first commit

Dockerfile

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+
+FROM python:3.11-slim
+
+# Install system deps for OpenCV + ffmpeg
+RUN apt-get update && apt-get install -y \
+    ffmpeg \
+    libgl1 \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Python deps
+RUN pip install --no-cache-dir \
+    opencv-python-headless \
+    numpy \
+    requests
+
+WORKDIR /app
+
+COPY desk_presence.py /app/desk_presence.py
+
+CMD ["python", "/app/desk_presence.py"]

desk_presence.py

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+#!/usr/bin/env python3
+import cv2
+import numpy as np
+import subprocess
+import os
+import json
+import time
+import requests
+
+# ---------- Camera ----------
+CAMERA = os.environ.get("CAMERA", "/dev/video0")
+TMP_IMG = "/tmp/desk_current.jpg"
+PREV_IMG = "/tmp/desk_prev.jpg"
+
+# ---------- State files ----------
+STATE_FILE = "/tmp/desk_presence_score.json"
+HA_STATE_FILE = "/tmp/desk_presence_last_ha.json"
+LIGHT_COOLDOWN_FILE = "/tmp/desk_light_cooldown.json"
+
+# ---------- Haar cascade ----------
+FACE_CASCADE = cv2.CascadeClassifier(
+    "/usr/share/opencv4/haarcascades/haarcascade_frontalface_default.xml"
+)
+
+# ---------- Home Assistant ----------
+HA_URL = os.environ.get("HA_URL", "http://192.168.0.202:8123")
+HA_ENTITY_ID = os.environ.get("HA_ENTITY_ID", "binary_sensor.desk_presence_vision")
+HA_TOKEN = os.environ.get("HA_TOKEN")
+
+# ---------- Presence logic ----------
+MAX_SCORE = 5
+FACE_BOOST = 2
+MOTION_BOOST = 1
+DECAY = 1
+
+MOTION_AREA_THRESHOLD = 4000
+LIGHT_COOLDOWN_SECONDS = 15
+
+# Adaptive delays (seconds)
+SCORE_DELAYS = {
+    0: 30,
+    1: 15,
+    2: 60,
+    3: 120,
+    4: 240,
+    5: 480,
+}
+
+# --------------------------------------------------
+
+
+def safe_delete(path):
+    try:
+        if os.path.exists(path):
+            os.remove(path)
+            print(f"[CLEANUP] Deleted {path}")
+    except Exception as e:
+        print(f"[WARN] Could not delete {path}: {e}")
+
+
+def capture():
+    subprocess.run(
+        [
+            "ffmpeg",
+            "-loglevel",
+            "quiet",
+            "-f",
+            "v4l2",
+            "-i",
+            CAMERA,
+            "-frames:v",
+            "1",
+            TMP_IMG,
+        ],
+        check=True,
+    )
+
+
+def load_json(path, default):
+    if not os.path.exists(path):
+        return default
+    try:
+        return json.load(open(path))
+    except Exception:
+        return default
+
+
+def save_json(path, data):
+    json.dump(data, open(path, "w"))
+
+
+# ---------- Presence score ----------
+def load_score():
+    return load_json(STATE_FILE, {}).get("score", 0)
+
+
+def save_score(score):
+    save_json(STATE_FILE, {"score": score})
+
+
+# ---------- HA state ----------
+def load_last_ha_state():
+    return load_json(HA_STATE_FILE, {}).get("state")
+
+
+def save_last_ha_state(state):
+    save_json(HA_STATE_FILE, {"state": state})
+
+
+def record_light_off_event():
+    save_json(LIGHT_COOLDOWN_FILE, {"ts": time.time()})
+
+
+def ignore_motion_due_to_light():
+    data = load_json(LIGHT_COOLDOWN_FILE, {})
+    ts = data.get("ts", 0)
+    remaining = LIGHT_COOLDOWN_SECONDS - (time.time() - ts)
+    if remaining > 0:
+        print(f"[INFO] Ignoring motion for {remaining:.1f}s (light cooldown)")
+        return True
+    return False
+
+
+def send_to_ha(present):
+    new_state = "on" if present else "off"
+    last_state = load_last_ha_state()
+
+    if new_state == last_state:
+        print("[HA] No state change")
+        return
+
+    headers = {
+        "Authorization": f"Bearer {HA_TOKEN}",
+        "Content-Type": "application/json",
+    }
+
+    payload = {
+        "state": new_state,
+        "attributes": {
+            "friendly_name": "Desk Presence (Vision)",
+            "source": "snapshot_camera",
+        },
+    }
+
+    try:
+        r = requests.post(
+            f"{HA_URL}/api/states/{HA_ENTITY_ID}",
+            headers=headers,
+            json=payload,
+            timeout=5,
+        )
+
+        if r.status_code in (200, 201):
+            print(f"[HA] Updated state → {new_state}")
+            save_last_ha_state(new_state)
+
+            if new_state == "off":
+                record_light_off_event()
+        else:
+            print(f"[HA] Error {r.status_code}: {r.text}")
+
+    except Exception as e:
+        print(f"[HA] Connection failed: {e}")
+
+
+# ---------- Detection ----------
+def detect_face(gray):
+    faces = FACE_CASCADE.detectMultiScale(
+        gray, scaleFactor=1.2, minNeighbors=4, minSize=(60, 60)
+    )
+    return len(faces) > 0
+
+
+def detect_motion(gray):
+    if ignore_motion_due_to_light():
+        return False
+
+    if not os.path.exists(PREV_IMG):
+        cv2.imwrite(PREV_IMG, gray)
+        return False
+
+    prev = cv2.imread(PREV_IMG, cv2.IMREAD_GRAYSCALE)
+    cv2.imwrite(PREV_IMG, gray)
+
+    diff = cv2.absdiff(prev, gray)
+    _, thresh = cv2.threshold(diff, 30, 255, cv2.THRESH_BINARY)
+
+    kernel = np.ones((5, 5), np.uint8)
+    thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
+
+    area = cv2.countNonZero(thresh)
+    print("[DEBUG] Motion area:", area)
+
+    return area > MOTION_AREA_THRESHOLD
+
+
+def get_delay(score):
+    return SCORE_DELAYS.get(score, 30) / 10
+
+
+# ---------- Main loop ----------
+def main_loop():
+    print("=== SNAPSHOT DESK PRESENCE (STABLE) ===")
+
+    while True:
+        try:
+            capture()
+
+            frame = cv2.imread(TMP_IMG)
+            if frame is None:
+                print("[ERROR] Frame read failed")
+                time.sleep(30)
+                continue
+
+            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+            face = detect_face(gray)
+            motion = detect_motion(gray)
+
+            score = load_score()
+            print("\nPrevious score:", score)
+
+            if face:
+                score += FACE_BOOST
+                print("Face detected → +", FACE_BOOST)
+            elif motion:
+                score += MOTION_BOOST
+                print("Motion detected → +", MOTION_BOOST)
+            else:
+                score -= DECAY
+                print("No signal → -", DECAY)
+
+            score = max(0, min(MAX_SCORE, score))
+            save_score(score)
+
+            present = score > 0
+            print("Current score:", score)
+            print("PRESENCE:", "YES" if present else "NO")
+
+            send_to_ha(present)
+
+        finally:
+            safe_delete(TMP_IMG)
+
+        delay = get_delay(score)
+        print(f"[SLEEP] Next check in {delay}s")
+        time.sleep(delay)
+
+
+if __name__ == "__main__":
+    main_loop()

readme.md

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+# Desk Presence Detection (Snapshot-Based, Home Assistant)
+
+This project provides a low-CPU desk presence detection system using a webcam and snapshot-based computer vision. It is designed to work reliably on weak hardware without running continuous video inference.
+
+Presence is detected using:
+
+- Face detection (Haar cascade)
+- Frame-to-frame motion detection
+- A confidence score with decay
+- A cooldown to prevent feedback loops caused by lights turning on or off
+- The detected presence is published to Home Assistant as a binary_sensor.
+
+## Installation
+
+### 1. Clone
+
+### 2. Build the image
+
+```sh
+docker build -t desk-presence .
+```
+
+### 3. Home Assistant Setup
+
+#### A. Create Long Lived Access Token
+
+#### B. Run the container
+
+```sh
+docker run -d \
+  --name desk-presence \
+  --restart unless-stopped \
+  --device /dev/video0:/dev/video0 \
+  -e HA_URL="http://192.168.0.202:8123" \
+  -e HA_ENTITY_ID="binary_sensor.desk_presence_vision" \
+  -e HA_TOKEN="YOUR_LONG_LIVED_TOKEN" \
+  -e CAMERA="/dev/video0"
+  desk-presence
+
+```