mirror of
https://gitcode.com/GitHub_Trending/ji/jitsi-meet.git
synced 2025-12-30 11:22:31 +00:00
61684b1071
* Initial implementation; Happy flow * Maybe revert this * Functional prototype * feat(facial-expressions): get stream when changing background effect and use presenter effect with camera * add(facial-expressions): array that stores the expressions durin the meeting * refactor(facial-expressions): capture imagebitmap from stream with imagecapture api * add(speaker-stats): expression label * fix(facial-expression): expression store * revert: expression leabel on speaker stats * add(facial-expressions): broadcast of expression when it changes * feat: facial expression handling on prosody * fix(facial-expressions): get the right track when opening and closing camera * add(speaker-stats): facial expression column * fix(facial-expressions): allow to start facial recognition only after joining conference * fix(mod_speakerstats_component): storing last emotion in speaker stats component and sending it * chore(facial-expressions): change detection from 2000ms to 1000ms * add(facial-expressions): send expression to server when there is only one participant * feat(facial-expressions): store expresions as a timeline * feat(mod_speakerstats_component): store facial expresions as a timeline * fix(facial-expressions): stop facial recognition only when muting video track * fix(facial-expressions): presenter mode get right track to detect face * add: polyfils for image capture for firefox and safari * refactor(facial-expressions): store expressions by counting them in a map * chore(facial-expressions): remove manually assigning the backend for tenserflowjs * feat(facial-expressions): move face-api from main thread to web worker * fix(facial-expressions): make feature work on firefox and safari * feat(facial-expressions): camera time tracker * feat(facial-expressions): camera time tracker in prosody * add(facial-expressions): expressions time as TimeElapsed object in speaker stats * fix(facial-expresions): lower the frequency of detection when tf uses cpu backend * add(facial-expressions): duration to the expression and send it with durantion when it is done * fix(facial-expressions): prosody speaker stats covert fro string to number and bool values set by xmpp * refactor(facial-expressions): change expressions labels from text to emoji * refactor(facial-expressions): remove camera time tracker * add(facial-expressions): detection time interval * chore(facial-expressions): add docs and minor refactor of the code * refactor(facial-expressions): put timeout in worker and remove set interval in main thread * feat(facial-expressions): disable feature in the config * add(facial-expressions): tooltips of labels in speaker stats * refactor(facial-expressions): send facial expressions function and remove some unused functions and console logs * refactor(facial-expressions): rename action type when a change is done to the track by the virtual backgrounds to be used in facial expressions middleware * chore(facial-expressions): order imports and format some code * fix(facial-expressions): rebase issues with newer master * fix(facial-expressions): package-lock.json * fix(facial-expression): add commented default value of disableFacialRecognition flag and short description * fix(facial-expressions): change disableFacialRecognition to enableFacialRecognition flag in config * fix: resources load-test package-lock.json * fix(facial-expressions): set and get facial expressions only if facial recognition enabled * add: facial recognition resources folder in .eslintignore * chore: package-lock update * fix: package-lock.json * fix(facial-expressions): gpu memory leak in the web worker * fix(facial-expressions): set cpu time interval for detection to 6000ms * chore(speaker-stats): fix indentation * chore(facial-expressions): remove empty lines between comments and type declarations * fix(facial-expressions): remove camera timetracker * fix(facial-expressions): remove facialRecognitionAllowed flag * fix(facial-expressions): remove sending interval time to worker * refactor(facial-expression): middleware * fix(facial-expression): end tensor scope after setting backend * fix(facial-expressions): sending info back to worker only on facial expression message * fix: lint errors * refactor(facial-expressions): bundle web worker using webpack * fix: deploy-facial-expressions command in makefile * chore: fix load test package-lock.json and package.json * chore: sync package-lock.json Co-authored-by: Mihai-Andrei Uscat <mihai.uscat@8x8.com>
1 line
6.2 KiB
JSON
1 line
6.2 KiB
JSON
[{"weights":[{"name":"dense0/conv0/filters","shape":[3,3,3,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0057930146946626555,"min":-0.7125408074435067}},{"name":"dense0/conv0/bias","shape":[32],"dtype":"float32"},{"name":"dense0/conv1/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006473719839956246,"min":-0.6408982641556684}},{"name":"dense0/conv1/pointwise_filter","shape":[1,1,32,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010509579321917366,"min":-1.408283629136927}},{"name":"dense0/conv1/bias","shape":[32],"dtype":"float32"},{"name":"dense0/conv2/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005666389652326995,"min":-0.7252978754978554}},{"name":"dense0/conv2/pointwise_filter","shape":[1,1,32,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010316079270605948,"min":-1.1760330368490781}},{"name":"dense0/conv2/bias","shape":[32],"dtype":"float32"},{"name":"dense0/conv3/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0063220320963392074,"min":-0.853474333005793}},{"name":"dense0/conv3/pointwise_filter","shape":[1,1,32,32],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010322785377502442,"min":-1.4658355236053466}},{"name":"dense0/conv3/bias","shape":[32],"dtype":"float32"},{"name":"dense1/conv0/depthwise_filter","shape":[3,3,32,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0042531527724920535,"min":-0.5741756242864272}},{"name":"dense1/conv0/pointwise_filter","shape":[1,1,32,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010653339647779278,"min":-1.1825207009035}},{"name":"dense1/conv0/bias","shape":[64],"dtype":"float32"},{"name":"dense1/conv1/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005166931012097527,"min":-0.6355325144879957}},{"name":"dense1/conv1/pointwise_filter","shape":[1,1,64,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.011478300188101974,"min":-1.3888743227603388}},{"name":"dense1/conv1/bias","shape":[64],"dtype":"float32"},{"name":"dense1/conv2/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006144821410085641,"min":-0.8479853545918185}},{"name":"dense1/conv2/pointwise_filter","shape":[1,1,64,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010541967317169788,"min":-1.3809977185492421}},{"name":"dense1/conv2/bias","shape":[64],"dtype":"float32"},{"name":"dense1/conv3/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005769844849904378,"min":-0.686611537138621}},{"name":"dense1/conv3/pointwise_filter","shape":[1,1,64,64],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010939095534530341,"min":-1.2689350820055196}},{"name":"dense1/conv3/bias","shape":[64],"dtype":"float32"},{"name":"dense2/conv0/depthwise_filter","shape":[3,3,64,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.0037769308277204924,"min":-0.40790852939381317}},{"name":"dense2/conv0/pointwise_filter","shape":[1,1,64,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.01188667194516051,"min":-1.4382873053644218}},{"name":"dense2/conv0/bias","shape":[128],"dtype":"float32"},{"name":"dense2/conv1/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006497045825509464,"min":-0.8381189114907208}},{"name":"dense2/conv1/pointwise_filter","shape":[1,1,128,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.011632198913424622,"min":-1.3377028750438316}},{"name":"dense2/conv1/bias","shape":[128],"dtype":"float32"},{"name":"dense2/conv2/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.005947182225246056,"min":-0.7969224181829715}},{"name":"dense2/conv2/pointwise_filter","shape":[1,1,128,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.011436844339557722,"min":-1.4524792311238306}},{"name":"dense2/conv2/bias","shape":[128],"dtype":"float32"},{"name":"dense2/conv3/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006665432686899222,"min":-0.8998334127313949}},{"name":"dense2/conv3/pointwise_filter","shape":[1,1,128,128],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.01283421422920975,"min":-1.642779421338848}},{"name":"dense2/conv3/bias","shape":[128],"dtype":"float32"},{"name":"dense3/conv0/depthwise_filter","shape":[3,3,128,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.004711699953266218,"min":-0.6737730933170692}},{"name":"dense3/conv0/pointwise_filter","shape":[1,1,128,256],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.010955964817720302,"min":-1.3914075318504784}},{"name":"dense3/conv0/bias","shape":[256],"dtype":"float32"},{"name":"dense3/conv1/depthwise_filter","shape":[3,3,256,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.00554193468654857,"min":-0.7149095745647656}},{"name":"dense3/conv1/pointwise_filter","shape":[1,1,256,256],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.016790372250126858,"min":-2.484975093018775}},{"name":"dense3/conv1/bias","shape":[256],"dtype":"float32"},{"name":"dense3/conv2/depthwise_filter","shape":[3,3,256,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006361540626077091,"min":-0.8142772001378676}},{"name":"dense3/conv2/pointwise_filter","shape":[1,1,256,256],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.01777329678628959,"min":-1.7062364914838006}},{"name":"dense3/conv2/bias","shape":[256],"dtype":"float32"},{"name":"dense3/conv3/depthwise_filter","shape":[3,3,256,1],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.006900275922289082,"min":-0.8625344902861353}},{"name":"dense3/conv3/pointwise_filter","shape":[1,1,256,256],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.015449936717164282,"min":-1.9003422162112067}},{"name":"dense3/conv3/bias","shape":[256],"dtype":"float32"},{"name":"fc/weights","shape":[256,7],"dtype":"float32","quantization":{"dtype":"uint8","scale":0.004834276554631252,"min":-0.7203072066400565}},{"name":"fc/bias","shape":[7],"dtype":"float32"}],"paths":["face_expression_model-shard1"]}] |