: A object detection model and a super resolution model. Object detection model is applied to detect QRCode with the bounding box. super resolution model is applied to zoom in QRCode when it is small.
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IntPtr | getNativeObjAddr () |
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| WeChatQRCode (string detector_prototxt_path, string detector_caffe_model_path, string super_resolution_prototxt_path, string super_resolution_caffe_model_path) |
| Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
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| WeChatQRCode (string detector_prototxt_path, string detector_caffe_model_path, string super_resolution_prototxt_path) |
| Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
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| WeChatQRCode (string detector_prototxt_path, string detector_caffe_model_path) |
| Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
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| WeChatQRCode (string detector_prototxt_path) |
| Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
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| WeChatQRCode () |
| Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
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List< string > | detectAndDecode (Mat img, List< Mat > points) |
| Both detects and decodes QR code. To simplify the usage, there is a only API: detectAndDecode.
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List< string > | detectAndDecode (Mat img) |
| Both detects and decodes QR code. To simplify the usage, there is a only API: detectAndDecode.
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void | setScaleFactor (float _scalingFactor) |
| set scale factor QR code detector use neural network to detect QR. Before running the neural network, the input image is pre-processed by scaling. By default, the input image is scaled to an image with an area of 160000 pixels. The scale factor allows to use custom scale the input image: width = scaleFactor*width height = scaleFactor*width
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float | getScaleFactor () |
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void | Dispose () |
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void | ThrowIfDisposed () |
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WeChat QRCode includes two CNN-based models: A object detection model and a super resolution model. Object detection model is applied to detect QRCode with the bounding box. super resolution model is applied to zoom in QRCode when it is small.
◆ WeChatQRCode() [1/5]
OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.WeChatQRCode |
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string | detector_prototxt_path, |
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string | detector_caffe_model_path, |
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string | super_resolution_prototxt_path, |
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string | super_resolution_caffe_model_path ) |
Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
- Parameters
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detector_prototxt_path | prototxt file path for the detector |
detector_caffe_model_path | caffe model file path for the detector |
super_resolution_prototxt_path | prototxt file path for the super resolution model |
super_resolution_caffe_model_path | caffe file path for the super resolution model |
◆ WeChatQRCode() [2/5]
OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.WeChatQRCode |
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string | detector_prototxt_path, |
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string | detector_caffe_model_path, |
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string | super_resolution_prototxt_path ) |
Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
- Parameters
-
detector_prototxt_path | prototxt file path for the detector |
detector_caffe_model_path | caffe model file path for the detector |
super_resolution_prototxt_path | prototxt file path for the super resolution model |
super_resolution_caffe_model_path | caffe file path for the super resolution model |
◆ WeChatQRCode() [3/5]
OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.WeChatQRCode |
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string | detector_prototxt_path, |
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string | detector_caffe_model_path ) |
Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
- Parameters
-
detector_prototxt_path | prototxt file path for the detector |
detector_caffe_model_path | caffe model file path for the detector |
super_resolution_prototxt_path | prototxt file path for the super resolution model |
super_resolution_caffe_model_path | caffe file path for the super resolution model |
◆ WeChatQRCode() [4/5]
OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.WeChatQRCode |
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string | detector_prototxt_path | ) |
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Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
- Parameters
-
detector_prototxt_path | prototxt file path for the detector |
detector_caffe_model_path | caffe model file path for the detector |
super_resolution_prototxt_path | prototxt file path for the super resolution model |
super_resolution_caffe_model_path | caffe file path for the super resolution model |
◆ WeChatQRCode() [5/5]
OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.WeChatQRCode |
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Initialize the WeChatQRCode. It includes two models, which are packaged with caffe format. Therefore, there are prototxt and caffe models (In total, four paramenters).
- Parameters
-
detector_prototxt_path | prototxt file path for the detector |
detector_caffe_model_path | caffe model file path for the detector |
super_resolution_prototxt_path | prototxt file path for the super resolution model |
super_resolution_caffe_model_path | caffe file path for the super resolution model |
◆ __fromPtr__()
static WeChatQRCode OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.__fromPtr__ |
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IntPtr | addr | ) |
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◆ detectAndDecode() [1/2]
List< string > OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.detectAndDecode |
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Mat | img | ) |
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Both detects and decodes QR code. To simplify the usage, there is a only API: detectAndDecode.
- Parameters
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img | supports grayscale or color (BGR) image. |
points | optional output array of vertices of the found QR code quadrangle. Will be empty if not found. |
- Returns
- list of decoded string.
◆ detectAndDecode() [2/2]
List< string > OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.detectAndDecode |
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Mat | img, |
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List< Mat > | points ) |
Both detects and decodes QR code. To simplify the usage, there is a only API: detectAndDecode.
- Parameters
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img | supports grayscale or color (BGR) image. |
points | optional output array of vertices of the found QR code quadrangle. Will be empty if not found. |
- Returns
- list of decoded string.
◆ Dispose()
override void OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.Dispose |
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bool | disposing | ) |
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protectedvirtual |
◆ getNativeObjAddr()
IntPtr OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.getNativeObjAddr |
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◆ getScaleFactor()
float OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.getScaleFactor |
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◆ setScaleFactor()
void OpenCVForUnity.Wechat_qrcodeModule.WeChatQRCode.setScaleFactor |
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float | _scalingFactor | ) |
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set scale factor QR code detector use neural network to detect QR. Before running the neural network, the input image is pre-processed by scaling. By default, the input image is scaled to an image with an area of 160000 pixels. The scale factor allows to use custom scale the input image: width = scaleFactor*width height = scaleFactor*width
scaleFactor valuse must be > 0 and <= 1, otherwise the scaleFactor value is set to -1 and use default scaled to an image with an area of 160000 pixels.
The documentation for this class was generated from the following file:
- OpenCVForUnity/Assets/OpenCVForUnity/org/opencv_contrib/wechat_qrcode/WeChatQRCode.cs