Merge pull request #24028 from VadimLevin:dev/vlevin/fix-flann-python-bindings

Fix FLANN python bindings #24028

As a side-effect this patch improves reporting errors by FLANN `get_param`.

resolves #21642

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
pull/24040/head
Vadim Levin 1 year ago committed by GitHub
parent 09d2f4ea46
commit e3cb5f80e7
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  1. 29
      modules/flann/include/opencv2/flann/any.h
  2. 2
      modules/flann/include/opencv2/flann/general.h
  3. 3
      modules/flann/include/opencv2/flann/matrix.h
  4. 18
      modules/flann/include/opencv2/flann/params.h
  5. 3
      modules/flann/include/opencv2/flann/result_set.h
  6. 100
      modules/flann/misc/python/pyopencv_flann.hpp
  7. 30
      modules/flann/misc/python/test/test_flann_based_matcher.py

@ -19,16 +19,39 @@
#include <ostream> #include <ostream>
#include <typeinfo> #include <typeinfo>
#include "opencv2/core/cvdef.h"
#include "opencv2/core/utility.hpp"
namespace cvflann namespace cvflann
{ {
namespace anyimpl namespace anyimpl
{ {
struct bad_any_cast struct bad_any_cast : public std::exception
{ {
bad_any_cast() = default;
bad_any_cast(const char* src, const char* dst)
: message_(cv::format("cvflann::bad_any_cast(from %s to %s)", src, dst)) {}
const char* what() const noexcept override
{
return message_.c_str();
}
private:
std::string message_{"cvflann::bad_any_cast"};
}; };
#ifndef CV_THROW_IF_TYPE_MISMATCH
#define CV_THROW_IF_TYPE_MISMATCH(src_type_info, dst_type_info) \
if ((src_type_info) != (dst_type_info)) \
throw cvflann::anyimpl::bad_any_cast((src_type_info).name(), \
(dst_type_info).name())
#endif
struct empty_any struct empty_any
{ {
}; };
@ -271,7 +294,7 @@ public:
template<typename T> template<typename T>
T& cast() T& cast()
{ {
if (policy->type() != typeid(T)) throw anyimpl::bad_any_cast(); CV_THROW_IF_TYPE_MISMATCH(policy->type(), typeid(T));
T* r = reinterpret_cast<T*>(policy->get_value(&object)); T* r = reinterpret_cast<T*>(policy->get_value(&object));
return *r; return *r;
} }
@ -280,7 +303,7 @@ public:
template<typename T> template<typename T>
const T& cast() const const T& cast() const
{ {
if (policy->type() != typeid(T)) throw anyimpl::bad_any_cast(); CV_THROW_IF_TYPE_MISMATCH(policy->type(), typeid(T));
const T* r = reinterpret_cast<const T*>(policy->get_value(&object)); const T* r = reinterpret_cast<const T*>(policy->get_value(&object));
return *r; return *r;
} }

@ -31,6 +31,8 @@
#ifndef OPENCV_FLANN_GENERAL_H_ #ifndef OPENCV_FLANN_GENERAL_H_
#define OPENCV_FLANN_GENERAL_H_ #define OPENCV_FLANN_GENERAL_H_
#include "opencv2/core/version.hpp"
#if CV_VERSION_MAJOR <= 4 #if CV_VERSION_MAJOR <= 4
//! @cond IGNORED //! @cond IGNORED

@ -35,6 +35,9 @@
#include <stdio.h> #include <stdio.h>
#include "opencv2/core/cvdef.h"
#include "opencv2/flann/defines.h"
namespace cvflann namespace cvflann
{ {

@ -72,11 +72,16 @@ struct SearchParams : public IndexParams
template<typename T> template<typename T>
T get_param(const IndexParams& params, cv::String name, const T& default_value) T get_param(const IndexParams& params, const cv::String& name, const T& default_value)
{ {
IndexParams::const_iterator it = params.find(name); IndexParams::const_iterator it = params.find(name);
if (it != params.end()) { if (it != params.end()) {
return it->second.cast<T>(); try {
return it->second.cast<T>();
} catch (const std::exception& e) {
CV_Error_(cv::Error::StsBadArg,
("FLANN '%s' param type mismatch: %s", name.c_str(), e.what()));
}
} }
else { else {
return default_value; return default_value;
@ -84,11 +89,16 @@ T get_param(const IndexParams& params, cv::String name, const T& default_value)
} }
template<typename T> template<typename T>
T get_param(const IndexParams& params, cv::String name) T get_param(const IndexParams& params, const cv::String& name)
{ {
IndexParams::const_iterator it = params.find(name); IndexParams::const_iterator it = params.find(name);
if (it != params.end()) { if (it != params.end()) {
return it->second.cast<T>(); try {
return it->second.cast<T>();
} catch (const std::exception& e) {
CV_Error_(cv::Error::StsBadArg,
("FLANN '%s' param type mismatch: %s", name.c_str(), e.what()));
}
} }
else { else {
FLANN_THROW(cv::Error::StsBadArg, cv::String("Missing parameter '")+name+cv::String("' in the parameters given")); FLANN_THROW(cv::Error::StsBadArg, cv::String("Missing parameter '")+name+cv::String("' in the parameters given"));

@ -40,6 +40,9 @@
#include <set> #include <set>
#include <vector> #include <vector>
#include "opencv2/core/base.hpp"
#include "opencv2/core/cvdef.h"
namespace cvflann namespace cvflann
{ {

@ -17,57 +17,89 @@ PyObject* pyopencv_from(const cvflann_flann_distance_t& value)
template<> template<>
bool pyopencv_to(PyObject *o, cv::flann::IndexParams& p, const ArgInfo& info) bool pyopencv_to(PyObject *o, cv::flann::IndexParams& p, const ArgInfo& info)
{ {
CV_UNUSED(info);
bool ok = true;
PyObject* key = NULL;
PyObject* item = NULL;
Py_ssize_t pos = 0;
if (!o || o == Py_None) if (!o || o == Py_None)
{
return true; return true;
}
if(!PyDict_Check(o))
{
failmsg("Argument '%s' is not a dictionary", info.name);
return false;
}
PyObject* key_obj = NULL;
PyObject* value_obj = NULL;
Py_ssize_t key_pos = 0;
if(PyDict_Check(o)) { while(PyDict_Next(o, &key_pos, &key_obj, &value_obj))
while(PyDict_Next(o, &pos, &key, &item)) {
// get key
std::string key;
if (!getUnicodeString(key_obj, key))
{ {
// get key failmsg("Key at pos %lld is not a string", static_cast<int64_t>(key_pos));
std::string k; return false;
if (!getUnicodeString(key, k)) }
// key_arg_info.name is bound to key lifetime
const ArgInfo key_arg_info(key.c_str(), false);
// get value
if (isBool(value_obj))
{
npy_bool npy_value = NPY_FALSE;
if (PyArray_BoolConverter(value_obj, &npy_value) >= 0)
{ {
ok = false; p.setBool(key, npy_value == NPY_TRUE);
break; continue;
} }
// get value PyErr_Clear();
if( !!PyBool_Check(item) ) }
int int_value = 0;
if (pyopencv_to(value_obj, int_value, key_arg_info))
{
if (key == "algorithm")
{ {
p.setBool(k, item == Py_True); p.setAlgorithm(int_value);
} }
else if( PyInt_Check(item) ) else
{ {
int value = (int)PyInt_AsLong(item); p.setInt(key, int_value);
if( strcmp(k.c_str(), "algorithm") == 0 )
p.setAlgorithm(value);
else
p.setInt(k, value);
} }
else if( PyFloat_Check(item) ) continue;
}
PyErr_Clear();
double flt_value = 0.0;
if (pyopencv_to(value_obj, flt_value, key_arg_info))
{
if (key == "eps")
{ {
double value = PyFloat_AsDouble(item); p.setFloat(key, static_cast<float>(flt_value));
p.setDouble(k, value);
} }
else else
{ {
std::string val_str; p.setDouble(key, flt_value);
if (!getUnicodeString(item, val_str))
{
ok = false;
break;
}
p.setString(k, val_str);
} }
continue;
} }
} PyErr_Clear();
return ok && !PyErr_Occurred(); std::string str_value;
if (getUnicodeString(value_obj, str_value))
{
p.setString(key, str_value);
continue;
}
PyErr_Clear();
// All conversions are failed
failmsg("Failed to parse IndexParam with key '%s'. "
"Supported types: [bool, int, float, str]", key.c_str());
return false;
}
return true;
} }
template<> template<>

@ -0,0 +1,30 @@
#!/usr/bin/env python
# Python 2/3 compatibility
from __future__ import print_function
import cv2
import numpy as np
from tests_common import NewOpenCVTests
class FlannBasedMatcher(NewOpenCVTests):
def test_all_parameters_can_be_passed(self):
img1 = self.get_sample("samples/data/right01.jpg")
img2 = self.get_sample("samples/data/right02.jpg")
orb = cv2.ORB.create()
kp1, des1 = orb.detectAndCompute(img1, None)
kp2, des2 = orb.detectAndCompute(img2, None)
FLANN_INDEX_KDTREE = 1
index_param = dict(algorithm=FLANN_INDEX_KDTREE, trees=4)
search_param = dict(checks=32, sorted=True, eps=0.5,
explore_all_trees=False)
matcher = cv2.FlannBasedMatcher(index_param, search_param)
matches = matcher.knnMatch(np.float32(des1), np.float32(des2), k=2)
self.assertGreater(len(matches), 0)
if __name__ == '__main__':
NewOpenCVTests.bootstrap()
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