Dev

.github/workflows/documentation.yml → .github/workflows/documentation_test_coverage.yml

@@ -1,4 +1,4 @@
-name: Deploy Documentation to GitHub Pages
+name: Deploy Documentation and Test Coverage to GitHub Pages
 
 on:
   push:
@@ -45,7 +45,6 @@ jobs:
 
       - name: Generate Documentation
         run: |
-          python3 ./yolo_models/scripts/copy_readme.py
           cd doxyfiles
           doxygen Doxyfile
 

README.md

@@ -106,12 +106,15 @@ By doing so, we achieved significantly higher inference performance using the Je
 
 Tested on: **Jetson Nano 4GB**, Ubuntu 20.04, JetPack 4.x, CUDA, cuDNN, TensorRT.
 
-## Test Coverage Report
+## Documentation
 
-To see our test coverage report click here: [Coverage Report](https://seame-pt.github.io/ObjectDetectionAvoidance/coverage/index.html).
+To see more documentation on:
+   - PID control, go to [this file](pid_control/README.md).
 
-## Documentation
+   - Microservices, go to [this file](services_raspberryPi/README.md).
 
-To see more Documentation on the PID control go to [this file](pid_control/README.md).
+For a more structured documentation, visit the [Doxygen documentation](https://seame-pt.github.io/ObjectDetectionAvoidance/).
 
-To see a more structured Documentation go to [Doxygen](https://seame-pt.github.io/ObjectDetectionAvoidance/).
+## Test Coverage Report
+
+To see our test coverage report click here: [Coverage Report](https://seame-pt.github.io/ObjectDetectionAvoidance/coverage/index.html).

doxyfiles/Doxyfile

@@ -1120,7 +1120,7 @@ FILTER_SOURCE_PATTERNS =
 # (index.html). This can be useful if you have a project on for instance GitHub
 # and want to reuse the introduction page also for the doxygen output.
 
-USE_MDFILE_AS_MAINPAGE = doxyfile_readme.md
+USE_MDFILE_AS_MAINPAGE = ../README.md
 
 # The Fortran standard specifies that for fixed formatted Fortran code all
 # characters from position 72 are to be considered as comment. A common

doxyfiles/doxyfile.css

@@ -6,3 +6,11 @@ body {
     font-family: Arial, sans-serif;
     font-size: 20px;
 }
+
+img {
+    max-width: 100%;   /* ensures images never overflow container */
+    height: auto;      /* keeps aspect ratio */
+    display: block;    /* optional: removes inline gaps */
+    margin: 10px auto; /* centers the image with margins */
+}
+

yolo_models/scripts/tests/test_bbox_seg.py

@@ -32,3 +32,4 @@ def test_convert_bbox_to_segmentation(tmp_path):
     # Check that all coords are in range [0.0, 1.0]
     coords = list(map(float, parts[1:]))
     assert all(0.0 <= c <= 1.0 for c in coords), "Coords not in [0.0, 1.0]"
+