Merge pull request #24231 from fengyuentau:halide_cleanup_5.x

dnn: cleanup of halide backend for 5.x #24231

Merge with https://github.com/opencv/opencv_extra/pull/1092.

### 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

samples/dnn/classification.cpp

@@ -8,7 +8,7 @@
 
 #include "common.hpp"
 
-std::string keys =
+std::string param_keys =
     "{ help  h          | | Print help message. }"
     "{ @alias           | | An alias name of model to extract preprocessing parameters from models.yml file. }"
     "{ zoo              | models.yml | An optional path to file with preprocessing parameters }"
@@ -19,23 +19,26 @@ std::string keys =
     "{ crop             | false | Preprocess input image by center cropping.}"
     "{ framework f      | | Optional name of an origin framework of the model. Detect it automatically if it does not set. }"
     "{ needSoftmax      | false | Use Softmax to post-process the output of the net.}"
-    "{ classes          | | Optional path to a text file with names of classes. }"
+    "{ classes          | | Optional path to a text file with names of classes. }";
+std::string backend_keys = cv::format(
     "{ backend          | 0 | Choose one of computation backends: "
-                            "0: automatically (by default), "
-                            "1: Halide language (http://halide-lang.org/), "
-                            "2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit), "
-                            "3: OpenCV implementation, "
-                            "4: VKCOM, "
-                            "5: CUDA, "
-                            "6: WebNN }"
+                              "%d: automatically (by default), "
+                              "%d: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit), "
+                              "%d: OpenCV implementation, "
+                              "%d: VKCOM, "
+                              "%d: CUDA, "
+                              "%d: WebNN }", cv::dnn::DNN_BACKEND_DEFAULT, cv::dnn::DNN_BACKEND_INFERENCE_ENGINE, cv::dnn::DNN_BACKEND_OPENCV, cv::dnn::DNN_BACKEND_VKCOM, cv::dnn::DNN_BACKEND_CUDA, cv::dnn::DNN_BACKEND_WEBNN);
+std::string target_keys = cv::format(
     "{ target           | 0 | Choose one of target computation devices: "
-                            "0: CPU target (by default), "
-                            "1: OpenCL, "
-                            "2: OpenCL fp16 (half-float precision), "
-                            "3: VPU, "
-                            "4: Vulkan, "
-                            "6: CUDA, "
-                            "7: CUDA fp16 (half-float preprocess) }";
+                              "%d: CPU target (by default), "
+                              "%d: OpenCL, "
+                              "%d: OpenCL fp16 (half-float precision), "
+                              "%d: VPU, "
+                              "%d: Vulkan, "
+                              "%d: CUDA, "
+                              "%d: CUDA fp16 (half-float preprocess) }", cv::dnn::DNN_TARGET_CPU, cv::dnn::DNN_TARGET_OPENCL, cv::dnn::DNN_TARGET_OPENCL_FP16, cv::dnn::DNN_TARGET_MYRIAD, cv::dnn::DNN_TARGET_VULKAN, cv::dnn::DNN_TARGET_CUDA, cv::dnn::DNN_TARGET_CUDA_FP16);
+
+std::string keys = param_keys + backend_keys + target_keys;
 
 using namespace cv;
 using namespace dnn;