Openface 128d embedding not match with same trained image

[iruthaya]

• face_recognition version: 1.3.0
• Python version: 3.10.12
• Operating System: Ubuntu 14.04.4 LTS

Description

Image comparison not working as expected.

What I Did

https://gist.github.com/ageitgey/ddbae3b209b6344a458fa41a3cf75719

I was generating 128d by using the steps in the above link.

labels.csv
reps.csv

The exact same trained image does not match when I compare it with compare_faces and euclidean distance.

my code is below

@app.route('/compare', methods=['POST'])
def compare_faces():
# Check if an image is uploaded
if 'image' not in request.files:
return jsonify({"error": "No image uploaded"}), 400

  #return jsonify({"error": known_faces}), 400

  image_file = request.files['image']
  image = face_recognition.load_image_file(image_file)
  
  # Get face encodings from the uploaded image
  uploaded_face_encodings = face_recognition.face_encodings(image)

  if not uploaded_face_encodings:
      return jsonify({"error": "No faces detected in the uploaded image"}), 400

uploaded_face_encoding = uploaded_face_encodings[0]
print(uploaded_face_encoding)
# Compare with known faces
known_face_encoding = [
[-0.042639598250389,0.12697510421276,0.014530797488987,0.13035343587399,-0.053164716809988,0.03371787071228,-0.065738879144192,-0.17718656361103,0.080609485507011,-0.11265439540148,0.027732145041227,-0.033682178705931,-0.021273426711559,0.1271135956049,-0.088499918580055,-0.017446519806981,0.04732845723629,0.13976719975471,-0.036167126148939,-0.0037440515588969,0.1137520223856,-0.130355656147,-0.027596805244684,0.042697597295046,0.087767049670219,-0.12187146395445,-0.13563132286072,0.022973045706749,-0.03948700428009,0.13130995631218,0.073374330997467,0.12439737468958,0.079822011291981,0.0089356424286962,0.082266487181187,0.095859199762344,-0.040055748075247,0.031072063371539,-0.074191235005856,-0.17806507647038,-0.087892279028893,0.013930887915194,0.085297517478466,-0.044885698705912,0.096631646156311,-0.0075566885061562,0.080720603466034,-0.035989042371511,-0.14826467633247,-0.056701730936766,-0.049690458923578,0.017967024818063,0.14563573896885,-0.027589414268732,0.054250501096249,0.10214652121067,-0.092639699578285,0.020972931757569,0.014154405333102,-0.14585763216019,-0.02223851531744,0.11198300123215,0.064870603382587,-0.11900229007006,0.078739352524281,0.18985342979431,-0.012095944024622,-0.064483337104321,-0.21039552986622,0.13132260739803,0.041820485144854,-0.11704779416323,-0.028266865760088,-0.10028419643641,-0.051676206290722,0.012402578257024,0.05369595810771,-0.14907367527485,-0.066312000155449,-0.10602341592312,-0.10003349930048,0.092825524508953,-0.14685097336769,-0.13497270643711,-0.053804859519005,0.03851144015789,-0.16012623906136,-0.11530403792858,0.0057000494562089,0.15166638791561,0.059543684124947,-0.12744852900505,0.03084815479815,-0.023206077516079,0.10967537015676,0.093494229018688,-0.068601228296757,0.093406267464161,0.015747642144561,0.048768877983093,0.06850703805685,0.035241514444351,-0.028212416917086,-0.05110789835453,-0.049297332763672,0.15850211679935,0.050036493688822,-0.06911689043045,-0.013669647276402,-0.062428008764982,-0.062884271144867,-0.03328175842762,-0.054058488458395,-0.051508847624063,0.086876899003983,-0.046026568859816,-0.0099649019539356,-0.045602090656757,0.16972871124744,0.047455701977015,0.017695063725114,-0.034802637994289,0.015226993709803,-0.022453054785728,0.089553937315941,0.09223198890686,0.18687371909618,-0.066576138138771],
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[-0.12132085859776,0.09852971881628,0.041892345994711,-0.07077968865633,0.11473740637302,0.086649492383003,-0.048417780548334,-0.028898872435093,0.040093656629324,0.07790419459343,-0.043610416352749,-0.025296568870544,-0.022419581189752,0.09338752925396,0.18799994885921,-0.01410439517349,0.088418371975422,0.055694758892059,0.032526738941669,-0.06257601827383,-0.070950523018837,0.030882589519024,-0.02001073397696,0.059368673712015,0.11423096805811,-0.086981095373631,0.029333433136344,0.13031956553459,0.039964940398932,-0.019474916160107,0.14282801747322,-0.020786892622709,0.092536844313145,0.05168729275465,0.072627350687981,0.13202904164791,0.095734313130379,-0.14917215704918,-0.058747950941324,-0.1127115637064,0.11738627403975,-0.036067955195904,0.21227933466434,-0.0075629027560353,-0.032846596091986,-0.0085843587294221,0.034755129367113,0.11516663432121,-0.03493957221508,-0.038479290902615,-0.066656783223152,-0.12994810938835,0.043748859316111,-0.10662186145782,0.050649229437113,0.15587782859802,-0.20941892266273,0.070244543254375,-0.037777483463287,-0.035057704895735,-0.16293980181217,0.048266883939505,-0.0096209840849042,-0.13721656799316,0.095396123826504,0.24169293045998,-0.099606916308403,-0.032394200563431,-0.19572451710701,0.056043546646833,-0.011456613428891,0.0169224049896,-0.052491143345833,-0.13217321038246,0.07500471919775,0.064426690340042,0.062439933419228,0.02089430950582,0.031240304931998,-0.2001047283411,0.01282867975533,0.079058483242989,0.0093256393447518,0.045348953455687,-0.0063658328726888,-0.030669068917632,-0.057113528251648,0.062472350895405,0.039604373276234,0.20688000321388,0.08102160692215,-0.040461245924234,-0.022124789655209,0.0040694810450077,0.10208822786808,0.099264450371265,-0.10149141401052,0.062004450708628,-0.039147946983576,-0.0041726198978722,-0.0045386534184217,-0.069970823824406,0.0010615786304697,-0.1452428996563,-0.089892648160458,0.14853870868683,-0.04631781950593,-0.18521182239056,-0.018989287316799,0.00084138632519171,0.014714129269123,0.0022349341306835,0.058381460607052,0.033589843660593,0.04635052382946,-0.11691634356976,0.023357275873423,0.025887282565236,0.040165822952986,0.10634339600801,0.16670942306519,-0.10392625629902,-0.0012454178649932,0.036852490156889,-0.048750702291727,0.065954804420471,0.044361095875502,-0.065958574414253]
]	
results = face_recognition.compare_faces(known_face_encoding, uploaded_face_encoding)
print(results)
mydb = mysql.connector.connect(
  host="localhost",
  user="thom",       # just an example
  passwd="pass",      # just an example
  database="dbname"    # just an example
)
    #return jsonify({"No match found"}), 404
    mycursor = mydb.cursor()
    quryString = 'SELECT user_id,name, sqrt(' \
'power(f1 - (' + str(uploaded_face_encoding[0]) + ') , 2) + ' \
'power(f2 - (' + str(uploaded_face_encoding[1]) + ') , 2) + ' \
'power(f3 - (' + str(uploaded_face_encoding[2]) + ') , 2) + ' \
'power(f4 - (' + str(uploaded_face_encoding[3]) + ') , 2) + ' \
'power(f5 - (' + str(uploaded_face_encoding[4]) + ') , 2) + ' \
'power(f6 - (' + str(uploaded_face_encoding[5]) + ') , 2) + ' \
'power(f7 - (' + str(uploaded_face_encoding[6]) + ') , 2) + ' \
'power(f8 - (' + str(uploaded_face_encoding[7]) + ') , 2) + ' \
'power(f9 - (' + str(uploaded_face_encoding[8]) + ') , 2) + ' \
'power(f10 - (' + str(uploaded_face_encoding[9]) + ') , 2) + ' \
'power(f11 - (' + str(uploaded_face_encoding[10]) + ') , 2) + ' \
'power(f12 - (' + str(uploaded_face_encoding[11]) + ') , 2) + ' \
'power(f13 - (' + str(uploaded_face_encoding[12]) + ') , 2) + ' \
'power(f14 - (' + str(uploaded_face_encoding[13]) + ') , 2) + ' \
'power(f15 - (' + str(uploaded_face_encoding[14]) + ') , 2) + ' \
'power(f16 - (' + str(uploaded_face_encoding[15]) + ') , 2) + ' \
'power(f17 - (' + str(uploaded_face_encoding[16]) + ') , 2) + ' \
'power(f18 - (' + str(uploaded_face_encoding[17]) + ') , 2) + ' \
'power(f19 - (' + str(uploaded_face_encoding[18]) + ') , 2) + ' \
'power(f20 - (' + str(uploaded_face_encoding[19]) + ') , 2) + ' \
'power(f21 - (' + str(uploaded_face_encoding[20]) + ') , 2) + ' \
'power(f22 - (' + str(uploaded_face_encoding[21]) + ') , 2) + ' \
'power(f23 - (' + str(uploaded_face_encoding[22]) + ') , 2) + ' \
'power(f24 - (' + str(uploaded_face_encoding[23]) + ') , 2) + ' \
'power(f25 - (' + str(uploaded_face_encoding[24]) + ') , 2) + ' \
'power(f26 - (' + str(uploaded_face_encoding[25]) + ') , 2) + ' \
'power(f27 - (' + str(uploaded_face_encoding[26]) + ') , 2) + ' \
'power(f28 - (' + str(uploaded_face_encoding[27]) + ') , 2) + ' \
'power(f29 - (' + str(uploaded_face_encoding[28]) + ') , 2) + ' \
'power(f30 - (' + str(uploaded_face_encoding[29]) + ') , 2) + ' \
'power(f31 - (' + str(uploaded_face_encoding[30]) + ') , 2) + ' \
'power(f32 - (' + str(uploaded_face_encoding[31]) + ') , 2) + ' \
'power(f33 - (' + str(uploaded_face_encoding[32]) + ') , 2) + ' \
'power(f34 - (' + str(uploaded_face_encoding[33]) + ') , 2) + ' \
'power(f35 - (' + str(uploaded_face_encoding[34]) + ') , 2) + ' \
'power(f36 - (' + str(uploaded_face_encoding[35]) + ') , 2) + ' \
'power(f37 - (' + str(uploaded_face_encoding[36]) + ') , 2) + ' \
'power(f38 - (' + str(uploaded_face_encoding[37]) + ') , 2) + ' \
'power(f39 - (' + str(uploaded_face_encoding[38]) + ') , 2) + ' \
'power(f40 - (' + str(uploaded_face_encoding[39]) + ') , 2) + ' \
'power(f41 - (' + str(uploaded_face_encoding[40]) + ') , 2) + ' \
'power(f42 - (' + str(uploaded_face_encoding[41]) + ') , 2) + ' \
'power(f43 - (' + str(uploaded_face_encoding[42]) + ') , 2) + ' \
'power(f44 - (' + str(uploaded_face_encoding[43]) + ') , 2) + ' \
'power(f45 - (' + str(uploaded_face_encoding[44]) + ') , 2) + ' \
'power(f46 - (' + str(uploaded_face_encoding[45]) + ') , 2) + ' \
'power(f47 - (' + str(uploaded_face_encoding[46]) + ') , 2) + ' \
'power(f48 - (' + str(uploaded_face_encoding[47]) + ') , 2) + ' \
'power(f49 - (' + str(uploaded_face_encoding[48]) + ') , 2) + ' \
'power(f50 - (' + str(uploaded_face_encoding[49]) + ') , 2) + ' \
'power(f51 - (' + str(uploaded_face_encoding[50]) + ') , 2) + ' \
'power(f52 - (' + str(uploaded_face_encoding[51]) + ') , 2) + ' \
'power(f53 - (' + str(uploaded_face_encoding[52]) + ') , 2) + ' \
'power(f54 - (' + str(uploaded_face_encoding[53]) + ') , 2) + ' \
'power(f55 - (' + str(uploaded_face_encoding[54]) + ') , 2) + ' \
'power(f56 - (' + str(uploaded_face_encoding[55]) + ') , 2) + ' \
'power(f57 - (' + str(uploaded_face_encoding[56]) + ') , 2) + ' \
'power(f58 - (' + str(uploaded_face_encoding[57]) + ') , 2) + ' \
'power(f59 - (' + str(uploaded_face_encoding[58]) + ') , 2) + ' \
'power(f60 - (' + str(uploaded_face_encoding[59]) + ') , 2) + ' \
'power(f61 - (' + str(uploaded_face_encoding[60]) + ') , 2) + ' \
'power(f62 - (' + str(uploaded_face_encoding[61]) + ') , 2) + ' \
'power(f63 - (' + str(uploaded_face_encoding[62]) + ') , 2) + ' \
'power(f64 - (' + str(uploaded_face_encoding[63]) + ') , 2) + ' \
'power(f65 - (' + str(uploaded_face_encoding[64]) + ') , 2) + ' \
'power(f66 - (' + str(uploaded_face_encoding[65]) + ') , 2) + ' \
'power(f67 - (' + str(uploaded_face_encoding[66]) + ') , 2) + ' \
'power(f68 - (' + str(uploaded_face_encoding[67]) + ') , 2) + ' \
'power(f69 - (' + str(uploaded_face_encoding[68]) + ') , 2) + ' \
'power(f70 - (' + str(uploaded_face_encoding[69]) + ') , 2) + ' \
'power(f71 - (' + str(uploaded_face_encoding[70]) + ') , 2) + ' \
'power(f72 - (' + str(uploaded_face_encoding[71]) + ') , 2) + ' \
'power(f73 - (' + str(uploaded_face_encoding[72]) + ') , 2) + ' \
'power(f74 - (' + str(uploaded_face_encoding[73]) + ') , 2) + ' \
'power(f75 - (' + str(uploaded_face_encoding[74]) + ') , 2) + ' \
'power(f76 - (' + str(uploaded_face_encoding[75]) + ') , 2) + ' \
'power(f77 - (' + str(uploaded_face_encoding[76]) + ') , 2) + ' \
'power(f78 - (' + str(uploaded_face_encoding[77]) + ') , 2) + ' \
'power(f79 - (' + str(uploaded_face_encoding[78]) + ') , 2) + ' \
'power(f80 - (' + str(uploaded_face_encoding[79]) + ') , 2) + ' \
'power(f81 - (' + str(uploaded_face_encoding[80]) + ') , 2) + ' \
'power(f82 - (' + str(uploaded_face_encoding[81]) + ') , 2) + ' \
'power(f83 - (' + str(uploaded_face_encoding[82]) + ') , 2) + ' \
'power(f84 - (' + str(uploaded_face_encoding[83]) + ') , 2) + ' \
'power(f85 - (' + str(uploaded_face_encoding[84]) + ') , 2) + ' \
'power(f86 - (' + str(uploaded_face_encoding[85]) + ') , 2) + ' \
'power(f87 - (' + str(uploaded_face_encoding[86]) + ') , 2) + ' \
'power(f88 - (' + str(uploaded_face_encoding[87]) + ') , 2) + ' \
'power(f89 - (' + str(uploaded_face_encoding[88]) + ') , 2) + ' \
'power(f90 - (' + str(uploaded_face_encoding[89]) + ') , 2) + ' \
'power(f91 - (' + str(uploaded_face_encoding[90]) + ') , 2) + ' \
'power(f92 - (' + str(uploaded_face_encoding[91]) + ') , 2) + ' \
'power(f93 - (' + str(uploaded_face_encoding[92]) + ') , 2) + ' \
'power(f94 - (' + str(uploaded_face_encoding[93]) + ') , 2) + ' \
'power(f95 - (' + str(uploaded_face_encoding[94]) + ') , 2) + ' \
'power(f96 - (' + str(uploaded_face_encoding[95]) + ') , 2) + ' \
'power(f97 - (' + str(uploaded_face_encoding[96]) + ') , 2) + ' \
'power(f98 - (' + str(uploaded_face_encoding[97]) + ') , 2) + ' \
'power(f99 - (' + str(uploaded_face_encoding[98]) + ') , 2) + ' \
'power(f100 - (' + str(uploaded_face_encoding[99]) + ') , 2) + ' \
'power(f101 - (' + str(uploaded_face_encoding[100]) + ') , 2) + ' \
'power(f102 - (' + str(uploaded_face_encoding[101]) + ') , 2) + ' \
'power(f103 - (' + str(uploaded_face_encoding[102]) + ') , 2) + ' \
'power(f104 - (' + str(uploaded_face_encoding[103]) + ') , 2) + ' \
'power(f105 - (' + str(uploaded_face_encoding[104]) + ') , 2) + ' \
'power(f106 - (' + str(uploaded_face_encoding[105]) + ') , 2) + ' \
'power(f107 - (' + str(uploaded_face_encoding[106]) + ') , 2) + ' \
'power(f108 - (' + str(uploaded_face_encoding[107]) + ') , 2) + ' \
'power(f109 - (' + str(uploaded_face_encoding[108]) + ') , 2) + ' \
'power(f110 - (' + str(uploaded_face_encoding[109]) + ') , 2) + ' \
'power(f111 - (' + str(uploaded_face_encoding[110]) + ') , 2) + ' \
'power(f112 - (' + str(uploaded_face_encoding[111]) + ') , 2) + ' \
'power(f113 - (' + str(uploaded_face_encoding[112]) + ') , 2) + ' \
'power(f114 - (' + str(uploaded_face_encoding[113]) + ') , 2) + ' \
'power(f115 - (' + str(uploaded_face_encoding[114]) + ') , 2) + ' \
'power(f116 - (' + str(uploaded_face_encoding[115]) + ') , 2) + ' \
'power(f117 - (' + str(uploaded_face_encoding[116]) + ') , 2) + ' \
'power(f118 - (' + str(uploaded_face_encoding[117]) + ') , 2) + ' \
'power(f119 - (' + str(uploaded_face_encoding[118]) + ') , 2) + ' \
'power(f120 - (' + str(uploaded_face_encoding[119]) + ') , 2) + ' \
'power(f121 - (' + str(uploaded_face_encoding[120]) + ') , 2) + ' \
'power(f122 - (' + str(uploaded_face_encoding[121]) + ') , 2) + ' \
'power(f123 - (' + str(uploaded_face_encoding[122]) + ') , 2) + ' \
'power(f124 - (' + str(uploaded_face_encoding[123]) + ') , 2) + ' \
'power(f125 - (' + str(uploaded_face_encoding[124]) + ') , 2) + ' \
'power(f126 - (' + str(uploaded_face_encoding[125]) + ') , 2) + ' \
'power(f127 - (' + str(uploaded_face_encoding[126]) + ') , 2) + ' \
'power(f128 - (' + str(uploaded_face_encoding[127]) + ') , 2) ' \
') as distance FROM user_face_embeddings ORDER BY distance LIMIT 100;'
#print(quryString)
mycursor.execute(quryString)	
face_data = mycursor.fetchall()
if not face_data:
    return jsonify({"match": "No match found"}), 404
else:
    return jsonify({"match": face_data})

Please assist me in fixing it.