v1.13.0

CHANGELOG.md

@@ -1,3 +1,31 @@
+## [1.13.0-beta.4](https://github.com/jakowenko/double-take/compare/v1.13.0-beta.3...v1.13.0-beta.4) (2022-10-21)
+
+
+### Features
+
+* **mqtt & api:** total count for person, match, miss, and unknown ([#223](https://github.com/jakowenko/double-take/issues/223)) ([2bf4406](https://github.com/jakowenko/double-take/commit/2bf4406aa7e92b1b255e95475b5393d7345207e4))
+
+## [1.13.0-beta.3](https://github.com/jakowenko/double-take/compare/v1.13.0-beta.2...v1.13.0-beta.3) (2022-10-20)
+
+
+### Bug Fixes
+
+* remove non alphanumeric characters from MQTT topic names ([#239](https://github.com/jakowenko/double-take/issues/239)) ([885d8a1](https://github.com/jakowenko/double-take/commit/885d8a112ae34e0f5632f3012a4ed63851cfa2ac))
+
+## [1.13.0-beta.2](https://github.com/jakowenko/double-take/compare/v1.13.0-beta.1...v1.13.0-beta.2) (2022-10-20)
+
+
+### Features
+
+* support for MQTT TLS ([#241](https://github.com/jakowenko/double-take/issues/241)) ([7f37b78](https://github.com/jakowenko/double-take/commit/7f37b78d45f879d782d493595d76a14dbd31b7b5))
+
+## [1.13.0-beta.1](https://github.com/jakowenko/double-take/compare/v1.12.1...v1.13.0-beta.1) (2022-10-19)
+
+
+### Features
+
+* frigate matches below an area target ([3365bc7](https://github.com/jakowenko/double-take/commit/3365bc78f893081fe69d784e3d6f968d3be561ce))
+
 ## [1.12.1](https://github.com/jakowenko/double-take/compare/v1.12.0...v1.12.1) (2022-06-17)
 
 

README.md

@@ -33,14 +33,14 @@ There's a lot of great open source software to perform facial recognition, but e
 
 ### Supported Detectors
 
-- [CompreFace](https://github.com/exadel-inc/CompreFace) v0.5.0-1.0.0
+- [CompreFace](https://github.com/exadel-inc/CompreFace)
 - [Amazon Rekognition](https://aws.amazon.com/rekognition)
-- [DeepStack](https://deepstack.cc) v2021.02.1-2022.01.01
+- [DeepStack](https://deepstack.cc)
 - [Facebox](https://machinebox.io)
 
 ### Supported NVRs
 
-- [Frigate](https://github.com/blakeblackshear/frigate) v0.8.0-0.11.0
+- [Frigate](https://github.com/blakeblackshear/frigate)
 
 ## Integrations
 
@@ -152,7 +152,8 @@ mqtt:
     "type": "latest",
     "duration": 0.28,
     "detector": "compreface",
-    "filename": "2f07d1ad-9252-43fd-9233-2786a36a15a9.jpg"
+    "filename": "2f07d1ad-9252-43fd-9233-2786a36a15a9.jpg",
+    "base64": null
   }
 }
 ```
@@ -176,9 +177,13 @@ mqtt:
       "type": "manual",
       "duration": 0.8,
       "detector": "compreface",
-      "filename": "4d8a14a9-96c5-4691-979b-0f2325311453.jpg"
+      "filename": "dcb772de-d8e8-4074-9bce-15dbba5955c5.jpg",
+      "base64": null
     }
-  ]
+  ],
+  "misses": [],
+  "unknowns": [],
+  "counts": { "person": 1, "match": 1, "miss": 0, "unknown": 0 }
 }
 ```
 
@@ -280,6 +285,16 @@ mqtt:
   password:
   client_id:
 
+  tls:
+    # cert chains in PEM format: /path/to/client.crt
+    cert:
+    # private keys in PEM format: /path/to/client.key
+    key:
+    # optionally override the trusted CA certificates: /path/to/ca.crt
+    ca:
+    # if true the server will reject any connection which is not authorized with the list of supplied CAs
+    reject_unauthorized: false
+
   topics:
     # mqtt topic for frigate message subscription
     frigate: frigate/events
@@ -338,6 +353,11 @@ frigate:
   # if set to false all image attempts will be processed before determining the best match
   stop_on_match: true
 
+  # ignore detected areas so small that face recognition would be difficult
+  # quadrupling the min_area of the detector is a good start
+  # does not apply to MQTT events
+  min_area: 0
+
   # object labels that are allowed for facial recognition
   labels:
     - person

api/package.json

@@ -1,6 +1,6 @@
 {
   "name": "double-take-api",
-  "version": "1.12.1",
+  "version": "1.13.0-beta.4",
   "description": "Unified UI and API for processing and training images for facial recognition",
   "scripts": {
     "start": "node server.js",

api/src/constants/config.js

@@ -134,6 +134,7 @@ module.exports.frigate = ({ id, camera, topic }) => {
     attempts,
     image,
     stop_on_match: stopOnMatch,
+    min_area: minArea,
   } = JSON.parse(JSON.stringify(CONFIG.frigate));
   const { masks } = module.exports;
 
@@ -152,5 +153,6 @@ module.exports.frigate = ({ id, camera, topic }) => {
     url: { frigate: url, snapshot, latest },
     attempts,
     stop_on_match: stopOnMatch,
+    min_area: minArea,
   });
 };

api/src/constants/defaults.js

@@ -27,8 +27,12 @@ module.exports = {
     labels: ['person'],
     update_sub_labels: false,
     stop_on_match: true,
+    min_area: 0,
   },
   mqtt: {
+    tls: {
+      reject_unauthorized: false,
+    },
     topics: {
       frigate: 'frigate/events',
       matches: 'double-take/matches',

api/src/controllers/recognize.controller.js

@@ -58,8 +58,8 @@ module.exports.start = async (req, res) => {
     if (event.type === 'frigate') {
       const { type: frigateEventType, topic } = req.body;
       const attributes = req.body.after ? req.body.after : req.body.before;
-      const { id, label, camera, current_zones: zones } = attributes;
-      event = { id, label, camera, zones, frigateEventType, topic, ...event };
+      const { id, label, camera, area, current_zones: zones } = attributes;
+      event = { id, label, camera, area, zones, frigateEventType, topic, ...event };
     } else {
       const { url, camera } = req.query;
 
@@ -148,7 +148,7 @@ module.exports.start = async (req, res) => {
       );
     }
 
-    const { best, misses, unknown, results, attempts } = recognize.normalize(
+    const { best, misses, unknowns, results, attempts, counts } = recognize.normalize(
       await Promise.all(promises)
     );
 
@@ -160,28 +160,28 @@ module.exports.start = async (req, res) => {
       attempts,
       camera,
       zones,
+      counts,
       matches: best,
       misses,
+      unknowns,
     };
-    if (unknown && Object.keys(unknown).length) output.unknown = unknown;
     if (AUTH) output.token = jwt.sign({ route: 'storage', expiresIn: TOKEN.IMAGE });
 
     if (resultsOutput === 'all') output.results = results;
 
     console.log(`done processing ${camera}: ${id} in ${duration} sec`);
 
     const loggedOutput = JSON.parse(JSON.stringify(output));
-    ['matches', 'misses'].forEach((type) =>
+    ['matches', 'misses', 'unknowns'].forEach((type) =>
       loggedOutput[type].forEach((result) => delete result.base64)
     );
-    if (loggedOutput.unknown) delete loggedOutput.unknown.base64;
     console.log(loggedOutput);
 
     PROCESSING = false;
 
     res.send(output);
 
-    recognize.save.latest(camera, best, misses, unknown);
+    recognize.save.latest(camera, best, misses, unknowns[0]);
     mqtt.recognize(output);
     notify.publish(output, camera, results);
     if (event.type === 'frigate') frigate.subLabel(event.topic, id, best);

api/src/util/detectors/actions/index.js

@@ -9,9 +9,13 @@ module.exports.normalize = ({ camera, detector, data }) =>
 module.exports.checks = ({ MATCH, UNKNOWN, name, confidence, box }) => {
   const checks = [];
   if (name === 'unknown' && box.width * box.height < UNKNOWN.MIN_AREA) return false;
-  if (confidence < MATCH.CONFIDENCE)
-    checks.push(`confidence too low: ${confidence} < ${MATCH.CONFIDENCE}`);
-  if (box.width * box.height < MATCH.MIN_AREA)
-    checks.push(`box area too low: ${box.width * box.height} < ${MATCH.MIN_AREA}`);
+  if (name === 'unknown' && confidence < UNKNOWN.CONFIDENCE) {
+    checks.push(`confidence too low: ${confidence} < ${UNKNOWN.CONFIDENCE}`);
+  } else {
+    if (confidence < MATCH.CONFIDENCE)
+      checks.push(`confidence too low: ${confidence} < ${MATCH.CONFIDENCE}`);
+    if (box.width * box.height < MATCH.MIN_AREA)
+      checks.push(`box area too low: ${box.width * box.height} < ${MATCH.MIN_AREA}`);
+  }
   return checks;
 };

api/src/util/detectors/deepstack.js

@@ -63,7 +63,10 @@ module.exports.remove = ({ name }) => {
 };
 
 module.exports.normalize = ({ camera, data }) => {
-  if (data.success === false) return [];
+  if (!data.success) {
+    console.warn('unexpected deepstack data');
+    return [];
+  }
   const { MATCH, UNKNOWN } = config.detect(camera);
   const normalized = data.predictions.flatMap((obj) => {
     const confidence = parseFloat((obj.confidence * 100).toFixed(2));

api/src/util/frigate.util.js

@@ -22,6 +22,7 @@ module.exports.checks = async ({
   topic,
   label,
   camera,
+  area,
   zones,
   PROCESSING,
   IDS,
@@ -63,6 +64,10 @@ module.exports.checks = async ({
       return `${id} - ${label} label not in (${FRIGATE.LABELS.join(', ')})`;
     }
 
+    if (FRIGATE.MIN_AREA > area) {
+      return `skipping object area smaller than ${FRIGATE.MIN_AREA} (${area})`;
+    }
+
     if (IDS.includes(id)) {
       return `already processed ${id}`;
     }