depth-anything: fix benchmark and add numbers, bump version

Author: Acly

CMakeLists.txt

@@ -1,6 +1,6 @@
 cmake_minimum_required(VERSION 3.28)
 
-project(vision.cpp VERSION 0.1.0 LANGUAGES CXX)
+project(vision.cpp VERSION 0.2.0 LANGUAGES CXX)
 
 option(VISP_VULKAN "Enable Vulkan support" OFF)
 option(VISP_DEV "Enable development mode" OFF)
@@ -30,7 +30,7 @@ elseif(CMAKE_BUILD_TYPE)
   endif()
 endif()
 
-# Configure address sanitizer (Clang only)
+# Configure address sanitizer
 
 if(VISP_ASAN)
   if(MSVC)

README.md

@@ -209,6 +209,13 @@ as other frameworks for inference speed, but with:
 | Lite  | cpu  | f32  |      4505 ms | 10900 ms |      6978 ms |
 | Lite  | gpu  | f16  |        85 ms |    84 ms |              |
 
+#### Depth-Anything, 518x714
+
+| Model |      |      | _vision.cpp_ | PyTorch |
+| :---- | :--- | :--- | -----------: | ------: |
+| Small | gpu  | f16  |        11 ms |   10 ms |
+| Base  | gpu  | f16  |        24 ms |   22 ms |
+
 #### MI-GAN, 512x512
 
 | Model       |      |      | _vision.cpp_ | PyTorch |
@@ -218,7 +225,7 @@ as other frameworks for inference speed, but with:
 
 #### Setup
 
-* vision.cpp: using vision-bench, GPU via Vulkan, eg. `vision-bench -m sam -b cpu`
+* vision.cpp: using vision-bench, GPU via Vulkan, eg. `vision-bench -m sam`
 * PyTorch: v2.7.1+cu128, eager eval, GPU via CUDA, average n iterations after warm-up
 
 ## Dependencies (integrated)

tests/benchmark.cpp

@@ -94,13 +94,13 @@ bench_timings benchmark_birefnet(path model_path, backend_device& backend) {
 }
 
 bench_timings benchmark_depth_anything(path model_path, backend_device& backend) {
-    path input_path = test_dir().input / "cat-and-hat.jpg";
+    path input_path = test_dir().input / "wardrobe.jpg";
 
     depthany_model model = depthany_load_model(model_path.string().c_str(), backend);
     image_data input = image_load(input_path.string().c_str());
-    image_data input_data = depthany_process_input(input, model.params);
-
     depthany_compute(model, input);
+
+    image_data input_data = depthany_process_input(input, model.params);
     return run_benchmark(model.graph, backend, 12, {{model.input, input_data}});
 }