detection, tracking and annotation added

examples/speed_estimation/ultralytics_example.py

@@ -1,7 +1,40 @@
-import cv2
 import argparse
+import json
+from dataclasses import dataclass
+from typing import List
+
+import cv2
+from ultralytics import YOLO
+
 import supervision as sv
 
+
+COLOR = sv.Color.red()
+
+
+@dataclass
+class Line:
+    start: sv.Point
+    end: sv.Point
+
+
+@dataclass
+class Config:
+    lines: List[Line]
+    distance: float
+
+    @classmethod
+    def load(cls, file_path: str):
+        with open(file_path, 'r') as file:
+            data = json.load(file)
+            lines = [
+                Line(sv.Point(**line['start']), sv.Point(**line['end']))
+                for line
+                in data['lines']
+            ]
+            return cls(lines, data['distance'])
+
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(
         description="Vehicle Speed Estimation using Supervision Package"
@@ -46,11 +79,64 @@ if __name__ == "__main__":
 
     args = parser.parse_args()
 
+    config = Config.load(args.lines_configuration_path)
     video_info = sv.VideoInfo.from_video_path(video_path=args.source_video_path)
+
+    model = YOLO(args.source_weights_path)
+    byte_track = sv.ByteTrack(frame_rate=video_info.fps)
+
+    thickness = sv.calculate_dynamic_line_thickness(
+        resolution_wh=video_info.resolution_wh)
+    text_scale = sv.calculate_dynamic_text_scale(
+        resolution_wh=video_info.resolution_wh)
+
+    bounding_box_annotator = sv.BoundingBoxAnnotator(
+        thickness=thickness, color=COLOR)
+    label_annotator = sv.LabelAnnotator(
+        text_scale=text_scale, text_thickness=thickness, color=COLOR,
+        text_position=sv.Position.BOTTOM_CENTER)
+    trace_annotator = sv.TraceAnnotator(
+        thickness=thickness, color=COLOR, trace_length=video_info.fps,
+        position=sv.Position.BOTTOM_CENTER)
+
     frame_generator = sv.get_video_frames_generator(source_path=args.source_video_path)
 
     for frame in frame_generator:
-        cv2.imshow("frame", frame)
+        result = model(frame)[0]
+        detections = sv.Detections.from_ultralytics(result)
+        detections = byte_track.update_with_detections(detections)
+
+        labels = [
+            f"#{tracker_id}"
+            for _, _, _, _, tracker_id
+            in detections
+        ]
+
+        annotated_frame = frame.copy()
+        annotated_frame = sv.draw_line(
+            scene=annotated_frame,
+            start=config.lines[0].start,
+            end=config.lines[0].end,
+            color=sv.Color.white(),
+            thickness=2)
+        annotated_frame = sv.draw_line(
+            scene=annotated_frame,
+            start=config.lines[1].start,
+            end=config.lines[1].end,
+            color=sv.Color.white(),
+            thickness=2)
+        annotated_frame = bounding_box_annotator.annotate(
+            scene=annotated_frame,
+            detections=detections)
+        annotated_frame = trace_annotator.annotate(
+            scene=annotated_frame,
+            detections=detections)
+        annotated_frame = label_annotator.annotate(
+            scene=annotated_frame,
+            detections=detections,
+            labels=labels)
+
+        cv2.imshow("frame", annotated_frame)
         if cv2.waitKey(1) & 0xFF == ord("q"):
             break
     cv2.destroyAllWindows()