build: support OpenCV 5 and TensorRT 10

OpenCV: distros (Arch/CachyOS) now ship OpenCV 5 as default. The config
package rejects a 5.x install when find_package requests 4, so probe for 5
first and fall back to 4. All components used here (core, imgproc, imgcodecs,
videoio, dnn, objdetect, highgui) exist in both.

TensorRT: nvinfer1::Dims5 was removed in TRT 10 (Dims2..Dims4 remain in
NvInferLegacyDims.h). Build the TransNetV2 rank-5 input shape via the generic
nvinfer1::Dims, which is valid on both 8.x and 10.x.

CMakeLists.txt

@@ -18,8 +18,17 @@ endif()
 add_subdirectory(external/KPN)
 
 # OpenCV (video decode, image ops, DNN inference, face detection)
+# Accept 4 or 5: the APIs used here are stable across both, and distros have
+# begun shipping 5.x as the default (Arch/CachyOS). find_package's version
+# argument is a minimum, but OpenCV's config rejects a 5.x install when 4 is
+# requested, so probe for 5 first and fall back to 4.
+find_package(OpenCV 5 QUIET COMPONENTS
+    core imgproc imgcodecs videoio dnn objdetect highgui)
+if(NOT OpenCV_FOUND)
     find_package(OpenCV 4 REQUIRED COMPONENTS
         core imgproc imgcodecs videoio dnn objdetect highgui)
+endif()
+message(STATUS "OpenCV: ${OpenCV_VERSION}")
 
 # ── Model paths ───────────────────────────────────────────────────────────────
 # Defined early so the backend object libraries below can embed it.

src/backends/trt_backend.cpp

@@ -511,8 +511,17 @@ public:
         }
 
         std::lock_guard<std::mutex> lk(mu_);
-        context_->setInputShape(input_name_.c_str(),
+        // TensorRT 10 removed the fixed-rank Dims5 helper (Dims2..Dims4 remain
-            nvinfer1::Dims5{1, kWindow, kFrameH, kFrameW, 3});
+        // in NvInferLegacyDims.h). Build the rank-5 shape via the generic Dims,
+        // which works on both 8.x and 10.x.
+        nvinfer1::Dims shape{};
+        shape.nbDims = 5;
+        shape.d[0] = 1;
+        shape.d[1] = kWindow;
+        shape.d[2] = kFrameH;
+        shape.d[3] = kFrameW;
+        shape.d[4] = 3;
+        context_->setInputShape(input_name_.c_str(), shape);
 
         check_cuda(cudaMemcpyAsync(d_input_, buf.data(), buf.size() * 4,
                                    cudaMemcpyHostToDevice, stream_), "H2D input");