mirror of https://github.com/vladmandic/human
84 lines
3.7 KiB
Markdown
84 lines
3.7 KiB
Markdown
# Human Face Recognition & Matching
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- **Browser** demo: `index.html` & `facematch.js`:
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Loads sample images, extracts faces and runs match and similarity analysis
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- **NodeJS** demo `node-match.js` and `node-match-worker.js`
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Advanced multithreading demo that runs number of worker threads to process high number of matches
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- Sample face database: `faces.json`
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<br>
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## Browser Face Recognition Demo
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- `demo/facematch`: Demo for Browsers that uses all face description and embedding features to
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detect, extract and identify all faces plus calculate simmilarity between them
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It highlights functionality such as:
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- Loading images
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- Extracting faces from images
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- Calculating face embedding descriptors
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- Finding face similarity and sorting them by similarity
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- Finding best face match based on a known list of faces and printing matches
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<br>
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## NodeJS Multi-Threading Match Solution
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### Methods and Properties in `node-match`
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- `createBuffer`: create shared buffer array
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single copy of data regardless of number of workers
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fixed size based on `options.dbMax`
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- `appendRecord`: add additional batch of descriptors to buffer
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can append batch of records to buffer at anytime
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workers are informed of the new content after append has been completed
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- `workersStart`: start or expand pool of `threadPoolSize` workers
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each worker runs `node-match-worker` and listens for messages from main thread
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can shutdown workers or create additional worker threads on-the-fly
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safe against workers that exit
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- `workersClose`: close workers in a pool
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first request workers to exit then terminate after timeout
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- `match`: dispach a match job to a worker
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returns first match that satisfies `minThreshold`
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assigment to workers using round-robin
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since timing for each job is near-fixed and predictable
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- `getDescriptor`: get descriptor array for a given id from a buffer
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- `fuzDescriptor`: small randomize descriptor content for harder match
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- `getLabel`: fetch label for resolved descriptor index
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- `loadDB`: load face database from a JSON file `dbFile`
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extracts descriptors and adds them to buffer
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extracts labels and maintains them in main thread
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for test purposes loads same database `dbFact` times to create a very large database
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`node-match` runs in a listens for messages from workers until `maxJobs` have been reached
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### Performance
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Linear performance decrease that depends on number of records in database
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Non-linear performance that increases with number of worker threads due to communication overhead
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- Face dataase with 10k records:
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> threadPoolSize: 1 => ~60 ms / match job
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> threadPoolSize: 6 => ~25 ms / match job
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- Face database with 50k records:
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> threadPoolSize: 1 => ~300 ms / match job
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> threadPoolSize: 6 => ~100 ms / match job
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- Face database with 100k records:
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> threadPoolSize: 1 => ~600 ms / match job
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> threadPoolSize: 6 => ~200 ms / match job
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### Example
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> node node-match
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```js
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2021-10-13 07:53:36 INFO: options: { dbFile: './faces.json', dbMax: 10000, threadPoolSize: 6, workerSrc: './node-match-worker.js', debug: false, minThreshold: 0.9, descLength: 1024 }
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2021-10-13 07:53:36 DATA: created shared buffer: { maxDescriptors: 10000, totalBytes: 40960000, totalElements: 10240000 }
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2021-10-13 07:53:36 DATA: db loaded: { existingRecords: 0, newRecords: 5700 }
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2021-10-13 07:53:36 INFO: starting worker thread pool: { totalWorkers: 6, alreadyActive: 0 }
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2021-10-13 07:53:36 STATE: submitted: { matchJobs: 100, poolSize: 6, activeWorkers: 6 }
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2021-10-13 07:53:38 STATE: { matchJobsFinished: 100, totalTimeMs: 1769, averageTimeMs: 17.69 }
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2021-10-13 07:53:38 INFO: closing workers: { poolSize: 6, activeWorkers: 6 }
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```
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