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Merge pull request #20547 from rogday:gdb_pretty_printer
* add gdb rpetty printer for cv::Mat * address review comments
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Using OpenCV with gcc and CMake {#tutorial_linux_gcc_cmake}
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===============================
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@prev_tutorial{tutorial_linux_install}
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@prev_tutorial{tutorial_linux_gdb_pretty_printer}
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@next_tutorial{tutorial_linux_eclipse}
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Using OpenCV with gdb-powered IDEs {#tutorial_linux_gdb_pretty_printer}
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=====================
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@prev_tutorial{tutorial_linux_install}
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@next_tutorial{tutorial_linux_gcc_cmake}
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| -: | :- |
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| Original author | Egor Smirnov |
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| Compatibility | OpenCV >= 4.0 |
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@tableofcontents
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# Capabilities {#tutorial_linux_gdb_pretty_printer_capabilities}
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This pretty-printer can show element type, `is_continuous`, `is_submatrix` flags and (possibly truncated) matrix. It is known to work in Clion, VS Code and gdb.
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![Clion example](images/example.png)
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# Installation {#tutorial_linux_gdb_pretty_printer_installation}
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Move into `opencv/samples/gdb/`. Place `mat_pretty_printer.py` in a convinient place, rename `gdbinit` to `.gdbinit` and move it into your home folder. Change 'source' line of `.gdbinit` to point to your `mat_pretty_printer.py` path.
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In order to check version of python bundled with your gdb, use the following commands from the gdb shell:
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python
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import sys
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print(sys.version_info)
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end
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If the version of python 3 installed in your system doesn't match the version in gdb, create a new virtual environment with the exact same version, install `numpy` and change the path to python3 in `.gdbinit` accordingly.
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# Usage {#tutorial_linux_gdb_pretty_printer_usage}
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The fields in a debugger prefixed with `view_` are pseudo-fields added for convinience, the rest are left as is.
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If you feel that the number of elements in truncated view is too low, you can edit `mat_pretty_printer.py` - `np.set_printoptions` controlls everything matrix display-related.
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Installation in Linux {#tutorial_linux_install}
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=====================
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@next_tutorial{tutorial_linux_gcc_cmake}
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@next_tutorial{tutorial_linux_gdb_pretty_printer}
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@ -6,6 +6,7 @@ Introduction to OpenCV {#tutorial_table_of_content_introduction}
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##### Linux
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- @subpage tutorial_linux_install
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- @subpage tutorial_linux_gdb_pretty_printer
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- @subpage tutorial_linux_gcc_cmake
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- @subpage tutorial_linux_eclipse
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23
samples/gdb/gdbinit
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samples/gdb/gdbinit
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set auto-load local-gdbinit on
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set print elements 0
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add-auto-load-safe-path /
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python
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# Update GDB's Python paths with the `sys.path` values of the local
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# Python installation, whether that is brew'ed Python, a virtualenv,
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# or another system python.
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# Convert GDB to interpret in Python
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import os, subprocess, sys
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# Execute a Python using the user's shell and pull out the sys.path (for site-packages)
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paths = subprocess.check_output('/usr/bin/python3 -c "import os,sys;print(os.linesep.join(sys.path).strip())"',shell=True).decode("utf-8").split()
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# Extend GDB's Python's search path
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sys.path.extend(paths)
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end
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source /your/path/to/mat_pretty_printer.py
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samples/gdb/mat_pretty_printer.py
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samples/gdb/mat_pretty_printer.py
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import gdb
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import numpy as np
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from enum import Enum
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np.set_printoptions(suppress=True) # prevent numpy exponential notation on print, default False
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# np.set_printoptions(threshold=sys.maxsize)
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def conv(obj, t):
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return gdb.parse_and_eval(f'({t})({obj})')
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def booli(obj):
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return conv(str(obj).lower(), 'bool')
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def stri(obj):
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s = f'"{obj}"'
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return conv(s.translate(s.maketrans('\n', ' ')), 'char*')
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class MagicValues(Enum):
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MAGIC_VAL = 0x42FF0000
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AUTO_STEP = 0
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CONTINUOUS_FLAG = 1 << 14
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SUBMATRIX_FLAG = 1 << 15
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class MagicMasks(Enum):
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MAGIC_MASK = 0xFFFF0000
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TYPE_MASK = 0x00000FFF
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DEPTH_MASK = 7
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class Depth(Enum):
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CV_8U = 0
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CV_8S = 1
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CV_16U = 2
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CV_16S = 3
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CV_32S = 4
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CV_32F = 5
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CV_64F = 6
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CV_16F = 7
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def create_enum(n):
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def make_type(depth, cn):
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return depth.value + ((cn - 1) << 3)
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defs = [(f'{depth.name}C{i}', make_type(depth, i)) for depth in Depth for i in range(1, n + 1)]
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return Enum('Type', defs)
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Type = create_enum(512)
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class Flags:
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def depth(self):
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return Depth(self.flags & MagicMasks.DEPTH_MASK.value)
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def dtype(self):
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depth = self.depth()
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ret = None
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if depth == Depth.CV_8U:
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ret = (np.uint8, 'uint8_t')
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elif depth == Depth.CV_8S:
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ret = (np.int8, 'int8_t')
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elif depth == Depth.CV_16U:
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ret = (np.uint16, 'uint16_t')
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elif depth == Depth.CV_16S:
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ret = (np.int16, 'int16_t')
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elif depth == Depth.CV_32S:
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ret = (np.int32, 'int32_t')
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elif depth == Depth.CV_32F:
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ret = (np.float32, 'float')
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elif depth == Depth.CV_64F:
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ret = (np.float64, 'double')
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elif depth == Depth.CV_16F:
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ret = (np.float16, 'float16')
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return ret
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def type(self):
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return Type(self.flags & MagicMasks.TYPE_MASK.value)
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def channels(self):
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return ((self.flags & (511 << 3)) >> 3) + 1
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def is_continuous(self):
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return (self.flags & MagicValues.CONTINUOUS_FLAG.value) != 0
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def is_submatrix(self):
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return (self.flags & MagicValues.SUBMATRIX_FLAG.value) != 0
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def __init__(self, flags):
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self.flags = flags
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def __iter__(self):
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return iter({
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'type': stri(self.type().name),
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'is_continuous': booli(self.is_continuous()),
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'is_submatrix': booli(self.is_submatrix())
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}.items())
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class Size:
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def __init__(self, ptr):
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self.ptr = ptr
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def dims(self):
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return int((self.ptr - 1).dereference())
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def to_numpy(self):
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return np.array([int(self.ptr[i]) for i in range(self.dims())], dtype=np.int64)
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def __iter__(self):
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return iter({'size': stri(self.to_numpy())}.items())
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class Mat:
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def __init__(self, m, size, flags):
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(dtype, ctype) = flags.dtype()
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elsize = np.dtype(dtype).itemsize
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ptr = m['data']
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dataptr = int(ptr)
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length = (int(m['dataend']) - dataptr) // elsize
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start = (int(m['datastart']) - dataptr) // elsize
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if length == 0:
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self.mat = np.array([])
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self.view = self.mat
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return
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if dtype != np.float16:
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ctype = gdb.lookup_type(ctype)
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ptr = ptr.cast(ctype.array(length - 1).pointer()).dereference()
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self.mat = np.array([ptr[i] for i in range(length)], dtype=dtype)
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else:
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u16 = gdb.lookup_type('uint16_t')
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ptr = ptr.cast(u16.array(length - 1).pointer()).dereference()
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self.mat = np.array([ptr[i] for i in range(length)], dtype=np.uint16)
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self.mat = self.mat.view(np.float16)
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steps = np.asarray([int(m['step']['p'][i]) for i in range(size.dims())], dtype=np.int64)
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self.view = np.lib.stride_tricks.as_strided(self.mat[start:], shape=size.to_numpy(), strides=steps)
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def __iter__(self):
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return iter({'data': stri(self.view)}.items())
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class MatPrinter:
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"""Print a cv::Mat"""
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def __init__(self, mat):
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self.mat = mat
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def views(self):
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m = self.mat
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flags = Flags(int(m['flags']))
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size = Size(m['size']['p'])
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data = Mat(m, size, flags)
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for x in [flags, size, data]:
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for k, v in x:
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yield 'view_' + k, v
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def real(self):
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m = self.mat
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for field in m.type.fields():
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k = field.name
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v = m[k]
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yield k, v
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# TODO: add an enum in interface.h with all cv::Mat element types and use that instead
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# yield 'test', gdb.parse_and_eval(f'(cv::MatTypes)0')
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def children(self): # TODO: hide real members under new child somehow
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yield from self.views()
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yield from self.real()
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def get_type(val):
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# Get the type.
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vtype = val.type
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# If it points to a reference, get the reference.
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if vtype.code == gdb.TYPE_CODE_REF:
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vtype = vtype.target()
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# Get the unqualified type, stripped of typedefs.
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vtype = vtype.unqualified().strip_typedefs()
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# Get the type name.
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typename = vtype.tag
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return typename
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def mat_printer(val):
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typename = get_type(val)
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if typename is None:
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return None
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if str(typename) == 'cv::Mat':
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return MatPrinter(val)
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gdb.pretty_printers.append(mat_printer)
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