Namespace OpenCvSharp.Dnn
Classes
- ClassificationModel
This class represents high-level API for classification models. ClassificationModel allows to set params for preprocessing input image. ClassificationModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return top-1 prediction.
- DetectionModel
This class represents high-level API for object detection networks. DetectionModel allows to set params for preprocessing input image. DetectionModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return result detections.
- Image2BlobParams
Processing params of image to blob. It includes all possible image processing operations and corresponding parameters.
- KeypointsModel
This class represents high-level API for keypoints models. KeypointsModel allows to set params for preprocessing input image. KeypointsModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and returns the x and y coordinates of each detected keypoint.
- Layer
This interface class allows to build new Layers - are building blocks of networks.
- Model
This class is presented high-level API for neural networks. It allows to set params for preprocessing input image. It creates net from file with trained weights and config, sets preprocessing input and runs forward pass.
- Net
Base class for objects that own a single native OpenCV pointer through an OpenCvSafeHandle. The SafeHandle is the single source of truth for the native handle value and is responsible for releasing it (including from its own finalizer when the managed object is dropped without Dispose()).
- SegmentationModel
This class represents high-level API for segmentation models. SegmentationModel allows to set params for preprocessing input image. SegmentationModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and returns the class prediction for each pixel.
- TextDetectionModel
Base class for text detection networks. This is an abstract base; use TextDetectionModelEAST or TextDetectionModelDB.
- TextDetectionModelDB
This class represents high-level API for text detection DL networks compatible with DB model.
- TextDetectionModelEAST
This class represents high-level API for text detection DL networks compatible with EAST model.
- TextRecognitionModel
This class represents high-level API for text recognition networks. TextRecognitionModel allows to set params for preprocessing input image. TextRecognitionModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return recognition result. For TextRecognitionModel, CRNN-CTC is supported.
- Tokenizer
Tokenizer for LLM / VLM text (OpenCV 5). Provides a simple API to encode text to token ids and decode token ids back to text (BPE, e.g. gpt2 / gpt4 families).
Enums
- Backend
Enum of computation backends supported by layers.
- EngineType
Enum of DNN inference engines that can be selected when reading a network (OpenCV 5).
- ImagePaddingMode
Enum of image processing mode. To facilitate the specialization pre-processing requirements of the dnn model. For example, the letter box often used in the Yolo series of models.
- ModelFormat
Enum of the original framework format a Net was loaded from.
- ProfilingMode
Profiling mode for the new DNN engine (OpenCV 5). See Net.ProfilingMode.
- SoftNMSMethod
Enum of Soft NMS methods.
- Target
Enum of target devices for computations.
- TracingMode
Tracing mode for the new DNN engine (OpenCV 5). See Net.TracingMode.