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135 lines
4.3 KiB
135 lines
4.3 KiB
import os
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import subprocess
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from cffi import FFI
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from common.basedir import BASEDIR
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# Initialize visiontest. Ignore output.
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_visiond_dir = os.path.dirname(os.path.abspath(__file__))
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_libvisiontest = "libvisiontest.so"
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try: # bacause this crashes somtimes when running pipeline
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subprocess.check_output(["make", "-C", _visiond_dir, "-f",
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os.path.join(_visiond_dir, "visiontest.mk"),
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_libvisiontest])
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except:
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pass
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class VisionTest():
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"""A version of the vision model that can be run on a desktop.
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WARNING: This class is not thread safe. VisionTest objects cannot be
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created or used on multiple threads simultaneously.
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"""
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ffi = FFI()
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ffi.cdef("""
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typedef unsigned char uint8_t;
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struct VisionTest;
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typedef struct VisionTest VisionTest;
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VisionTest* visiontest_create(int temporal_model, int disable_model,
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int input_width, int input_height,
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int model_input_width, int model_input_height);
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void visiontest_destroy(VisionTest* visiontest);
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void visiontest_transform(VisionTest* vt, const uint8_t* yuv_data,
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uint8_t* out_y, uint8_t* out_u, uint8_t* out_v,
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const float* transform);
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""")
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clib = ffi.dlopen(os.path.join(_visiond_dir, _libvisiontest))
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def __init__(self, input_size, model_input_size, model):
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"""Create a wrapper around visiond for off-device python code.
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Inputs:
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input_size: The size of YUV images passed to transform.
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model_input_size: The size of YUV images passed to the model.
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model: The name of the model to use. "temporal", "yuv", or None to disable the
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model (used to disable OpenCL).
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"""
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self._input_size = input_size
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self._model_input_size = model_input_size
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if model is None:
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disable_model = 1
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temporal_model = 0
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elif model == "yuv":
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disable_model = 0
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temporal_model = 0
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elif model == "temporal":
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disable_model = 0
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temporal_model = 1
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else:
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raise ValueError("Bad model name: {}".format(model))
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prevdir = os.getcwd()
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os.chdir(_visiond_dir) # tmp hack to find kernels
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os.environ['BASEDIR'] = BASEDIR
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self._visiontest_c = self.clib.visiontest_create(
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temporal_model, disable_model, self._input_size[0], self._input_size[1],
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self._model_input_size[0], self._model_input_size[1])
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os.chdir(prevdir)
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@property
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def input_size(self):
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return self._input_size
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@property
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def model_input_size(self):
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return self._model_input_size
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def transform(self, yuv_data, transform):
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y_len = self.model_input_size[0] * self.model_input_size[1]
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t_y_ptr = bytearray(y_len)
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t_u_ptr = bytearray(y_len // 4)
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t_v_ptr = bytearray(y_len // 4)
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self.transform_output_buffer(yuv_data, t_y_ptr, t_u_ptr, t_v_ptr,
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transform)
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return t_y_ptr, t_u_ptr, t_v_ptr
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def transform_contiguous(self, yuv_data, transform):
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y_ol = self.model_input_size[0] * self.model_input_size[1]
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uv_ol = y_ol // 4
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result = bytearray(y_ol * 3 // 2)
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result_view = memoryview(result)
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t_y_ptr = result_view[:y_ol]
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t_u_ptr = result_view[y_ol:y_ol + uv_ol]
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t_v_ptr = result_view[y_ol + uv_ol:]
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self.transform_output_buffer(yuv_data, t_y_ptr, t_u_ptr, t_v_ptr,
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transform)
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return result
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def transform_output_buffer(self, yuv_data, y_out, u_out, v_out,
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transform):
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assert len(yuv_data) == self.input_size[0] * self.input_size[1] * 3/2
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cast = self.ffi.cast
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from_buffer = self.ffi.from_buffer
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yuv_ptr = cast("unsigned char*", from_buffer(yuv_data))
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transform_ptr = self.ffi.new("float[]", transform)
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y_out_ptr = cast("unsigned char*", from_buffer(y_out))
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u_out_ptr = cast("unsigned char*", from_buffer(u_out))
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v_out_ptr = cast("unsigned char*", from_buffer(v_out))
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self.clib.visiontest_transform(self._visiontest_c, yuv_ptr, y_out_ptr,
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u_out_ptr, v_out_ptr, transform_ptr)
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def close(self):
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self.clib.visiontest_destroy(self._visiontest_c)
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self._visiontest_c = None
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def __enter__(self):
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return self
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def __exit__(self, type, value, traceback):
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self.close()
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if __name__ == "__main__":
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VisionTest((560, 304), (320, 160), "temporal")
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