Merge pull request #29093 from varun-jaiswal17:dnn-overflow-large-image

fix int32 overflow in shape_utils::total() for large tensors #29093

Fixes https://github.com/opencv/opencv/issues/24914

### Problem

When running inference with a ConvTranspose (deconvolution) layer on large inputs
(e.g. 4864×4864 with 30 channels), the DNN module crashes with:

OpenCV net_impl.cpp: error:

(expected: 'total(ints[i]) > 0'), where
'total(ints[i])' is -1455947776
must be greater than
'0' is 0

The root cause is `shape_utils::total()` which returns `int` (32-bit signed).

`ENGINE_CLASSIC` catches this via `CV_CheckGT` and throws.
`ENGINE_NEW` was silently bypassing the check — the overflow in `total()` itself
was never addressed.

### Changes

**`modules/dnn/include/opencv2/dnn/shape_utils.hpp`** — root fix
- Changed return type of both `total()` overloads from `int` to `size_t`
- Changed accumulator from `int elems = 1` to `size_t elems = 1`

**`modules/dnn/src/net_impl.cpp`**
- Updated `CV_CheckGT(total(...), 0)` to `CV_CheckGT(total(...), (size_t)0)`
  to match the new return type

**`modules/dnn/src/net_impl2.cpp`**
- Added the same `CV_CheckGT` shape validation that `ENGINE_CLASSIC` has in
  `net_impl.cpp:1333-1337` — `ENGINE_NEW` was missing this check entirely

**`modules/dnn/src/legacy_backend.hpp`**
- Removed the now-incorrect `(int)` cast in `CV_CheckEQ` — both sides are
  now `size_t`

### Test

Added `Net.ShapeUtils_total_no_int32_overflow` in `modules/dnn/test/test_misc.cpp`:
- The shape [1920 × 1,478,656] is the exact im2col buffer from the bug report.
EXPECT_EQ verifies total() returns the correct size_t value 2,839,019,520.
EXPECT_LT documents that casting it to int wraps to -1,455,947,776 — the
value that caused the original crash.



### 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

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modules/dnn/test/test_misc.cpp

@@ -10,6 +10,7 @@
 #include <opencv2/core/ocl.hpp>
 #include <opencv2/core/opencl/ocl_defs.hpp>
 #include <opencv2/dnn/layer.details.hpp>  // CV_DNN_REGISTER_LAYER_CLASS
+#include <opencv2/dnn/shape_utils.hpp>
 
 namespace opencv_test { namespace {
 
@@ -1071,4 +1072,12 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/, Test_two_inputs, Combine(
     dnnBackendsAndTargets()
 ));
 
+TEST(Net, ShapeUtils_total_no_int32_overflow)
+{
+    cv::MatShape shape = cv::dnn::shape(1920, 1478656);
+
+    size_t t = cv::dnn::total(shape);
+    EXPECT_EQ(t, 2839019520llu);
+}
+
 }} // namespace