POC

README.md

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+# Foobar
+
+Foobar is a Python library for dealing with word pluralization.
+
+## Installation
+
+Use the package manager [pip](https://pip.pypa.io/en/stable/) to install foobar.
+
+```bash
+python3 -m venv venv3
+source venv3/bin/activate
+pip install -r requirements.txt
+# adapt paths inside feature_matching.py
+python feature_matching.py
+```
+
+

acquire-camera.py

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+import cv2
+import dlib
+import time  # To measure time for FPS calculation
+
+# GStreamer pipeline to acquire video from the CSI camera (Jetson Nano)
+def gstreamer_pipeline(
+    sensor_id=0,
+    capture_width=1280,
+    capture_height=720,
+    display_width=640,
+    display_height=360,
+    framerate=15,
+    flip_method=0,
+):
+    return (
+        f"nvarguscamerasrc sensor-id={sensor_id} ! "
+        f"video/x-raw(memory:NVMM), width=(int){capture_width}, height=(int){capture_height}, "
+        f"format=(string)NV12, framerate=(fraction){framerate}/1 ! "
+        f"nvvidconv flip-method={flip_method} ! "
+        f"video/x-raw, width=(int){display_width}, height=(int){display_height}, format=(string)BGRx ! "
+        f"videoconvert ! video/x-raw, format=(string)BGR ! appsink"
+    )
+
+# Capture from the camera using OpenCV and start tracking
+cap = cv2.VideoCapture(gstreamer_pipeline(), cv2.CAP_GSTREAMER)
+
+if not cap.isOpened():
+    print("Unable to open camera")
+else:
+    # Read the first frame to allow user to draw a bounding box
+    ret, frame = cap.read()
+    if not ret:
+        print("Failed to grab the initial frame")
+        cap.release()
+
+    # Let the user draw the initial bounding box
+    bbox = cv2.selectROI("Select ROI", frame, fromCenter=False, showCrosshair=True)
+
+    # Initialize Dlib correlation tracker
+    tracker = dlib.correlation_tracker()
+    tracker.start_track(frame, dlib.rectangle(bbox[0], bbox[1], bbox[0] + bbox[2], bbox[1] + bbox[3]))
+
+    img_counter = 0  # To count frames and name images
+    frame_counter = 0  # To track the number of frames
+    start_time = time.time()  # Start time for FPS calculation
+
+    try:
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                print("Failed to grab frame")
+                break
+
+            # Start measuring time per frame
+            frame_start_time = time.time()
+
+            # Update the tracker with the current frame
+            tracker.update(frame)
+            pos = tracker.get_position()
+
+            # Extract the bounding box from the tracker
+            x1, y1, x2, y2 = int(pos.left()), int(pos.top()), int(pos.right()), int(pos.bottom())
+
+            # Draw the updated tracking bounding box on the frame
+            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+
+            # Show the frame with the tracking rectangle
+            cv2.imshow("Tracking", frame)
+
+            # Save every 10th frame
+            if frame_counter % 10 == 0:
+                img_name = f"tracked_frame_{img_counter}.jpg"
+                cv2.imwrite(img_name, frame)
+                print(f"Saved {img_name}")
+                img_counter += 1
+
+            # Calculate and print FPS
+            frame_time = time.time() - frame_start_time
+            fps = 1.0 / frame_time
+            print(f"FPS: {fps:.2f}")
+
+            frame_counter += 1
+
+            # Exit if 'q' is pressed
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+
+    except KeyboardInterrupt:
+        print("Tracking interrupted by user")
+
+    cap.release()
+    cv2.destroyAllWindows()
+
+# Calculate and print average FPS over all frames
+end_time = time.time()
+total_time = end_time - start_time
+average_fps = frame_counter / total_time
+print(f"Average FPS: {average_fps:.2f}")
+
+print("Finished tracking")