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使用 OpenCV-SeventhSense SOTA 模型進行人臉識別

OpenCV 最近發(fā)布了與 SeventhSense 合作的人臉識別 SDK。它是 NIST 人臉識別挑戰(zhàn)賽(2022 年 3 月)的前 10 名模型,速度極快且無需 GPU。

在 opencv-seventhsense FR webapp 中,你可以創(chuàng)建一個集合并將組織中的人員聚合到組中。添加到集合中的每個人都具有姓名、出生日期、國籍、性別等屬性,可用于識別此人。

下面是 webapp 的鏈接和 UI 的快照。

OpenCV — SeventhSense-人臉識別網(wǎng)絡(luò)應用程序

Python 和 C++ SDK 可用于將圖像對象發(fā)布到 API 并檢索給定圖像的檢測響應。

下面的代碼片段使你能夠?qū)⒔巧砑拥郊现校z索給定測試圖像的檢測響應。

我使用自己的舊照片來查看模型是否能夠準確檢測到我的臉。

導入圖片到 FR Webapp

# Import the packages

from opencv.fr import FR

from opencv.fr.persons.schemas import PersonBase,PersonGender

from pathlib import Path

import cv2

import json

# Define the region, and developer key

BACKEND_URL = "https://us.opencv.fr"

DEVELOPER_KEY = "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"

# Initialize the SDK

sdk = FR(BACKEND_URL, DEVELOPER_KEY)

directory = "/imagepath"

files = Path(directory).glob('*')

# Here we get an existing collection, but this could also

# be a collection you created

all_collections = sdk.collections.list()

all_collections = str(all_collections)

all_collections = all_collections.replace("'", """)

all_collections = json.loads(all_collections)

col_id = all_collections['collections'][0]['id']

print(f"The collection id is - {col_id}")

my_collection = sdk.collections.get(col_id)

for file in files:

   if Path(str(file)).suffix == ".jpg" :

       # Create PersonBase

       image = cv2.imread(str(file))

       person = PersonBase([image], name="Rajathithan Rajasekar",

           gender=PersonGender("M"), nationality="Indian",)

       # Add collection to the person's collections

       person.collections.a(chǎn)ppend(my_collection)

       # Create the person

       person = sdk.persons.create(person)

       print(f'Uploaded the image file - {file}')

從 FR webapp 人物集合中檢測給定圖像

from opencv.fr.search.schemas import DetectionRequest, SearchOptions

from opencv.fr.a(chǎn)pi_error import APIError, APIDataValidationError

from pathlib import Path

from opencv.fr import FR

import json

from json import JSONDecodeError

import cv2

import numpy as np

import imutils

import time

BACKEND_URL = "https://us.opencv.fr"

DEVELOPER_KEY = "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"

# Initialize the SDK

sdk = FR(BACKEND_URL, DEVELOPER_KEY)

image_base_path = Path("sample_images")

image_path = "imagepath/test/test.jpg"

sourceimage = "imagepath/rajathithan-rajasekar.jpg"

# resize source image

simg = cv2.imread(sourceimage)

simg = imutils.resize(simg, width=640)

simg = imutils.resize(simg, height=480)

#Read old test image

frame = cv2.imread(image_path)

print(frame.shape)

#Get collection id

all_collections = sdk.collections.list()

all_collections = str(all_collections)

all_collections = all_collections.replace("'", """)

all_collections = json.loads(all_collections)

col_id = all_collections['collections'][0]['id']

print(f"The collection id is - {col_id}")

#Initilize the search options

options = SearchOptions(

   collection_id=col_id,

   min_score = 0.8,



#Detection request with search options

detect_request_with_search = DetectionRequest(image_path,options)

detectionObject = sdk.search.detect(detect_request_with_search)

print(detectionObject)

bbox = detectionObject[0].box

print(bbox)

personInfo = detectionObject[0].persons[0]

print(f"Name:{personInfo.person.name}")

print(f"Gender:{personInfo.person.gender}")

print(f"Nationality:{personInfo.person.nationality}")

print(f"Score:{personInfo.score}")

def rec_frame_display(frame: np.ndarray, roi, personInfo) -> np.ndarray:

   diff1 = round((roi['bottom'] - roi['top'])/4)

   diff2 = round((roi['left'] - roi['right'])/4)
   

   cv2.line(frame, (roi['left'],roi['top']), (roi['left'],roi['top']+diff1), (0, 200, 0), 4)

   cv2.line(frame, (roi['left'],roi['bottom']), (roi['left'],roi['bottom']-diff1), (0, 200, 0), 4)
   

   cv2.line(frame, (roi['right'],roi['top']), (roi['right'],roi['top']+diff1), (0, 200, 0), 4)

   cv2.line(frame, (roi['right'],roi['bottom']), (roi['right'],roi['bottom']-diff1), (0, 200, 0), 4)
   
   

   cv2.line(frame, (roi['left'],roi['top']), (roi['left']-diff2,roi['top']), (0, 200, 0), 4)

   cv2.line(frame, (roi['left'],roi['bottom']), (roi['left']-diff2,roi['bottom']), (0, 200, 0), 4)
   

   cv2.line(frame, (roi['right'],roi['top']), (roi['right']+diff2,roi['top']), (0, 200, 0), 4)

   cv2.line(frame, (roi['right'],roi['bottom']), (roi['right']+diff2,roi['bottom']), (0, 200, 0), 4)

   cv2.putText(frame, "Name : " + personInfo.person.name, (50, 50),

       cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255),2,cv2.LINE_AA, False)
   

   cv2.putText(frame, "Gender : " + str(personInfo.person.gender), (50, 150),

       cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255),2,cv2.LINE_AA, False)
   

   cv2.putText(frame, "Nationality : " + str(personInfo.person.nationality), (50, 250),

       cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255),2,cv2.LINE_AA, False)
   

   cv2.putText(frame, "Confidence Score : " + str(round(personInfo.score * 100,2)) + " %", (50, 350),

       cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 255, 255),2,cv2.LINE_AA, False)
   

   return frame

roi = json.loads(str(bbox).replace("'","""))

frame = rec_frame_display(frame, roi, personInfo)

frame = imutils.resize(frame, width = 640,height = 480)

combine = np.concatenate((simg, frame), axis=1)

cv2.imwrite("final.jpg",combine)

cv2.imshow("Face recognition on an old pic",combine)

cv2.waitKey(0)

cv2.destroyAllWindows()

左側(cè)照片是我當前的圖像,右側(cè)照片是我?guī)в袡z測結(jié)果的舊圖像。

       原文標題 : 使用 OpenCV-SeventhSense SOTA 模型進行人臉識別

聲明: 本文由入駐維科號的作者撰寫,觀點僅代表作者本人,不代表OFweek立場。如有侵權(quán)或其他問題,請聯(lián)系舉報。

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