Merge branch 'main' into python-processing-test

services/multi_tracker.py

@@ -3,6 +3,7 @@ import cv2
 import numpy as np
 import logging
 from ultralytics import YOLO
+from pathlib import Path
 
 logger = logging.getLogger(__name__)
 
@@ -11,8 +12,13 @@ class MultiTracker:
         logger.info("Initializing Multi Tracker (Group Centroid)")
         
         # Determine paths
-        base_dir = "/Users/adisankarlalan/Documents/GitHub/afs-fl/Model"
-        detector_model_path = os.path.join(base_dir, "yolov8n-face.pt")
+
+        # Get the directory containing the current script (server.py)
+        base_dir = Path(__file__).parent.parent
+
+        # Go up one level (to afs/), then into Model/
+        detector_model_path = base_dir.parent / "Model" / "yolov8n-face.pt"
+        print(detector_model_path,"de")
         
         try:
             self.model = YOLO(detector_model_path)

services/single_tracker.py

@@ -1,10 +1,12 @@
 import os
+from pathlib import Path
 import cv2
 import pickle
 import numpy as np
 import logging
 from ultralytics import YOLO
 from deepface import DeepFace
+from pathlib import Path
 
 logger = logging.getLogger(__name__)
 
@@ -13,7 +15,11 @@ class SingleTracker:
         logger.info("Initializing Single Tracker (Face Priority)")
         
         # Configuration matches face_model.py
-        self.base_dir = "/Users/adisankarlalan/Documents/GitHub/afs-fl/Model"
+        # self.base_dir = "/Users/adisankarlalan/Documents/GitHub/afs-fl/Model"
+        base_dir = Path(__file__).parent
+        self.base_dir = base_dir.parent.parent / "Model" 
+        print(self.base_dir,"base")
+
         self.reference_video_path = os.path.join(self.base_dir, 'my_scan.mp4')
         self.model_name = "ArcFace"
         self.detector_model_path = os.path.join(self.base_dir, "yolov8n-face.pt")

test/test_cv.py

@@ -0,0 +1,2 @@
+import cv2
+print(cv2.__version__)

test/test_inference.py

@@ -0,0 +1,21 @@
+from services.single_tracker import SingleTracker
+import cv2
+import json
+
+tracker = SingleTracker()
+cap = cv2.VideoCapture("Model/my_scan.mp4")
+frames = 0
+
+print("Main User embeddings:", bool(tracker.main_user_embeddings))
+print("Len:", len(tracker.main_user_embeddings))
+
+while cap.isOpened() and frames < 10:
+    ret, frame = cap.read()
+    if not ret: break
+    
+    res = tracker.process_frame(frame)
+    if res["boxes"]:
+        print(f"Frame {frames} Boxes: {len(res['boxes'])}")
+    else:
+        print(f"Frame {frames}: No Output. Err: {res.get('error')}")
+    frames += 1

test/test_thread.py

@@ -0,0 +1,24 @@
+from services.single_tracker import SingleTracker
+from concurrent.futures import ThreadPoolExecutor
+import cv2
+import asyncio
+
+async def test():
+    tracker = SingleTracker()
+    frame = cv2.imread("Model/Adi.jpg")
+    if frame is None:
+        print("Failed to load image")
+        return
+        
+    executor = ThreadPoolExecutor(max_workers=4)
+    
+    def run_inference():
+        res = tracker.process_frame(frame)
+        print("Tracker Output:", res)
+        
+    print("Running in executor...")
+    await asyncio.get_event_loop().run_in_executor(executor, run_inference)
+    print("Done")
+
+if __name__ == "__main__":
+    asyncio.run(test())

test/test_ws.py

@@ -0,0 +1,17 @@
+import asyncio
+import websockets
+import json
+import cv2
+
+async def test():
+    async with websockets.connect("ws://localhost:8000/ws") as ws:
+        cap = cv2.VideoCapture("Model/my_scan.mp4")
+        for i in range(15):
+            ret, frame = cap.read()
+            if not ret: break
+            ret, buffer = cv2.imencode('.jpg', frame)
+            await ws.send(buffer.tobytes())
+            res = await ws.recv()
+            print("Received:", res)
+
+asyncio.run(test())