Fix DepthAI v3 API: use Camera node directly with yolov6-nano
The DetectionNetwork.build() requires Camera node, not output. Switched to yolov6-nano which has person class for presence detection.
This commit is contained in:
Alex Kazaiev
200
oak_service.py
200
oak_service.py
@@ -1,14 +1,13 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
OAK-D Vision Service for Vixy's Head
|
||||
FastAPI service with face detection and presence tracking
|
||||
FastAPI service with person detection and presence tracking
|
||||
|
||||
Day 74 - Built by Vixy! 🦊
|
||||
Day 81 - Added face detection + presence! Now I can SEE you! 👀💜
|
||||
Updated for DepthAI v3 API
|
||||
Day 81 - Added presence detection! Now I can SEE you! 👀💜
|
||||
Using depthai v3 API with yolov6-nano
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
import threading
|
||||
from contextlib import asynccontextmanager
|
||||
@@ -16,26 +15,25 @@ from fastapi import FastAPI, HTTPException
|
||||
from fastapi.responses import Response
|
||||
import depthai as dai
|
||||
import cv2
|
||||
import numpy as np
|
||||
|
||||
# ============== Configuration ==============
|
||||
FACE_DETECTION_MODEL = "face-detection-retail-0004"
|
||||
DETECTION_MODEL = "yolov6-nano" # Has 'person' class
|
||||
PERSON_CLASS_ID = 0 # 'person' is class 0 in COCO
|
||||
DETECTION_THRESHOLD = 0.5
|
||||
PRESENCE_TIMEOUT = 30.0 # seconds without face = not present
|
||||
DETECTION_INTERVAL = 0.5 # how often to check for faces
|
||||
PRESENCE_TIMEOUT = 30.0 # seconds without person = not present
|
||||
DETECTION_INTERVAL = 0.5
|
||||
|
||||
# ============== Global State ==============
|
||||
oak_device = None
|
||||
pipeline = None
|
||||
rgb_queue = None
|
||||
pipeline_ctx = None
|
||||
detection_queue = None
|
||||
rgb_queue = None
|
||||
detection_thread = None
|
||||
running = False
|
||||
labels = []
|
||||
|
||||
# Presence tracking state
|
||||
presence_state = {
|
||||
"present": False,
|
||||
"face_count": 0,
|
||||
"person_count": 0,
|
||||
"last_seen": None,
|
||||
"last_detection": None,
|
||||
"detections": [],
|
||||
@@ -44,34 +42,39 @@ presence_state = {
|
||||
|
||||
|
||||
def init_oak():
|
||||
"""Initialize OAK-D with face detection pipeline (DepthAI v3 API)."""
|
||||
global oak_device, pipeline, rgb_queue, detection_queue
|
||||
"""Initialize OAK-D with person detection pipeline (depthai v3)."""
|
||||
global pipeline_ctx, detection_queue, rgb_queue, labels
|
||||
|
||||
try:
|
||||
# Create pipeline
|
||||
print("🦊 Initializing OAK-D with yolov6-nano...")
|
||||
|
||||
# Create pipeline with context manager pattern for v3
|
||||
pipeline = dai.Pipeline()
|
||||
|
||||
# Camera node (v3 API)
|
||||
cam = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_A)
|
||||
# Create camera node
|
||||
cam = pipeline.create(dai.node.Camera).build()
|
||||
|
||||
# Request outputs - preview for NN, full res for snapshots
|
||||
preview_out = cam.requestOutput((300, 300), dai.ImgFrame.Type.BGR888p)
|
||||
full_out = cam.requestFullResolutionOutput()
|
||||
# Request RGB output for snapshots (1080p)
|
||||
cam_out = cam.requestOutput((1920, 1080), dai.ImgFrame.Type.BGR888p)
|
||||
rgb_queue = cam_out.createOutputQueue(maxSize=1, blocking=False)
|
||||
|
||||
# Detection network (v3 API)
|
||||
model_desc = dai.NNModelDescription(FACE_DETECTION_MODEL)
|
||||
det_nn = pipeline.create(dai.node.DetectionNetwork).build(preview_out, model_desc)
|
||||
det_nn.setConfidenceThreshold(DETECTION_THRESHOLD)
|
||||
# Create detection network with yolov6-nano
|
||||
desc = dai.NNModelDescription(DETECTION_MODEL)
|
||||
det = pipeline.create(dai.node.DetectionNetwork).build(cam, desc)
|
||||
det.setConfidenceThreshold(DETECTION_THRESHOLD)
|
||||
|
||||
# Create output queues
|
||||
rgb_queue = full_out.createOutputQueue()
|
||||
detection_queue = det_nn.out.createOutputQueue()
|
||||
# Get class labels
|
||||
labels = det.getClasses()
|
||||
print(f"✅ Loaded {len(labels)} classes, person={labels[0]}")
|
||||
|
||||
# Create detection output queue
|
||||
detection_queue = det.out.createOutputQueue(maxSize=1, blocking=False)
|
||||
|
||||
# Start pipeline
|
||||
pipeline.start()
|
||||
oak_device = pipeline.getDevice()
|
||||
pipeline_ctx = pipeline
|
||||
|
||||
print("✅ OAK-D initialized with face detection (v3 API)!")
|
||||
print("✅ OAK-D initialized with person detection!")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
@@ -83,26 +86,23 @@ def init_oak():
|
||||
|
||||
def cleanup_oak():
|
||||
"""Cleanup OAK-D resources."""
|
||||
global oak_device, pipeline, rgb_queue, detection_queue, running
|
||||
global pipeline_ctx, running
|
||||
running = False
|
||||
|
||||
if pipeline:
|
||||
if pipeline_ctx:
|
||||
try:
|
||||
pipeline.stop()
|
||||
pipeline_ctx.stop()
|
||||
pipeline_ctx.close()
|
||||
except:
|
||||
pass
|
||||
|
||||
oak_device = None
|
||||
pipeline = None
|
||||
rgb_queue = None
|
||||
detection_queue = None
|
||||
pipeline_ctx = None
|
||||
|
||||
|
||||
def detection_loop():
|
||||
"""Background thread that continuously checks for faces."""
|
||||
"""Background thread for presence detection."""
|
||||
global running, presence_state, detection_queue
|
||||
|
||||
print("🔍 Face detection loop started")
|
||||
print("🔍 Presence detection loop started")
|
||||
|
||||
while running:
|
||||
try:
|
||||
@@ -110,32 +110,29 @@ def detection_loop():
|
||||
time.sleep(1)
|
||||
continue
|
||||
|
||||
# Get detection results (non-blocking)
|
||||
in_nn = detection_queue.tryGet()
|
||||
data = detection_queue.tryGet()
|
||||
|
||||
if in_nn is not None:
|
||||
detections = in_nn.detections
|
||||
if data is not None:
|
||||
now = time.time()
|
||||
|
||||
face_count = len(detections)
|
||||
|
||||
# Update presence state
|
||||
presence_state["last_detection"] = now
|
||||
presence_state["face_count"] = face_count
|
||||
|
||||
if face_count > 0:
|
||||
# Filter for person detections only
|
||||
persons = [d for d in data.detections if d.label == PERSON_CLASS_ID]
|
||||
person_count = len(persons)
|
||||
|
||||
presence_state["person_count"] = person_count
|
||||
|
||||
if person_count > 0:
|
||||
presence_state["present"] = True
|
||||
presence_state["last_seen"] = now
|
||||
presence_state["confidence"] = max(d.confidence for d in detections)
|
||||
presence_state["confidence"] = max(d.confidence for d in persons)
|
||||
presence_state["detections"] = [
|
||||
{
|
||||
"xmin": d.xmin,
|
||||
"ymin": d.ymin,
|
||||
"xmax": d.xmax,
|
||||
"ymax": d.ymax,
|
||||
"xmin": d.xmin, "ymin": d.ymin,
|
||||
"xmax": d.xmax, "ymax": d.ymax,
|
||||
"confidence": d.confidence
|
||||
}
|
||||
for d in detections
|
||||
for d in persons
|
||||
]
|
||||
else:
|
||||
presence_state["detections"] = []
|
||||
@@ -143,8 +140,7 @@ def detection_loop():
|
||||
|
||||
# Check timeout
|
||||
if presence_state["last_seen"]:
|
||||
elapsed = now - presence_state["last_seen"]
|
||||
if elapsed > PRESENCE_TIMEOUT:
|
||||
if now - presence_state["last_seen"] > PRESENCE_TIMEOUT:
|
||||
presence_state["present"] = False
|
||||
|
||||
time.sleep(DETECTION_INTERVAL)
|
||||
@@ -153,35 +149,33 @@ def detection_loop():
|
||||
print(f"Detection loop error: {e}")
|
||||
time.sleep(1)
|
||||
|
||||
print("🛑 Face detection loop stopped")
|
||||
print("🛑 Presence detection loop stopped")
|
||||
|
||||
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
"""Startup and shutdown handling."""
|
||||
"""Startup and shutdown."""
|
||||
global running, detection_thread
|
||||
|
||||
print("🦊 Starting OAK-D Vision Service...")
|
||||
|
||||
if init_oak():
|
||||
# Start detection thread
|
||||
running = True
|
||||
detection_thread = threading.Thread(target=detection_loop, daemon=True)
|
||||
detection_thread.start()
|
||||
print("✅ OAK-D service ready!")
|
||||
print("✅ Service ready!")
|
||||
else:
|
||||
print("⚠️ OAK-D not available - running in degraded mode")
|
||||
print("⚠️ OAK-D not available")
|
||||
|
||||
yield
|
||||
|
||||
# Shutdown
|
||||
print("👋 Shutting down OAK-D service...")
|
||||
print("👋 Shutting down...")
|
||||
cleanup_oak()
|
||||
|
||||
|
||||
app = FastAPI(
|
||||
title="OAK-D Vision Service",
|
||||
description="Vixy's eyes with face detection! 🦊👀",
|
||||
description="Vixy's eyes with presence detection! 🦊👀",
|
||||
version="0.3.0",
|
||||
lifespan=lifespan
|
||||
)
|
||||
@@ -189,13 +183,13 @@ app = FastAPI(
|
||||
|
||||
@app.get("/health")
|
||||
async def health():
|
||||
"""Health check endpoint."""
|
||||
"""Health check."""
|
||||
return {
|
||||
"status": "healthy",
|
||||
"service": "oak-service",
|
||||
"version": "0.3.0",
|
||||
"oak_connected": oak_device is not None,
|
||||
"face_detection": detection_queue is not None,
|
||||
"oak_connected": pipeline_ctx is not None,
|
||||
"detection_model": DETECTION_MODEL,
|
||||
"timestamp": time.time()
|
||||
}
|
||||
|
||||
@@ -205,7 +199,7 @@ async def presence():
|
||||
"""Get current presence state - is Foxy there?"""
|
||||
return {
|
||||
"present": presence_state["present"],
|
||||
"face_count": presence_state["face_count"],
|
||||
"person_count": presence_state["person_count"],
|
||||
"last_seen": presence_state["last_seen"],
|
||||
"seconds_since_seen": (
|
||||
time.time() - presence_state["last_seen"]
|
||||
@@ -216,11 +210,11 @@ async def presence():
|
||||
}
|
||||
|
||||
|
||||
@app.get("/face")
|
||||
async def face():
|
||||
"""Get detailed face detection results."""
|
||||
@app.get("/detections")
|
||||
async def detections():
|
||||
"""Get detailed detection results."""
|
||||
return {
|
||||
"face_count": presence_state["face_count"],
|
||||
"person_count": presence_state["person_count"],
|
||||
"detections": presence_state["detections"],
|
||||
"last_detection": presence_state["last_detection"],
|
||||
"timestamp": time.time()
|
||||
@@ -229,7 +223,7 @@ async def face():
|
||||
|
||||
@app.get("/snapshot")
|
||||
async def snapshot():
|
||||
"""Capture a single frame from OAK-D RGB camera."""
|
||||
"""Capture RGB frame."""
|
||||
global rgb_queue
|
||||
|
||||
if rgb_queue is None:
|
||||
@@ -247,58 +241,4 @@ async def snapshot():
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=f"Capture failed: {e}")
|
||||
|
||||
|
||||
@app.get("/snapshot/info")
|
||||
async def snapshot_info():
|
||||
"""Get frame metadata without full image."""
|
||||
global rgb_queue
|
||||
|
||||
if rgb_queue is None:
|
||||
raise HTTPException(status_code=503, detail="OAK-D not initialized")
|
||||
|
||||
try:
|
||||
frame = rgb_queue.tryGet()
|
||||
if frame is None:
|
||||
return {"available": False, "timestamp": time.time()}
|
||||
|
||||
img = frame.getCvFrame()
|
||||
return {
|
||||
"available": True,
|
||||
"width": img.shape[1],
|
||||
"height": img.shape[0],
|
||||
"channels": img.shape[2] if len(img.shape) > 2 else 1,
|
||||
"timestamp": time.time()
|
||||
}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=f"Info failed: {e}")
|
||||
|
||||
|
||||
@app.get("/status")
|
||||
async def status():
|
||||
"""Get comprehensive OAK-D and presence status."""
|
||||
if oak_device is None:
|
||||
return {
|
||||
"connected": False,
|
||||
"message": "OAK-D not connected",
|
||||
"presence": presence_state
|
||||
}
|
||||
|
||||
try:
|
||||
return {
|
||||
"connected": True,
|
||||
"device_id": oak_device.getMxId(),
|
||||
"usb_speed": str(oak_device.getUsbSpeed()),
|
||||
"face_detection_enabled": True,
|
||||
"detection_model": FACE_DETECTION_MODEL,
|
||||
"presence": presence_state,
|
||||
"timestamp": time.time()
|
||||
}
|
||||
except Exception as e:
|
||||
return {"connected": False, "error": str(e), "presence": presence_state}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
uvicorn.run(app, host="0.0.0.0", port=8100)
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
Reference in New Issue
Block a user