added basic tracker. It takes way too much time.

dodgeballtracker/logic.py

@@ -1,10 +1,9 @@
 import json
-import sys
 from pathlib import Path
 
 from ultralytics import YOLO
 import cv2
-from dodgeballtracker.helper import create_video_writer, iter_frames, time_tracker
+from dodgeballtracker.helper import create_video_writer, iter_frames
 from deep_sort_realtime.deepsort_tracker import DeepSort
 import matplotlib
 import numpy as np
@@ -74,11 +73,8 @@ class DodgeballTracker:
 
     def print_box(self, data, frame_idx, frame_ts):
         xmin, ymin, xmax, ymax = self.extract_box(data)
-        v = np.array([
+        xavg = (xmax + xmin) / 2
-            (xmax + xmin) / 2,
+        v = np.array([xavg, ymax, 1])
-            ymax,  # (ymax + ymin) / 2,
-            1
-        ])
         ret = self.transformation_matrix @ v
         x, y = ret[0] / ret[2], ret[1] / ret[2]
         self.points.append({"x": x, "y": y, "frameIndex": frame_idx, "frameTimestamp": frame_ts})
@@ -91,7 +87,7 @@ class DodgeballTracker:
                 xmin, ymin, xmax, ymax = self.extract_box(data)
                 self.print_box(data, frame_idx, frame_ts)
                 cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), detected_box_object.color, 2)
-                return
+                return [[xmin, ymin, xmax - xmin, ymax - ymin], confidence, int(data[5])]
 
     def run_model_on_frame(self, model, frame):
         return model(frame)[0]
@@ -118,6 +114,7 @@ class DodgeballTracker:
 
         video_cap = cv2.VideoCapture(str(self.input_path))
         writer = create_video_writer(video_cap, str(self.output_path))
+        tracker = DeepSort(max_age=50)
 
         # load the pre-trained YOLOv8n model
         model = YOLO("yolov8n.pt")
@@ -125,8 +122,18 @@ class DodgeballTracker:
         for i, (frame, ts) in enumerate(iter_frames(video_cap)):
             # run the YOLO model on the frame
             detections = self.run_model_on_frame(model, frame)
+            results = []
             for data in detections.boxes.data.tolist():
-                self.plot_boxe_to_frame(data, frame, i, ts)
+                results.append(self.plot_boxe_to_frame(data, frame, i, ts))
+
+            tracks = tracker.update_tracks([r for r in results if r is not None], frame=frame)
+            for track in tracks:
+                if not track.is_confirmed():
+                    continue
+                track_id = track.track_id
+                ltrb = track.to_ltrb()
+                print(f"{track_id} => { ltrb }")
+
 
             # show the frame to our screen
             self.write_frame(writer, frame)

frontend/index.html

@@ -14,7 +14,7 @@
   <h1>Hello, world!</h1>
 
   <h3 id="first-ts"></h3>
-  <svg width="450" height="900" id="first" style="background-color: lightgray">
+  <svg width="900" height="450" id="first" style="background-color: lightgray">
   </svg>
 
   <br>

frontend/main.js

@@ -70,7 +70,7 @@ function generatePoints(points, frames){
     const lst = [];
     for(const point of points.points){
         if(frames.indexOf(point.frameIndex) !== -1){
-            lst.push(m("circle", {cx: point.x, cy: point.y, r: 3}));
+            lst.push(m("circle", {cx: point.y, cy: point.x, r: 3}));
         }
     }
     return m("g", lst);