From 08f1fcad1c74e25f97641a0ccbd229b267ec528c Mon Sep 17 00:00:00 2001
From: Michael Welter <michael@welter-4d.de>
Date: Sun, 11 Sep 2022 20:55:26 +0200
Subject: tracker/nn: Tweaks, refactoring, a deadzone filtering and support for
 uncertainty estimation

* Add rudimentary test for two functions .. maybe more in future
* Fix the rotation correction from vertical translation
* Move preview class to new files
* Move neural network model adapters to new files
* Add utility functions for opencv
* Query the model inputs/outputs by name to see what is available
* Supports outputs for standard deviation of the data distribution -
  What you get if you let your model output the full parameters of a
  gaussian distribution (depending on the inputs) and fit it with
  negative log likelihood loss.
* Disabled support for sequence models
* Add support for detection of eye open/close classification.
  Scale uncertainty estimate up if eyes closed
* Add a deadzone filter which activates if the model supports uncertainty
  quantification. The deadzone scales becomes larger the more uncertain
  the model/data are. This is mostly supposed to be useful to suppress
  large estimate errors when the user blinks with the eyes
* Fix distance being twice of what it should have been
---
 tracker-neuralnet/tests.cpp | 58 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 58 insertions(+)
 create mode 100644 tracker-neuralnet/tests.cpp

(limited to 'tracker-neuralnet/tests.cpp')

diff --git a/tracker-neuralnet/tests.cpp b/tracker-neuralnet/tests.cpp
new file mode 100644
index 00000000..b1d2a6d0
--- /dev/null
+++ b/tracker-neuralnet/tests.cpp
@@ -0,0 +1,58 @@
+#include "model_adapters.h"
+
+#include <algorithm>
+#include <numeric>
+#include <cstdio>
+
+namespace neuralnet_tracker_tests
+{
+
+
+void assert_(bool ok, const std::string& msg)
+{
+    if (ok)
+        return;
+    std::cout << msg << std::endl;
+    std::exit(-1);
+}
+
+
+void test_find_input_intensity_quantile()
+{
+    cv::Mat data(10,10, CV_8UC1);
+    std::iota(data.begin<uint8_t>(), data.end<uint8_t>(), 0);
+
+    const float pct = 90;
+
+    const int val = neuralnet_tracker_ns::find_input_intensity_quantile(data, pct);
+    
+    assert_(val == int(10*10*pct/100.f), "test_find_input_intensity_quantile failed");
+}
+
+
+void test_normalize_brightness()
+{
+    cv::Mat data(10,10, CV_8UC1);
+    std::iota(data.begin<uint8_t>(), data.end<uint8_t>(), 0);
+
+    cv::Mat out;
+    neuralnet_tracker_ns::normalize_brightness(data, out);
+
+    auto [minit,maxit] = std::minmax_element(out.begin<float>(),out.end<float>());
+    const auto minval = *minit;
+    const auto maxval = *maxit;
+    assert_(std::abs(minval + 0.5f) < 0.02, "test_normalize_brightness failed");
+    // If the brightest value is lower than half-max, it will be boosted to half-max.
+    // Otherwise it will just be rescaled to [-.5, 0.5 ]. Here we have the low-brightness case.
+    assert_(std::abs(maxval - 0.0f) < 0.02, "test_normalize_brightness failed");
+}
+
+
+void run()
+{
+    test_find_input_intensity_quantile();
+    test_normalize_brightness();
+}
+
+
+}
\ No newline at end of file
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