Using PIP Python Package
iApp Technology just released a PIP Python Package on Face Detection.
For easing the python development using iApp AI API service, we have released the iapp_ai python pip package. It is the api client library for iApp AI API service for python.
Installation
$ pip install iapp_aiNote: It can be either pip or pip3 depend on your environment.
Calling Face Detection API
# Face Detection API required an image file path
# Single Face Detection
api.face_detect_single("iapp_ai/media/passport.jpg", "iApp").json()
# Multiple Face Detection
api.face_detect_multi("iapp_ai/media/passport.jpg", "iApp").json()Example Usages
import iapp_ai
pyt
# You can request API key at https://ai.iapp.co.th
apikey = 'XXXXX_Your_API_Key_XXXXX'
api = iapp_ai.api(apikey)
# Face Detection API required an image file path
# Single Face Detection
result = api.face_detect_single("iapp_ai/media/passport.jpg", "iApp").json()
print(result)
# {
# 'bbox': {'xmax': 202.30653381347656,
# 'xmin': 81.03941345214844,
# 'ymax': 364.5769958496094,
# 'ymin': 216.234130859375},
# 'detection_score': 0.999946117401123,
# 'face': 'data:image/png;base64, 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',
# 'feature': '[0.0063276035, 0.053983275, 0.063125744, -0.056844063, 0.0109783085, -0.040525876, 0.0012875537, 0.008345665, 0.04152181, -0.0059968955, 0.003957388, 0.025650345, 0.0139219705, 0.054407857, 0.085155495, 0.060351763, 0.010360959, 0.11966012, 0.10008971, 0.0754888, -0.04961645, -0.017568769, 0.02722117, -0.0074627106, -0.001852635, -0.058803983, 0.06311055, 0.0003803191, 0.02154163, 0.021787355, 0.016615985, -0.00010560776, -0.026270524, 0.055930384, 0.04163311, -0.01463029, 0.0069261454, -0.02030536, 0.12834539, 0.031990923, 0.046556417, 0.05767328, -0.04347385, -0.021849237, -0.042204294, 0.017241253, 0.022834962, -0.01561912, 0.03373753, 0.07497015, 0.046285175, -0.05970527, 0.017042136, -0.07286729, 0.0493543, 0.12468433, -0.022261368, 0.025134344, -0.107936986, -0.030413022, -0.06870085, -0.00877329, -0.06441421, -0.00012654591, -0.035477724, 0.007739441, 0.027253427, -0.030975347, 0.10033078, 0.092037395, -0.03542829, -0.011367502, -0.0010421318, 0.012088898, 0.03448258, 0.0665386, -0.017977562, 0.0136662945, -0.049114566, -0.011942528, -0.0094365515, -0.0018772021, -0.004239277, 0.010784469, -0.06699133, -0.06455332, 0.00073150743, 0.0074654045, 0.008003496, -0.03481075, -0.04029029, 0.007954266, 0.021139506, -0.026849546, 0.074273676, -0.033621877, -0.010842816, -0.051575862, 0.048840117, 0.001417258, 0.048228677, -0.035117816, -0.029609835, -0.020305736, -0.021421699, -0.035684496, -0.03885661, 0.030015973, 0.082972035, -0.0042267353, -0.021044193, 0.066834636, -0.03469954, -0.030781196, 0.0022335069, 0.1270456, 0.0137245385, 0.15907766, -0.033364095, -0.018152528, 0.05314111, -0.003793487, 0.05951645, -0.040761158, -0.019168075, 0.018007794, 0.05514791, -0.005754659, 0.01423506, 0.016516466, 0.019224081, 0.008454211, 0.05327612, 0.02277847, 0.0034147084, 0.019097438, -0.08441977, -0.060508907, -0.065536655, -0.007349361, -0.030036958, -0.029433215, -0.029049903, -0.011782274, 0.05701369, 0.08467278, 0.020804837, 0.01307125, 0.040415164, 0.010958562, -0.055431098, -0.05504812, -0.043048322, 0.013210876, -0.015592378, 0.038080323, 0.034006, -0.03849802, -0.0125254765, -0.016955223, 0.011559768, 0.05137864, 0.016504, -0.0048203375, 0.019223273, -0.009550119, 0.046902083, 0.040686615, -0.034054615, 0.051882785, 0.05217705, -0.04129343, -0.035980813, 0.031534906, 0.026131846, -0.012367606, -0.030757258, 0.05486598, -0.02448148, -0.04665106, 0.01828044, -0.09085556, -0.08484297, -0.013877999, -0.036102396, -0.015248968, 0.029470235, 0.024446411, -0.022840844, -0.012136167, -0.018062118, -0.027884051, -0.06489081, 0.085634954, 0.020452205, -0.006561045, -0.024856992, 0.004637928, -0.006405105, -0.01462166, 0.012704767, 0.046187192, 0.036308825, 0.012694416, -0.075260185, -0.009790872, 0.01282923, 0.029497974, -0.0009382374, -0.057217564, 0.0658865, -0.0023279705, -0.062155154, 0.01214691, 0.024090242, 0.0008757728, 0.069366015, -0.0011863243, 0.016879799, -0.08465692, 0.014432098, 0.082603745, -0.060773, 0.014493894, 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-0.054431155, -0.024977667, -0.0052783643, 0.0067303884, 0.065724045, -0.020694327, 0.010488514, 0.056008566, 0.08008653, -0.02447237, 0.014966813, -0.0016027731, -0.022245575, -0.0077517214, 0.0047056405, -0.03039826, -0.011671708, 0.019239692, 0.14256664, -0.010456125, 0.03938853, -0.011526102, 0.03256885, 0.006480175, 0.04029494, 0.092870876, 0.0048286337, -0.011494458, -0.03439038, -0.009581201, 0.016784936, 0.010412918, -0.0027428768, 0.025990466, 0.13621943, -0.055987593, -0.019557914, 0.026582958, -0.04743681, 0.03566752, -0.010194367, 0.07319426, -0.04876895, -0.023200953, 0.004854468, 0.028626664, 0.07185032, 0.0643467, -0.024008647, -0.020126175, 0.03356395, -0.00067361287, 0.027355794, 0.038464557, 0.014856804, -0.06386498, 0.03894236, -0.035060845, 0.063157685, -0.07032134, 0.008308251, -0.08266254, 0.02515444]',
# 'message': 'successfully performed',
# 'process_time': 0.13691496849060059
# }
# Multiple Face Detection
result = api.face_detect_multi("iapp_ai/media/passport.jpg", "iApp").json()
print(result)
# {
# 'message': 'successfully performed',
# 'process_time': 0.12974238395690918,
# 'result': [{'bbox': {'xmax': 202.30653381347656,
# 'xmin': 81.03941345214844,
# 'ymax': 364.5769958496094,
# 'ymin': 216.234130859375},
# 'detection_score': 0.999946117401123,
# 'face': 'data:image/png;base64, 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# }Full Example in Google Colaboratory
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