Merge pull request #26026 from Abdurrahheem:ash/python_bool_binding

Add support for boolan input/outputs in python bindings #26026

This PR add support boolean input/output binding in python. The issue what mention in ticket https://github.com/opencv/opencv/issues/26024 and the PR soleves it. Data and models are located in [here](https://github.com/opencv/opencv_extra/pull/1201)

### 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

modules/core/misc/python/pyopencv_core.hpp

@@ -29,7 +29,8 @@ static PyObject* pycvMakeTypeCh(PyObject*, PyObject *value) {
   {"CV_32SC", (PyCFunction)(pycvMakeTypeCh<CV_32S>), METH_O, "CV_32SC(channels) -> retval"}, \
   {"CV_32FC", (PyCFunction)(pycvMakeTypeCh<CV_32F>), METH_O, "CV_32FC(channels) -> retval"}, \
   {"CV_64FC", (PyCFunction)(pycvMakeTypeCh<CV_64F>), METH_O, "CV_64FC(channels) -> retval"}, \
-  {"CV_16FC", (PyCFunction)(pycvMakeTypeCh<CV_16F>), METH_O, "CV_16FC(channels) -> retval"},
+  {"CV_16FC", (PyCFunction)(pycvMakeTypeCh<CV_16F>), METH_O, "CV_16FC(channels) -> retval"}, \
+  {"CV_BoolC", (PyCFunction)(pycvMakeTypeCh<CV_Bool>), METH_O, "CV_BoolC(channels) -> retval"},
 
 #endif  // HAVE_OPENCV_CORE
 #endif  // OPENCV_CORE_PYOPENCV_CORE_HPP

modules/dnn/misc/python/test/test_dnn.py

@@ -546,5 +546,24 @@ class dnn_test(NewOpenCVTests):
         out = net.forward()
         self.assertEqual(out.shape, (1, 2, 3, 4))
 
+    def test_bool_operator(self):
+        n = self.find_dnn_file('dnn/onnx/models/and_op.onnx')
+
+        x = np.random.randint(0, 2, [5], dtype=np.bool_)
+        y = np.random.randint(0, 2, [5], dtype=np.bool_)
+        o = x & y
+
+        net = cv.dnn.readNet(n)
+
+        names = ["x", "y"]
+        net.setInputsNames(names)
+        net.setInput(x, names[0])
+        net.setInput(y, names[1])
+
+        out = net.forward()
+
+        self.assertTrue(np.all(out == o))
+
+
 if __name__ == '__main__':
     NewOpenCVTests.bootstrap()

modules/python/src2/cv2.cpp

@@ -562,6 +562,11 @@ static bool init_body(PyObject * m)
     PUBLISH(CV_16FC2);
     PUBLISH(CV_16FC3);
     PUBLISH(CV_16FC4);
+    PUBLISH(CV_Bool);
+    PUBLISH(CV_BoolC1);
+    PUBLISH(CV_BoolC2);
+    PUBLISH(CV_BoolC3);
+    PUBLISH(CV_BoolC4);
 #undef PUBLISH_
 #undef PUBLISH
 

modules/python/src2/cv2_convert.cpp

@@ -137,7 +137,9 @@ bool pyopencv_to(PyObject* o, Mat& m, const ArgInfo& info)
                typenum == NPY_INT32 ? CV_32S :
                typenum == NPY_HALF ? CV_16F :
                typenum == NPY_FLOAT ? CV_32F :
-               typenum == NPY_DOUBLE ? CV_64F : -1;
+               typenum == NPY_DOUBLE ? CV_64F :
+               typenum == NPY_BOOL ? CV_Bool :
+               -1;
 
     if( type < 0 )
     {

modules/python/src2/cv2_numpy.cpp

@@ -37,7 +37,7 @@ UMatData* NumpyAllocator::allocate(int dims0, const int* sizes, int type, void*
     int typenum = depth == CV_8U ? NPY_UBYTE : depth == CV_8S ? NPY_BYTE :
     depth == CV_16U ? NPY_USHORT : depth == CV_16S ? NPY_SHORT :
     depth == CV_32S ? NPY_INT : depth == CV_32F ? NPY_FLOAT :
-    depth == CV_64F ? NPY_DOUBLE : depth == CV_16F ? NPY_HALF : f*NPY_ULONGLONG + (f^1)*NPY_UINT;
+    depth == CV_64F ? NPY_DOUBLE : depth == CV_16F ? NPY_HALF : depth == CV_Bool ? NPY_BOOL : f*NPY_ULONGLONG + (f^1)*NPY_UINT;
     int i, dims = dims0;
     cv::AutoBuffer<npy_intp> _sizes(dims + 1);
     for( i = 0; i < dims; i++ )

modules/python/src2/typing_stubs_generation/api_refinement.py

@@ -56,7 +56,7 @@ def export_matrix_type_constants(root: NamespaceNode) -> None:
     MAX_PREDEFINED_CHANNELS = 4
 
     depth_names = ("CV_8U", "CV_8S", "CV_16U", "CV_16S", "CV_32S",
-                   "CV_32F", "CV_64F", "CV_16F")
+                   "CV_32F", "CV_64F", "CV_16F", "CV_Bool")
     for depth_value, depth_name in enumerate(depth_names):
         # Export depth constants
         root.add_constant(depth_name, str(depth_value))

modules/python/test/test_misc.py

@@ -234,6 +234,7 @@ class Bindings(NewOpenCVTests):
             cv.CV_16UC2: [cv.CV_16U, 2, cv.CV_16UC],
             cv.CV_32SC1: [cv.CV_32S, 1, cv.CV_32SC],
             cv.CV_16FC3: [cv.CV_16F, 3, cv.CV_16FC],
+            cv.CV_BoolC1: [cv.CV_Bool, 1, cv.CV_BoolC],
         }
         for ref, (depth, channels, func) in data.items():
             self.assertEqual(ref, cv.CV_MAKETYPE(depth, channels))
@@ -277,6 +278,9 @@ class Arguments(NewOpenCVTests):
         a = np.zeros((2,3,4,5), dtype='f')
         res7 = cv.utils.dumpInputArray(a)
         self.assertEqual(res7, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=120 dims(-1)=4 size(-1)=[2 3 4 5] type(-1)=CV_32FC1")
+        a = np.array([0, 1, 0, 1], dtype=bool)
+        res8 = cv.utils.dumpInputArray(a)
+        self.assertEqual(res8, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=4 dims(-1)=1 size(-1)=4x1 type(-1)=CV_BoolC1")
 
     def test_InputArrayOfArrays(self):
         res1 = cv.utils.dumpInputArrayOfArrays(None)
@@ -339,7 +343,7 @@ class Arguments(NewOpenCVTests):
 
     def test_parse_to_bool_not_convertible(self):
         for not_convertible in (1.2, np.float32(2.3), 's', 'str', (1, 2), [1, 2], complex(1, 1),
-                                complex(imag=2), complex(1.1), np.array([1, 0], dtype=bool)):
+                                complex(imag=2), complex(1.1)):
             with self.assertRaises((TypeError, OverflowError),
                                    msg=get_no_exception_msg(not_convertible)):
                 _ = cv.utils.dumpBool(not_convertible)