mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 15:56:32 +00:00
Oleksandr Bezdieniezhnykh
2149cd6c08
- Dockerfile.jetson: JetPack 6.x L4T base image (aarch64), TensorRT and PyCUDA from apt - requirements-jetson.txt: derived from requirements.txt, no pip tensorrt/pycuda - docker-compose.jetson.yml: runtime: nvidia for NVIDIA Container Runtime - tensorrt_engine.pyx: convert_from_source accepts optional calib_cache_path; INT8 used when cache present, FP16 fallback; get_engine_filename encodes precision suffix to avoid engine cache confusion - inference.pyx: init_ai tries INT8 engine then FP16 on lookup; downloads calibration cache before conversion thread; passes cache path through to convert_from_source - constants_inf: add INT8_CALIB_CACHE_FILE constant - Unit tests for AC-3 (INT8 flag set when cache provided) and AC-4 (FP16 when no cache) Made-with: Cursor
31 lines
584 B
Cython
31 lines
584 B
Cython
cdef str CONFIG_FILE
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cdef str AI_ONNX_MODEL_FILE
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cdef str INT8_CALIB_CACHE_FILE
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cdef str CDN_CONFIG
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cdef str MODELS_FOLDER
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cdef int SMALL_SIZE_KB
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cdef str SPLIT_SUFFIX
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cdef double TILE_DUPLICATE_CONFIDENCE_THRESHOLD
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cdef int METERS_IN_TILE
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cdef log(str log_message)
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cdef logerror(str error)
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cdef format_time(long ms)
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cdef dict[int, AnnotationClass] annotations_dict
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cdef class AnnotationClass:
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cdef public int id
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cdef public str name
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cdef public str color
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cdef public int max_object_size_meters
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cdef enum WeatherMode:
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Norm = 0
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Wint = 20
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Night = 40
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