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"""
MorphGuard Drone Simulation Test
Simulates a companion computer sending face crops to the ground station.
This script allows testing the ground station API WITHOUT the actual Pi hardware.
It uses your computer's webcam to detect faces and sends them to MorphGuard.
Usage:
python test_drone_simulation.py [--server URL] [--camera N] [--interval SECONDS]
Examples:
# Use default settings (localhost, camera 0, 2 second interval)
python test_drone_simulation.py
# Connect to specific server
python test_drone_simulation.py --server http://192.168.200.112:5000
# Use different camera
python test_drone_simulation.py --camera 1
"""
import os
import sys
import time
import json
import base64
import argparse
import random
from datetime import datetime
from io import BytesIO
import cv2
import numpy as np
import requests
# Simulated GPS coordinates (Austin, TX area)
SIMULATED_GPS = {
"lat": 30.2672 + random.uniform(-0.01, 0.01),
"lon": -97.7431 + random.uniform(-0.01, 0.01),
"alt": 100.0 + random.uniform(-10, 10)
}
class DroneSimulator:
"""Simulates a drone companion computer for testing."""
def __init__(self, server_url: str, camera_id: int = 0):
self.server_url = server_url.rstrip('/')
self.camera_id = camera_id
self.cap = None
self.face_cascade = None
self.connected = False
self.faces_sent = 0
self.session_start = None
def initialize(self) -> bool:
"""Initialize camera and face detector."""
print(f"π Drone Simulator Starting...")
print(f" Server: {self.server_url}")
print(f" Camera: {self.camera_id}")
print()
# Initialize camera
print("π· Initializing camera...")
self.cap = cv2.VideoCapture(self.camera_id)
if not self.cap.isOpened():
print("β Failed to open camera!")
return False
# Set camera resolution
self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
print(f" Resolution: {int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))}x{int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))}")
# Initialize face detector
print("π Loading face detector...")
cascade_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
self.face_cascade = cv2.CascadeClassifier(cascade_path)
if self.face_cascade.empty():
print("β Failed to load face cascade!")
return False
print(" Using OpenCV Haar Cascade (simulating Hailo)")
print()
return True
def connect(self) -> bool:
"""Register with ground station."""
print("π‘ Connecting to ground station...")
try:
response = requests.post(
f"{self.server_url}/api/drone/connect",
json={
"companion_ip": "SIMULATION",
"hardware": "Simulated Pi5 + Hailo 26 TOPS",
"model": "opencv_haar_cascade (simulation)"
},
timeout=5
)
if response.status_code == 200:
data = response.json()
print(f" β
Connected: {data.get('message')}")
self.connected = True
self.session_start = datetime.now()
return True
else:
print(f" β Failed: HTTP {response.status_code}")
return False
except requests.exceptions.RequestException as e:
print(f" β Connection error: {e}")
return False
def disconnect(self):
"""Disconnect from ground station."""
if self.connected:
try:
requests.post(f"{self.server_url}/api/drone/disconnect", timeout=5)
print("π Disconnected from ground station")
except:
pass
if self.cap:
self.cap.release()
self.connected = False
def detect_faces(self, frame: np.ndarray) -> list:
"""Detect faces in frame using OpenCV."""
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = self.face_cascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(60, 60)
)
return list(faces)
def crop_face(self, frame: np.ndarray, bbox: tuple, margin: float = 0.2) -> np.ndarray:
"""Crop face from frame with margin."""
x, y, w, h = bbox
# Add margin
margin_x = int(w * margin)
margin_y = int(h * margin)
x1 = max(0, x - margin_x)
y1 = max(0, y - margin_y)
x2 = min(frame.shape[1], x + w + margin_x)
y2 = min(frame.shape[0], y + h + margin_y)
return frame[y1:y2, x1:x2].copy()
def encode_crop(self, crop: np.ndarray) -> str:
"""Encode face crop to base64 JPEG."""
# Resize if too large
max_size = 256
h, w = crop.shape[:2]
if max(h, w) > max_size:
scale = max_size / max(h, w)
crop = cv2.resize(crop, (int(w * scale), int(h * scale)))
# Encode
_, buffer = cv2.imencode('.jpg', crop, [cv2.IMWRITE_JPEG_QUALITY, 85])
return base64.b64encode(buffer).decode('utf-8')
def send_face_crop(self, crop: np.ndarray, bbox: tuple, confidence: float) -> dict:
"""Send face crop to ground station for analysis."""
# Update simulated GPS (slight drift)
gps = {
"lat": SIMULATED_GPS["lat"] + random.uniform(-0.0001, 0.0001),
"lon": SIMULATED_GPS["lon"] + random.uniform(-0.0001, 0.0001),
"alt": SIMULATED_GPS["alt"] + random.uniform(-1, 1)
}
payload = {
"crop_base64": self.encode_crop(crop),
"confidence": confidence,
"bbox": list(bbox),
"gps_lat": gps["lat"],
"gps_lon": gps["lon"],
"gps_alt": gps["alt"],
"heading": random.uniform(0, 360),
"flight_mode": "SIMULATION"
}
try:
response = requests.post(
f"{self.server_url}/api/drone/analyze",
json=payload,
timeout=10
)
if response.status_code == 200:
return response.json()
else:
return {"error": f"HTTP {response.status_code}"}
except requests.exceptions.RequestException as e:
return {"error": str(e)}
def send_heartbeat(self, fps: float = 30.0):
"""Send heartbeat with telemetry."""
try:
requests.post(
f"{self.server_url}/api/drone/heartbeat",
json={
"fps": fps,
"gps": SIMULATED_GPS,
"battery": random.randint(70, 100)
},
timeout=2
)
except:
pass
def run(self, interval: float = 2.0, show_preview: bool = True):
"""
Main simulation loop.
Args:
interval: Seconds between sending face crops
show_preview: Show camera preview window
"""
print()
print("=" * 50)
print("π DRONE SIMULATION RUNNING")
print("=" * 50)
print()
print("Press 'Q' to quit (in preview window)")
print("Press Ctrl+C to stop")
print()
last_send_time = 0
frame_count = 0
fps_start = time.time()
current_fps = 0
try:
while True:
# Capture frame
ret, frame = self.cap.read()
if not ret:
print("β οΈ Failed to capture frame")
time.sleep(0.1)
continue
# FPS calculation
frame_count += 1
elapsed = time.time() - fps_start
if elapsed >= 1.0:
current_fps = frame_count / elapsed
frame_count = 0
fps_start = time.time()
self.send_heartbeat(current_fps)
# Detect faces
faces = self.detect_faces(frame)
# Draw boxes on preview
display_frame = frame.copy()
for (x, y, w, h) in faces:
cv2.rectangle(display_frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
# Add status overlay
status_text = f"FPS: {current_fps:.1f} | Faces: {len(faces)} | Sent: {self.faces_sent}"
cv2.putText(display_frame, status_text, (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
gps_text = f"GPS: {SIMULATED_GPS['lat']:.4f}, {SIMULATED_GPS['lon']:.4f}"
cv2.putText(display_frame, gps_text, (10, 60),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 2)
# Show preview
if show_preview:
cv2.imshow("Drone Simulation - MorphGuard", display_frame)
key = cv2.waitKey(1) & 0xFF
if key == ord('q'):
break
# Send face crops at interval
current_time = time.time()
if faces is not None and len(faces) > 0 and (current_time - last_send_time) >= interval:
# Send first detected face
x, y, w, h = faces[0]
crop = self.crop_face(frame, (x, y, w, h))
confidence = 0.9 + random.uniform(0, 0.09) # Simulated confidence
print(f"\nπ€ Sending face crop to ground station...")
print(f" Size: {crop.shape[1]}x{crop.shape[0]}")
print(f" Confidence: {confidence:.2%}")
result = self.send_face_crop(crop, (x, y, w, h), confidence)
if "error" in result:
print(f" β Error: {result['error']}")
else:
is_morph = result.get("is_morph", False)
morph_conf = result.get("confidence", 0)
print(f" β
Result: {'MORPH DETECTED!' if is_morph else 'Genuine'}")
print(f" π Morph Confidence: {morph_conf:.2%}")
self.faces_sent += 1
last_send_time = current_time
time.sleep(0.01) # Small delay to prevent CPU overload
except KeyboardInterrupt:
print("\n\nπ Simulation stopped by user")
finally:
cv2.destroyAllWindows()
self.disconnect()
# Print summary
print()
print("=" * 50)
print("π SIMULATION SUMMARY")
print("=" * 50)
if self.session_start:
duration = datetime.now() - self.session_start
print(f" Duration: {duration}")
print(f" Face crops sent: {self.faces_sent}")
print()
def main():
parser = argparse.ArgumentParser(description="Drone Simulation Test for MorphGuard")
parser.add_argument("--server", "-s", default="http://192.168.200.112:5000",
help="Ground station URL (default: http://192.168.200.112:5000)")
parser.add_argument("--camera", "-c", type=int, default=0,
help="Camera ID (default: 0)")
parser.add_argument("--interval", "-i", type=float, default=2.0,
help="Seconds between sending crops (default: 2.0)")
parser.add_argument("--no-preview", action="store_true",
help="Disable camera preview window")
args = parser.parse_args()
# Create simulator
sim = DroneSimulator(args.server, args.camera)
# Initialize
if not sim.initialize():
print("\nβ Initialization failed!")
sys.exit(1)
# Connect
if not sim.connect():
print("\nβ Connection failed!")
sys.exit(1)
# Run simulation
sim.run(interval=args.interval, show_preview=not args.no_preview)
if __name__ == "__main__":
main()
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