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Oleksandr Bezdieniezhnykh
b6b6751c37
put tile size to name and set it dynamically for AI recognition
62 lines
2.3 KiB
Cython
62 lines
2.3 KiB
Cython
from msgpack import unpackb
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cdef class AIRecognitionConfig:
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def __init__(self,
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frame_period_recognition,
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frame_recognition_seconds,
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probability_threshold,
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tracking_distance_confidence,
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tracking_probability_increase,
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tracking_intersection_threshold,
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file_data,
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paths,
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model_batch_size,
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big_image_tile_overlap_percent,
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tile_size
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):
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self.frame_period_recognition = frame_period_recognition
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self.frame_recognition_seconds = frame_recognition_seconds
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self.probability_threshold = probability_threshold
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self.tracking_distance_confidence = tracking_distance_confidence
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self.tracking_probability_increase = tracking_probability_increase
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self.tracking_intersection_threshold = tracking_intersection_threshold
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self.file_data = file_data
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self.paths = paths
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self.model_batch_size = model_batch_size
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self.big_image_tile_overlap_percent = big_image_tile_overlap_percent
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self.tile_size = tile_size
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def __str__(self):
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return (f'frame_seconds : {self.frame_recognition_seconds}, distance_confidence : {self.tracking_distance_confidence}, '
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f'probability_increase : {self.tracking_probability_increase}, '
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f'intersection_threshold : {self.tracking_intersection_threshold}, '
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f'frame_period_recognition : {self.frame_period_recognition}, '
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f'big_image_tile_overlap_percent: {self.big_image_tile_overlap_percent}, '
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f'paths: {self.paths}, '
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f'model_batch_size: {self.model_batch_size}')
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@staticmethod
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cdef from_msgpack(bytes data):
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unpacked = unpackb(data, strict_map_key=False)
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return AIRecognitionConfig(
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unpacked.get("f_pr", 0),
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unpacked.get("f_rs", 0.0),
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unpacked.get("pt", 0.0),
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unpacked.get("t_dc", 0.0),
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unpacked.get("t_pi", 0.0),
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unpacked.get("t_it", 0.0),
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unpacked.get("d", b''),
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unpacked.get("p", []),
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unpacked.get("m_bs"),
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unpacked.get("ov_p", 20),
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unpacked.get("tile_size", 550),
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) |