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| struct | CelanturDetection |
| | Structure to hold information about a detection made by the Celantur SDK. More...
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| class | ModelCompileException |
| | Exception class for errors during model compilation. This exception is thrown when there are issues encountered while compiling a machine learning model. More...
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| class | LicensingException |
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| class | ModelLoadException |
| | Exception class for errors during model loading. This exception is thrown when there are issues encountered while loading a machine learning model. More...
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| class | DimensionMismatchException |
| | Exception class for dimension mismatches. This exception is thrown when there is a mismatch in expected dimensions, such as input size or tensor shapes. More...
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| class | WrongConfig |
| | Exception that is getting thrown in case the user tries to set wrong configuration for the processor, for example, if the detection type is lower than the blur type. More...
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| struct | DetectionProcessingConfig |
| | Configuration that describes processing of a particular class This structure contains the type of blurring to be applied to detections of a specific class. More...
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| struct | ProcessorParams |
| | Structure to hold parameters for the image processor. This structure contains various settings for configuring the image processing. More...
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| struct | ImageMetadata |
| | Metadata associated with an image or frame. for now, just a placeholder. More...
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| struct | FrameMetadata |
| | Metadata associated with a video frame. for now, just a placeholder. More...
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| struct | MatContainer |
| | Container for an image and its associated metadata. for now, just a placeholder. More...
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| struct | MinOptMaxDims |
| | A tuple representing minimum, optimal, and maximum dimensions. This tuple is used to specify the range of dimensions for model optimization. The three integers represent the minimum, optimal, and maximum dimensions respectively. More...
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| struct | ModelThresholds |
| | Structure to hold model threshold values for different object classes. This structure contains threshold values for detecting faces, license plates, persons, and vehicles. Class ids are identical to the celantur container. More...
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| struct | CPUInfo |
| | Structure to hold CPU information. More...
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| struct | Dims |
| | Structure to hold dimensions information. This structure contains the name, number of dimensions, dimension sizes, and whether it is an input dimension. More...
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| struct | ExifMetadata |
| | Structure to manage EXIF metadata for images. This structure encapsulates EXIF data and provides methods to manipulate and retrieve information from it. It is used in conjunction with JPEG encoding and decoding functions to preserve image metadata. More...
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| enum class | DetectionType { Auto = 0
, None = 1
, BBox = 2
, Segmentation = 3
} |
| | Enum to describe the detection type in celantur::DetectionProcessingConfig. More...
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| enum class | BlurType { None = 0
, BBox_Oval = 1
, BBox_Rectangle = 2
, Segmentation = 3
} |
| | Enum to describe the blur in celantur::DetectionProcessingConfig. More...
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| enum class | CelanturClassId { LicensePlate = 101
, Person = 102
, Face = 103
, Vehicle = 104
} |
| | Class ids enum that is used in celantur::CelanturDetection and celantur::DetectionProcessingConfig to describe detection class Class ids are identical to the celantur container. More...
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| enum class | Rotation { None = 0
, Rotated90Clockwise = 1
, Rotated180 = 2
, Rotated90CounterClockwise = 3
} |
| | Enum to represent image rotation states. is used in celantur::FrameMetadata to describe the rotation of the frame. More...
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| enum class | OptimisationLevel { Low
, Medium
, Full
} |
| | Enumeration for different levels of optimization. This enum is used to specify the desired level of optimization during model compilation. More...
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| enum class | CompilePrecision { FP32
, FP16
, INT8
} |
| | Enumeration for different precision levels during model compilation. This enum is used to specify the desired precision for model weights and computations. Most engines support only FP32. Currently, only TensorRT supports FP16. INT8 is supported by TensorRT and OpenVINO, but requires special model provided to you by Celantur. More...
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| enum class | LogSeverity { Error
, Warning
, Debug
} |
| | Enumeration for different log severity levels. More...
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| std::ostream & | operator<< (std::ostream &os, const celantur::BlurType &blur_type) |
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| std::istream & | operator>> (std::istream &os, celantur::BlurType &blur_type) |
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| std::ostream & | operator<< (std::ostream &os, const celantur::DetectionType &blur_type) |
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| std::istream & | operator>> (std::istream &os, celantur::DetectionType &blur_type) |
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| std::ostream & | operator<< (std::ostream &os, const celantur::CelanturClassId &id) |
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| std::istream & | operator>> (std::istream &os, celantur::CelanturClassId &id) |
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| std::istream & | operator>> (std::istream &in, celantur::OptimisationLevel &opt_level) |
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| std::ostream & | operator<< (std::ostream &out, const celantur::OptimisationLevel &opt_level) |
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| std::istream & | operator>> (std::istream &in, celantur::CompilePrecision &precision) |
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| std::ostream & | operator<< (std::ostream &out, const celantur::CompilePrecision &precision) |
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| std::istream & | operator>> (std::istream &in, celantur::MinOptMaxDims &dims) |
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| std::ostream & | operator<< (std::ostream &out, const celantur::MinOptMaxDims &dims) |
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| std::istream & | operator>> (std::istream &in, celantur::InferenceEnginePluginId &plugin_id) |
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| std::ostream & | operator<< (std::ostream &out, const celantur::InferenceEnginePluginId &plugin_id) |
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| std::istream & | operator>> (std::istream &in, celantur::LogSeverity &log_severity) |
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| std::ostream & | operator<< (std::ostream &out, const celantur::LogSeverity &log_severity) |
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| CPUInfo | get_cpu_info () |
| | Function to retrieve CPU information. More...
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| void | serialise_image_metrics_to_json (cv::Mat image, std::vector< CelanturDetection > detections, std::string image_name, std::string input_folder, std::ostream &os) |
| | serialise detections to JSON format. Is identical to the celantur-container functionality. More...
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| std::vector< CelanturDetection > | deserialise_image_metrics_from_json (std::string_view is) |
| | Construct detections vector from the JSON string. More...
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| std::vector< CelanturDetection > | filter_detections_by_threshold (const std::vector< CelanturDetection > &detections, const ModelThresholds &thresholds) |
| | Filter detections based on confidence thresholds for different object classes. This function takes a vector of CelanturDetection objects and filters them according to the specified thresholds for each class. More...
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| std::vector< CelanturDetection > | filter_detections_by_class_name (const std::vector< CelanturDetection > &detections, const std::set< std::string > &classes) |
| | Filter detections based on a set of class names. This function takes a vector of CelanturDetection objects and filters them to include only those whose class names are present in the provided set. More...
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| std::vector< CelanturDetection > | filter_detections_by_class (const std::vector< CelanturDetection > &detections, const std::set< CelanturClassId > &classes) |
| | Filter detections by type. This function takes a vector of CelanturDetection objects and filters them to include only those whose class IDs are present in the provided set. More...
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| cv::Mat | generate_binary_mask (const cv::Size &image_size, const std::vector< CelanturDetection > &detections, PerTypeProcessingConfig config) |
| | Generate a binary mask for a specific class from detections. This function creates a binary mask image where pixels corresponding to the specified class in the detections are set to 255 (white) and all other pixels are set to 0 (black). More...
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| cv::Mat | visualise_detections (const cv::Mat image, std::vector< CelanturDetection > detections) |
| | Visualise detections on an image. This function takes an input image and a vector of CelanturDetection objects, and draws bounding boxes and class labels on the image to visualize the detections. Can be used for debug purposes. More...
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| std::string | detection_to_yolo_repr (const CelanturDetection &detection, const cv::Size &image_size) |
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| std::string | detections_to_yolo_repr (const std::vector< CelanturDetection > &detections, const cv::Size &image_size) |
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| std::vector< unsigned char > | jpeg_encode (cv::Mat image, int jpeg_quality=95, std::optional< ExifMetadata > exif_metadata=std::nullopt) |
| | Encode an image to JPEG format with optional EXIF metadata. This function compresses the input image to JPEG format, allowing specification of JPEG quality and embedding of EXIF metadata if provided. More...
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| cv::Mat | jpeg_decode (const unsigned char *data, size_t size) |
| | Decode a JPEG image from a byte array. This function takes a byte array containing JPEG-encoded data and decodes it into an OpenCV cv::Mat image. More...
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| cv::Mat | jpeg_decode (std::vector< unsigned char > data) |
| | Decode a JPEG image from a vector of bytes. More...
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| ExifMetadata | jpeg_get_exif_metadata (const unsigned char *data, size_t size) |
| | Extract EXIF metadata from a JPEG byte array. This function parses the EXIF metadata from a JPEG image provided as a byte array and returns it as an ExifMetadata object. More...
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| cv::Mat | rotate_image (const cv::Mat &image, int orientation) |
| | Rotate an image based on EXIF orientation. This function rotates the input image according to the specified EXIF orientation value, ensuring correct display orientation. More...
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