Just realised we can get rid of the resolution!

.gitignore

@@ -158,3 +158,6 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+
+*.csv
+.idea/

lib/led_identifier.py

@@ -33,7 +33,9 @@ def find_led(self, image):
         center_x = moments["m10"] / moments["m00"]
         center_y = moments["m01"] / moments["m00"]
 
-        return LedResults((center_x, center_y), contours)
+        max_dimension = max(image.shape)
+
+        return LedResults((center_x/max_dimension, center_y/max_dimension), contours)
 
     @staticmethod
     def draw_results(image, results):

lib/sfm/database_populator.py

@@ -27,8 +27,8 @@ def populate(db_path, input_directory, led_count=23, min_avg_points_per_view=100
         for line in lines:
             led_id, u, v = line.split(",")
 
-            key_points[int(led_id)][0] = float(u)
-            key_points[int(led_id)][1] = float(v)
+            key_points[int(led_id)][0] = float(u)*2000
+            key_points[int(led_id)][1] = float(v)*2000
 
             total_keypoints += 1
 
@@ -47,8 +47,8 @@ def populate(db_path, input_directory, led_count=23, min_avg_points_per_view=100
     # model=0 means that it's a "SIMPLE PINHOLE" with just 1 focal length parameter that I think should get optimised
     # the params here should be f, cx, cy
 
-    width = int(str(input_files[0]).split("_")[-2])
-    height = int(str(input_files[0]).split("_")[-1].replace(".csv", ""))
+    width = 2000
+    height = 2000
     fov = 60  # degrees, this gets optimised so doesn't //really// matter that much
 
     SIMPLE_PINHOLE = 0

scripts/capture_sequence.py

@@ -53,7 +53,7 @@
         # The filename is made out of the date, then the resolution of the camera
         string_time = time.strftime("%Y%m%d-%H%M%S")
         filename = (
-            f"capture_{string_time}_{l3d.cam.get_width()}_{l3d.cam.get_height()}.csv"
+            f"capture_{string_time}.csv"
         )
 
         filepath = os.path.join(output_dir_full, filename)

scripts/visualise.py

@@ -14,26 +14,23 @@
 
     args = parser.parse_args()
 
-    file_resolution = [
-        int(r) for r in args.filename.replace(".csv", "").split("_")[-2:]
-    ]
-
-    display = np.zeros((file_resolution[1], file_resolution[0], 3))
+    display = np.zeros((640, 640, 3))
 
     with open(args.filename, "r") as file:
         lines = file.readlines()
-        file_points = [
-            [int(float(v)) for v in line.strip().split(",")] for line in lines
-        ]
+        file_points = []
+        for line in lines:
+            led_id, u, v = line.strip().split(",")
+            file_points.append([led_id, float(u), float(v)])
 
         if len(file_points[0]) == 3:
 
             for point_id, point_u, point_v in file_points:
-                image_point = (int(point_u), int(point_v))
+                image_point = (int(point_u*640), int(point_v*640))
                 cv2.drawMarker(display, image_point, color=(0, 255, 0))
                 cv2.putText(
                     display,
-                    f"{point_id}",
+                    point_id,
                     image_point,
                     cv2.FONT_HERSHEY_SIMPLEX,
                     1,

test/test_capture_sequence.py

@@ -27,7 +27,7 @@ def test_capture_sequence():
 
         # The filename is made out of the date, then the resolution of the camera
         filename = (
-            f"capture_cam_{device_id}_{l3d.cam.get_width()}_{l3d.cam.get_height()}.csv"
+            f"capture_cam_{device_id}.csv"
         )
 
         filepath = os.path.join(output_dir_full, filename)
@@ -49,9 +49,9 @@ def test_capture_sequence_correctness():
 
     mock_camera = MockCamera()
 
-    for device_id in range(5):
+    for device_id in range(9):
         output_dir_full = os.path.join(os.getcwd(), "my_scans", "test")
-        filename = f"capture_cam_{device_id}_{mock_camera.get_width()}_{mock_camera.get_height()}.csv"
+        filename = f"capture_cam_{device_id}.csv"
         filepath = os.path.join(output_dir_full, filename)
 
         with open(filepath, "r") as csv_file:

test/test_led_identifier.py

@@ -20,8 +20,8 @@ def test_basic_image_loading():
 
     led_results = led_finder.find_led(mock_camera.read())
 
-    assert close(led_results.u(), 257)
-    assert close(led_results.v(), 177)
+    assert close(led_results.u(), 257/640.0)
+    assert close(led_results.v(), 177/480.0)
 
 
 def test_none_found():