going in the right direction.

object_tracking.py

@@ -0,0 +1,81 @@
+from ultralytics import YOLO
+import cv2
+from helper import create_video_writer, iter_frames, time_tracker
+import matplotlib
+from numpy import arange
+
+Color = tuple[int, int, int]
+
+
+class DetectedObjectBox:
+    def __init__(self, min_threshold: float, color: Color):
+        self.min_threshold = min_threshold
+        self.color = color
+
+    def __lt__(self, other):
+        return self.min_threshold < other.min_threshold
+
+    @classmethod
+    def from_viridis(cls, min_threshold):
+        cm = matplotlib.colormaps['viridis']
+        color: Color = tuple((int(255 * cm(min_threshold)[i]) for i in range(3)))
+        return cls(min_threshold, color)
+
+
+def write_frame(writer, frame):
+    cv2.imshow("Frame", frame)
+    writer.write(frame)
+
+
+def extract_box(data):
+    return int(data[0]), int(data[1]), int(data[2]), int(data[3])
+
+
+def plot_boxe_to_frame(data, frame, detected_box_objects):
+    confidence = float(data[4])
+    for detected_box_object in detected_box_objects:
+
+        if detected_box_object.min_threshold < confidence:
+            xmin, ymin, xmax, ymax = extract_box(data)
+            cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), detected_box_object.color, 2)
+            return
+
+
+def run_model_on_frame(model, frame):
+    return model(frame)[0]
+
+
+def main(input_filename, output_filename, detected_box_objects):
+    # define some constants
+    detected_box_objects = sorted(detected_box_objects, reverse=True)
+
+    video_cap = cv2.VideoCapture(input_filename)
+    writer = create_video_writer(video_cap, output_filename)
+
+    # load the pre-trained YOLOv8n model
+    model = YOLO("yolov8n.pt")
+
+    for frame in iter_frames(video_cap):
+        with time_tracker():
+            # run the YOLO model on the frame
+            detections = run_model_on_frame(model, frame)
+            for data in detections.boxes.data.tolist():
+                plot_boxe_to_frame(data, frame, detected_box_objects)
+
+            # show the frame to our screen
+            write_frame(writer, frame)
+
+            if cv2.waitKey(1) == ord("q"):
+                break
+
+    video_cap.release()
+    writer.release()
+    cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    detected_box_objects = [
+        DetectedObjectBox.from_viridis(threshold) for threshold in arange(0.5, 1, 0.05)
+    ]
+
+    main("micro.mp4", "output.mp4", detected_box_objects)