From 7807470c573ff3321d10896c527403fac1e93739 Mon Sep 17 00:00:00 2001 From: Pei-Yun Sun Date: Tue, 20 Oct 2020 12:43:29 +1100 Subject: [PATCH] fixing statistical results --- .DS_Store | Bin 10244 -> 10244 bytes src/__pycache__/config.cpython-38.pyc | Bin 948 -> 948 bytes .../general_controller.cpython-38.pyc | Bin 6207 -> 5503 bytes .../prediction_controller.cpython-38.pyc | Bin 1955 -> 2074 bytes src/controller/general_controller.py | 127 +++++++++--------- src/controller/prediction_controller.py | 16 +-- .../__pycache__/constants.cpython-38.pyc | Bin 744 -> 681 bytes src/extension/constants.py | 117 +++++++--------- .../__pycache__/feedback.cpython-38.pyc | Bin 838 -> 897 bytes src/models/feedback.py | 7 +- src/templates/homePage.html | 14 +- src/templates/statisticalPage.html | 71 +++++----- 12 files changed, 175 insertions(+), 177 deletions(-) diff --git a/.DS_Store b/.DS_Store index b94b956d9c2f87ddde3af72ba6dfbfe3260d9574..a4fab54b683477cc80b4807faeee4fdb07fad17f 100644 GIT binary patch delta 206 zcmZn(XbIS$Di9}=^p=5vfrUYjA)O(Up(Hoo#U&{xKM5$tAttdk|M|Q_j;Qh}c;yQ+ z41<&Na|?ia7??~9Ha82bV`Mx%*+{5?TdKO+(AdOKN5R-=@*W|1#@Una0LeL%{|HGi z70uc#CTz~CtmkW6`V3+vGea>$5kqorKEgtf?Eb98u*{@X8lt z7zQWj=N16dxhi~XHC8fBxg_lD<2dYN>s6LW>fghvYAPgnHc~- Ckvc>G diff --git a/src/__pycache__/config.cpython-38.pyc b/src/__pycache__/config.cpython-38.pyc index de6c9380c7d81007a7e6b98548ad919a478d76cb..9cd495276fd5b236a93e156a75a745571dbdeff2 100644 GIT binary patch delta 20 acmdnOzJ;ATl$V!_0SH#<_HE=|$qWE5{shPX delta 20 acmdnOzJ;ATl$V!_0SMBj^={-|$qWE6lLYJl diff --git a/src/controller/__pycache__/general_controller.cpython-38.pyc b/src/controller/__pycache__/general_controller.cpython-38.pyc index f13adf3946a3fd2da3ca4997a1c59fd1a34dad58..6cd5e9b931cfcaf93d231b9f0a08006a85bfa2c8 100644 GIT binary patch literal 5503 zcmc&2O>Y~=b-%b=epA%96FY0!4oox_fg(T)LlGj&t>Yk3j7mn)1%kzDXDF_{++EEK zrHUX=&aHLeQ+sg%>6m+eM1I4b3iPB)F1h(o_08;(TvD43aSF8nqq25-IbcPbFfYNPL3NC2grU#!@wq(Mqxm4Q;rMUU+wJfZSCys?lhIS zu;X+A=eRgF{(x!NBQCb`2ROjQ@!!a;{#yENdOPJyf}@9n4jm2p?fTj4;XC=gJ^+^eFI=hqeukz7HJ|;*pjF`?Wrl znKY1*@j?Mrg}z%f(v&W+aO}{r6Uf{@ z5uSaC{e75<0Gk*l1v|v;n2$)rSs}9(%0gCDGY+ zJ7MUXVcXmeyHSsM!GY-n$mC%h&ExI~Ww=YtyB)?NdcW0jJ$gx|!^}O1_S3*S!i0M4 zgv*>*C@h+>W8LfzI1itp9>w4(VP4yFJ;#T6V%YaRNGlhccik{J3VpCH3;-A49;6+- z*l|dn(9G6e*wMEo z)Ma(EJgMIQg&=!JeM-KN)pYUevWHf%e9^ToE~qHT9W)bsgw z*|raRj-O&wC-Pzyg)ZSDg{hg2>mvM2u0W$2bcSNc0@7a*Ck$n9CQ;_Oj(-pK#h%aT z|9IHcb|)eqI?U-Wr(1hQm5Bf`b=k;1y&s7k-h*2BFZlVl`I`T z80diC7#c_(SRLd}8)y}ZB?T=lOEBlF8xkuboz0&v45~aEkp3P>7-h}S znB>W6V*q(G=FDVIN^@;h0-7p<_Y56C68Hw!$vNLkY2iIX3lN}%enWbt99qymA84sx zwL$Hn^h*BvufzJFj@}2)<_2>Dax`oR->zq*T?cIqbYoR|rP6OfZzjLN&IbBmN_PgE z;5MY-;|v$9fOl~5^&un*ohInisFHH?c)*$x+&3@jOtHWXxQtE?AL+cBE72*qfO}2o zJW6%)xQ=w*x}-D30vF&iIyro#^J=a{r{H>}9)1jMjjwW^b)b0_qL4$^ML)`qN!&T_ zWW;xwBo}ygB=FSd%xFRdwx#gY%FKvU718b2mEk;F9L%FTqALHe|Mzk2oGG)j`|(v} z_F)f`6Vq`?NU7Pz80|amb5S-%1S8KCl_MNW*dI%ut>%A91>si>xK$OOj3vUz_4-l@A2;5Tjz_waL(_MZ{%NDwTU4%KT%>8DqO2FvQ@yW+%XA*16~>s zf?d|sVyy$WgIMo+L66~Brx*@t6qmXlcU26|^~5d>IVZGl+(E57-PWBy#V}^Lsr1#` zK6|6xK4AEqAFAj4I(E+MhjZ=_`4GBzZekqVLioXIWk7b&>+WN)A}Pn?d|HYpB@EQ; zR&DG?LTXjPx$VS>08?s}U_6f0Tp}lnuO^@|Nh4K}rKzQ`5mB>ZU1K40{2gK5SM4XA zkcCepKXedA*77uNJZaYA6k;T8M%LB=p3JlL!4wPNQoF{?*Jla-$S3kG=ttsKlM%l* z#hsvMHQc;{22E?ZF-7vbM z5>U$EN*w1{2$>(}366aJ=SG1;VWGnkGk~%!h-z-w3z!YHXRiwhOJl9=1xVDPu?By2 zbmCmw4S!(yUV{q5g`L*o#GQ<_*8IquEU=#0NRm}u5OKF*3B#v7KD+?J&UhF~-lWdO|j_!>S2689-z5&Hn`wtGFbHl95$SWQ>fq zDgrqg#`V#cxClU$;<6y%*8)D$6EU+TJFn$$L8EJYKgpNnGL-FxTvau>EU&kx(&XD0%FlYQ0G$E!#S7&}tx*&b4Ox>FNx6V~$c3TZP?s*M>a~jov};;XDT2=8 z6h%=j0;MMFDUb4>s;pmV`T7h*(SJ5&uBgs(UzS(Y4MmrAu&63mr+VcFeX&2kJALO6 zHz+a(vCBl3U*m|l5iP^lO=y!F5r;JE@e=+sObdm-Q`X^66@M3#BhSTDWUw_qLBjMw zMncXfi%E6qQLGRgSKGcrpYu#%k>8_)A5?^&CFD1}`!(-2dB=}2Sc4%PK;kw=xB*w$ g8XFtQ&2N)u0_E!-vH|9W=K${wrK%coW8RSe3)H(QYXATM literal 6207 zcmdrQO>Y~=b-ze1DTTEydK3x-T{BufZni8#!)J>?7+D4Sb7W8U{YaO*t;_e6hEGaC`4y zf3K;;x5Mxri0N+<%zDH(SO;^}2EtFV7lfE(?Q>+1Ir=H^QG#a&9(olTB*Y^v z3HGbvKxR@TBmJ2Is>*$*Vx+%}s&){typA!|&4lbG1SMzLC`OsMjd}Xt9&}tP95}Y= z*a>7Do(RuA$KD|fg^vvkgMw}1bd0+s=!M3O%=? 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', - 'description': 'The app uses artificial intelligence (convolutional neural networks) that have been trained on dog/cat images to identify whether a dog/cat is in an image, and if so the species type (breed) and it\'s emotion.', + 'description': 'The app uses artificial intelligence (convolutional neural networks) to identify the age, gender, and emotion of the people.', 'contact': 'https://eresearch.unimelb.edu.au', 'developedByHTML': '

This app was developed by the Melbourne eResearch Group (www.eresearch.unimelb.edu.au) within the School of Computing and Information Systems (https://cis.unimelb.edu.au) at The University of Melbourne (www.unimelb.edu.au).

', - 'descriptionHTML': '

The app uses artificial intelligence (convolutional neural networks) that have been trained on dog/cat images to identify whether a dog/cat is in an image, and if so the species type (breed) and it\'s emotion.

', + 'descriptionHTML': '

The app uses artificial intelligence (convolutional neural networks) to identify the age, gender, and emotion of the people.

', 'contactHTML': '

Please contact us at: eresearch.unimelb.edu.au

' } @@ -41,33 +42,19 @@ class StatisticalData(Resource): from models.prediction import Prediction from models.feedback import Feedback - total_cat_breed = [] - total_dog_breed = [] prediction_collection = Prediction._get_collection() feedback_collection = Feedback._get_collection() statistical_data = copy.deepcopy(CONSTANTS['STATISTICAL_DATA']) - # initial statistical_data based on breed and alpha order - f = open("model_data/pet_classes.txt", "r") - for each_line in f: - first_char = each_line[0] - if first_char.isupper(): - total_cat_breed.append(re.sub(r"_", " ", each_line.rstrip(), flags=re.IGNORECASE).title()) - else: - total_dog_breed.append(re.sub(r"_", " ", each_line.rstrip(), flags=re.IGNORECASE).title()) - f.close() - total_cat_breed.sort() - total_dog_breed.sort() + # initial statistical_data based on age and ascending order + total_age = [] + for i in range(21): + total_age.append(str(i * 5) + '+') - for each_breed in total_cat_breed: - statistical_data['Cat']['prediction_data']['breed'][each_breed] = 0 - statistical_data['Cat']['feedback_data']['breed']['wrong'][each_breed] = 0 - statistical_data['Cat']['feedback_data']['breed']['correct'][each_breed] = 0 - - for each_breed in total_dog_breed: - statistical_data['Dog']['prediction_data']['breed'][each_breed] = 0 - statistical_data['Dog']['feedback_data']['breed']['wrong'][each_breed] = 0 - statistical_data['Dog']['feedback_data']['breed']['correct'][each_breed] = 0 + for each_age in total_age: + statistical_data['prediction_data']['age'][each_age] = 0 + statistical_data['feedback_data']['age']['wrong'][each_age] = 0 + statistical_data['feedback_data']['age']['correct'][each_age] = 0 # photo by date today = datetime.datetime.today().replace(hour=0, minute=0, second=0, microsecond=0) @@ -90,65 +77,85 @@ class StatisticalData(Resource): # prediction total_prediction = prediction_collection.find({}) + for each_prediction in total_prediction: prediction_results = each_prediction['predictionResults'] for each_result in prediction_results: - statistical_data[each_result['type']]['prediction_number'] = statistical_data[each_result['type']].get( + statistical_data['prediction_number'] = statistical_data.get( 'prediction_number', 0) + 1 - statistical_data[each_result['type']]['prediction_data']['breed'][each_result['breed']] = \ - statistical_data[each_result['type']]['prediction_data']['breed'].get(each_result['breed'], 0) + 1 - statistical_data[each_result['type']]['prediction_data']['emotion'][each_result['emotion']] = \ - statistical_data[each_result['type']]['prediction_data']['emotion'].get(each_result['emotion'], - 0) + 1 + + # age, gender, emotion + each_age = str(5*math.floor(each_result['age'] / 5)) + '+' + + statistical_data['prediction_data']['age'][each_age] = \ + statistical_data['prediction_data']['age'].get(each_age, 0) + 1 + statistical_data['prediction_data']['gender'][each_result['gender']] = \ + statistical_data['prediction_data']['gender'].get(each_result['gender'], 0) + 1 + statistical_data['prediction_data']['emotion'][each_result['emotion']] = \ + statistical_data['prediction_data']['emotion'].get(each_result['emotion'], 0) + 1 + # feedback total_feedback = feedback_collection.find({}) for each_feedback in total_feedback: feedback_content = each_feedback['content'] for each_content in feedback_content: - statistical_data[each_content['type']]['feedback_number'] = statistical_data[each_content['type']].get( + statistical_data['feedback_number'] = statistical_data.get( 'feedback_number', 0) + 1 - if not each_content['breedCorrectness']: - statistical_data[each_content['type']]['feedback_data']['breed']['wrong'][ - each_content['breedFeedback']] = \ - statistical_data[each_content['type']]['feedback_data']['breed'][ - 'wrong'].get(each_content['breedFeedback'], 0) + 1 + # age + if not each_content['ageCorrectness']: + statistical_data['feedback_data']['age']['wrong'][ + each_content['ageFeedback']] = \ + statistical_data['feedback_data']['age'][ + 'wrong'].get(each_content['ageFeedback'], 0) + 1 else: - statistical_data[each_content['type']]['feedback_data']['breed']['correct'][ - each_content['breedFeedback']] = \ - statistical_data[each_content['type']]['feedback_data']['breed']['correct'].get( - each_content['breedFeedback'], 0) + 1 + statistical_data['feedback_data']['age']['correct'][ + each_content['ageFeedback']] = \ + statistical_data['feedback_data']['age']['correct'].get( + each_content['ageFeedback'], 0) + 1 + + # gender + if not each_content['genderCorrectness']: + statistical_data['feedback_data']['gender']['wrong'][ + each_content['genderFeedback']] = \ + statistical_data['feedback_data']['gender'][ + 'wrong'].get(each_content['genderFeedback'], 0) + 1 + else: + statistical_data['feedback_data']['gender']['correct'][ + each_content['genderFeedback']] = \ + statistical_data['feedback_data']['gender']['correct'].get( + each_content['genderFeedback'], 0) + 1 if not each_content['emotionCorrectness']: - statistical_data[each_content['type']]['feedback_data']['emotion']['wrong'][ + statistical_data['feedback_data']['emotion']['wrong'][ each_content['emotionFeedback']] = \ - statistical_data[each_content['type']]['feedback_data']['emotion']['wrong'].get( + statistical_data['feedback_data']['emotion']['wrong'].get( each_content['emotionFeedback'], 0) + 1 else: - statistical_data[each_content['type']]['feedback_data']['emotion']['correct'][ + statistical_data['feedback_data']['emotion']['correct'][ each_content['emotionFeedback']] = \ - statistical_data[each_content['type']]['feedback_data']['emotion']['correct'].get( + statistical_data['feedback_data']['emotion']['correct'].get( each_content['emotionFeedback'], 0) + 1 result = { 'totalNumberOfPhotoUploaded': prediction_collection.count_documents({}), - 'totalNumberOfCatPrediction': statistical_data['Cat']['prediction_number'], - 'totalNumberOfDogPrediction': statistical_data['Dog']['prediction_number'], - 'totalNumberOfCatFeedback': statistical_data['Cat']['feedback_number'], - 'totalNumberOfDogFeedback': statistical_data['Dog']['feedback_number'], - 'totalNumberOfDogBreedPrediction': statistical_data['Dog']['prediction_data']['breed'], - 'totalNumberOfDogBreedCorrectFeedback': statistical_data['Dog']['feedback_data']['breed']['correct'], - 'totalNumberOfDogBreedWrongFeedback': statistical_data['Dog']['feedback_data']['breed']['wrong'], - 'totalNumberOfDogEmotionPrediction': statistical_data['Dog']['prediction_data']['emotion'], - 'totalNumberOfDogEmotionCorrectFeedback': statistical_data['Dog']['feedback_data']['emotion']['correct'], - 'totalNumberOfDogEmotionWrongFeedback': statistical_data['Dog']['feedback_data']['emotion']['wrong'], - 'totalNumberOfCatBreedPrediction': statistical_data['Cat']['prediction_data']['breed'], - 'totalNumberOfCatBreedCorrectFeedback': statistical_data['Cat']['feedback_data']['breed']['correct'], - 'totalNumberOfCatBreedWrongFeedback': statistical_data['Cat']['feedback_data']['breed']['wrong'], - 'totalNumberOfCatEmotionPrediction': statistical_data['Cat']['prediction_data']['emotion'], - 'totalNumberOfCatEmotionCorrectFeedback': statistical_data['Cat']['feedback_data']['emotion']['correct'], - 'totalNumberOfCatEmotionWrongFeedback': statistical_data['Cat']['feedback_data']['emotion']['wrong'], + + 'totalNumberOfPrediction': statistical_data['prediction_number'], + 'totalNumberOfFeedback': statistical_data['feedback_number'], + + 'totalNumberOfAgePrediction': statistical_data['prediction_data']['age'], + 'totalNumberOfAgeCorrectFeedback': statistical_data['feedback_data']['age']['correct'], + 'totalNumberOfAgeWrongFeedback': statistical_data['feedback_data']['age']['wrong'], + + 'totalNumberOfGenderPrediction': statistical_data['prediction_data']['gender'], + 'totalNumberOfGenderCorrectFeedback': statistical_data['feedback_data']['gender']['correct'], + 'totalNumberOfGenderdWrongFeedback': statistical_data['feedback_data']['gender']['wrong'], + + 'totalNumberOfEmotionPrediction': statistical_data['prediction_data']['emotion'], + 'totalNumberOfEmotionCorrectFeedback': statistical_data['feedback_data']['emotion']['correct'], + 'totalNumberOfEmotionWrongFeedback': statistical_data['feedback_data']['emotion']['wrong'], + 'numberOfPhotoByDate': total_number_of_photo_within_one_week } diff --git a/src/controller/prediction_controller.py b/src/controller/prediction_controller.py index ac522f5..c4d360a 100644 --- a/src/controller/prediction_controller.py +++ b/src/controller/prediction_controller.py @@ -27,7 +27,6 @@ class Prediction(Resource): img, detections = deepface.analyze(image) - # TODO: handle outputs # encode image and jsonify detections buffered = io.BytesIO() img.save(buffered, format="JPEG") @@ -61,13 +60,12 @@ class Prediction(Resource): 'emotionScore': emotion_score }) - # store to db? - - # new_prediction = Prediction(**{ - # 'predictionResults': formatted_prediction_results, - # 'rawPredictionResults': detections, - # 'date': datetime.datetime.now(), - # }) - # new_prediction.save() + # store results to db + new_prediction = Prediction(**{ + 'predictionResults': formatted_prediction_results, + 'rawPredictionResults': detections, + 'date': datetime.datetime.now(), + }) + new_prediction.save() return send_json_response(result, 200) diff --git a/src/extension/__pycache__/constants.cpython-38.pyc b/src/extension/__pycache__/constants.cpython-38.pyc index 9927c170367bbe54d8bc8585b9bd6d5108191784..4568404b2040ad78d0ff9985673f9935c6060390 100644 GIT binary patch literal 681 zcmZ9I&u-H|5XRT*bv6xzl-~OQzTh(wAgs2~NYpvl6;dS>HlB&GXx7%QEy#^0;0gQ! zywYAdap2l2RaLRuD1XF^{H^Dk`C03^91aJ>#;4amr}qINzg@8(BU`++kN#l=2zWrj z2L=K3fOj1F&@YKoIOyo(>E72lu>B{UUlKdo}o;d!ML=1s`VXpRUok$;`ab}_Tl&ufKH<__3cqdf~mBg}9MxiX|z{On?q zjVFmYOtUx}r`h-<{xCg_vp5Mob8s?Ate<4*FQSg!HJ#kOj4m}Q9o1MaTdAY>Wpm!n zB0#L?BF9LpJi_k{N^S2F<(1Tpkd1y}7u|ogsGz;ZH*N>|vlZ&?<%$h#<-(&6EZFOK abj9x2(bj)pz5lw7+~tbhuv_+*-TVVqVY}4; literal 744 zcmb`D&uZI15XRTi%94^ePNA>RgD%y%P)da@Vu2%@N`gigBWpHB)Rx5ViYB+bK;A$v z&}$xNbL^?-9$Fd*oux_YbLlMlwBK+3uuL`@9T1G`o10bU67p4>{WwPR9zSu50t5yd z0}L>Mf(1jcdkY+JDx&rAxX2EAqasKTd*hiqpfgWZf1J)^Egbb!Xa38a5zagA&78nE zA>N5H%R=TRG#h2jinhH{cFa1-i>RYWMDYw|tvO?$Y_@A;)zq4N z=1sj(cG+;wO6gHGzQB@oQGQz0-EPgedeL$QRjC`E(0C6)AqzEnZqgR#nv+5*bJ}b? zGd~RC=q#A8((`4Q+u_+FjTW&wNzx#Vk~ErNY8s?L>!zux$n zU|jeutFF3Q_@|Yeb!#6OYcGnD`GS`|yOgXJ_(;EOY9WhSir2Vd=k2b6Zp+^3wTNq! np1E zS_D@u2;onTU^HeE0$N=pG
  • ID: ${response['results'][i].id}` - const emotionList = `
    • ${response['results'][i].emotion['all'][0]}
    • ${response['results'][i].emotion['all'][1]}
    • ${response['results'][i].emotion['all'][2]}
    • ${response['results'][i].emotion['all'][3]}
    • ${response['results'][i].emotion['all'][4]}
    • ${response['results'][i].emotion['all'][5]}
    • ${response['results'][i].emotion['all'][6]}
    ` - const otherInfo = `
  • Age: ${response['results'][i].age}
  • Gender: ${response['results'][i].gender}
  • Emotion: ${response['results'][i].emotion['dominant']}
${emotionList}` + const addedId = `
  • ID: ${response['results'][i].id}
    • ` + const emotionList = `
    • ${response['results'][i].emotion['all'][0]}
      • +
    • ${response['results'][i].emotion['all'][1]}
      • +
    • ${response['results'][i].emotion['all'][2]}
      • +
    • ${response['results'][i].emotion['all'][3]}
      • +
    • ${response['results'][i].emotion['all'][4]}
      • +
    • ${response['results'][i].emotion['all'][5]}
      • +
    • ${response['results'][i].emotion['all'][6]}
    ` + const otherInfo = `
  • Age: ${response['results'][i].age}
    • +
  • Gender: ${response['results'][i].gender}
    • +
  • Emotion: ${response['results'][i].emotion['dominant']}
${emotionList}
` const addedHtml = response['isShowId'] !== 'false' ? addedId + otherInfo : otherInfo resultArea.innerHTML += addedHtml } diff --git a/src/templates/statisticalPage.html b/src/templates/statisticalPage.html index 2d58a46..d992a8e 100644 --- a/src/templates/statisticalPage.html +++ b/src/templates/statisticalPage.html @@ -16,25 +16,25 @@
-

Cat:

+

Age:

- +

- +

-

Dog:

+

Gender:

- +

- +

@@ -42,7 +42,7 @@
-
+ +
+
+
+