from msgpack import unpackb cdef class AIRecognitionConfig: def __init__(self, frame_period_recognition, frame_recognition_seconds, probability_threshold, tracking_distance_confidence, tracking_probability_increase, tracking_intersection_threshold, file_data, paths, model_batch_size, big_image_tile_overlap_percent, altitude, focal_length, sensor_width ): self.frame_period_recognition = frame_period_recognition self.frame_recognition_seconds = frame_recognition_seconds self.probability_threshold = probability_threshold self.tracking_distance_confidence = tracking_distance_confidence self.tracking_probability_increase = tracking_probability_increase self.tracking_intersection_threshold = tracking_intersection_threshold self.file_data = file_data self.paths = paths self.model_batch_size = model_batch_size self.big_image_tile_overlap_percent = big_image_tile_overlap_percent self.altitude = altitude self.focal_length = focal_length self.sensor_width = sensor_width def __str__(self): return (f'frame_seconds : {self.frame_recognition_seconds}, distance_confidence : {self.tracking_distance_confidence}, ' f'probability_increase : {self.tracking_probability_increase}, ' f'intersection_threshold : {self.tracking_intersection_threshold}, ' f'frame_period_recognition : {self.frame_period_recognition}, ' f'big_image_tile_overlap_percent: {self.big_image_tile_overlap_percent}, ' f'paths: {self.paths}, ' f'model_batch_size: {self.model_batch_size}, ' f'altitude: {self.altitude}, ' f'focal_length: {self.focal_length}, ' f'sensor_width: {self.sensor_width}' ) @staticmethod cdef from_msgpack(bytes data): unpacked = unpackb(data, strict_map_key=False) return AIRecognitionConfig( unpacked.get("f_pr", 0), unpacked.get("f_rs", 0.0), unpacked.get("pt", 0.0), unpacked.get("t_dc", 0.0), unpacked.get("t_pi", 0.0), unpacked.get("t_it", 0.0), unpacked.get("d", b''), unpacked.get("p", []), unpacked.get("m_bs"), unpacked.get("ov_p", 20), unpacked.get("cam_a", 400), unpacked.get("cam_fl", 24), unpacked.get("cam_sw", 23.5) ) @staticmethod def from_dict(dict data): return AIRecognitionConfig( data.get("frame_period_recognition", 4), data.get("frame_recognition_seconds", 2), data.get("probability_threshold", 0.25), data.get("tracking_distance_confidence", 0.0), data.get("tracking_probability_increase", 0.0), data.get("tracking_intersection_threshold", 0.6), data.get("file_data", b''), data.get("paths", []), data.get("model_batch_size", 1), data.get("big_image_tile_overlap_percent", 20), data.get("altitude", 400), data.get("focal_length", 24), data.get("sensor_width", 23.5) )