💎一站式轻松地调用各大LLM模型接口，支持GPT4、智谱、星火、月之暗面及文生图 广告
只是本地跑了个demo，有需要的时候查看一下，在此记录一下。 Vahid Kazemi 和 Josephine Sullivan 的《使用回归树一毫秒脸部对准》论文 https://github.com/ageitgey/face_recognition/blob/master/Dockerfile#L6-L34 docker run -v /D/face_recognition/www:/mnt -d -p 127.0.0.1:5001:5001 -it facedemo:v1 /bin/bash pip install -i https://pypi.tuna.tsinghua.edu.cn/simple face_recognition pip install -i https://pypi.tuna.tsinghua.edu.cn/simple scikit-image pip install -i https://pypi.tuna.tsinghua.edu.cn/simple opencv-python pip install -i https://pypi.tuna.tsinghua.edu.cn/simple flask pip install scikit-image ```python # This is a _very simple_ example of a web service that recognizes faces in uploaded images. # Upload an image file and it will check if the image contains a picture of Barack Obama. # The result is returned as json. For example: # # $ curl -XPOST -F "file=@obama2.jpg" http://127.0.0.1:5001 # # Returns: # # { # "face_found_in_image": true, # "is_picture_of_obama": true # } # # This example is based on the Flask file upload example: http://flask.pocoo.org/docs/0.12/patterns/fileuploads/ # NOTE: This example requires flask to be installed! You can install it with pip: # $ pip3 install flask import face_recognition from flask import Flask, jsonify, request, redirect # You can change this to any folder on your system ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif'} app = Flask(__name__) def allowed_file(filename): return '.' in filename and \ filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS @app.route('/', methods=['GET', 'POST']) def upload_image(): # Check if a valid image file was uploaded if request.method == 'POST': if 'file1' not in request.files: return redirect(request.url) file1 = request.files['file1'] if file1.filename == '': return redirect(request.url) #if file1 and allowed_file(file1.filename): # The image file seems valid! Detect faces and return the result. # return detect_faces_in_image(file1) if 'file2' not in request.files: return redirect(request.url) file2 = request.files['file2'] if file2.filename == '': return redirect(request.url) if file1 and allowed_file(file1.filename) and file2 and allowed_file(file2.filename): # The image file seems valid! Detect faces and return the result. return detect_faces_in_image(file1,file2) # If no valid image file was uploaded, show the file upload form: return ''' <!doctype html> <title>人脸对比</title> <h1>人脸对比demo</h1> <form method="POST" enctype="multipart/form-data"> 人脸图片1：<input type="file" name="file1"><br><br> 人脸图片2：<input type="file" name="file2"> <input type="submit" value="对比"> </form> ''' def detect_faces_in_image(file1,file2): # Pre-calculated face encoding of Obama generated with face_recognition.face_encodings(img) known_face_encoding = [-0.09634063, 0.12095481, -0.00436332, -0.07643753, 0.0080383, 0.01902981, -0.07184699, -0.09383309, 0.18518871, -0.09588896, 0.23951106, 0.0986533 , -0.22114635, -0.1363683 , 0.04405268, 0.11574756, -0.19899382, -0.09597053, -0.11969153, -0.12277931, 0.03416885, -0.00267565, 0.09203379, 0.04713435, -0.12731361, -0.35371891, -0.0503444 , -0.17841317, -0.00310897, -0.09844551, -0.06910533, -0.00503746, -0.18466514, -0.09851682, 0.02903969, -0.02174894, 0.02261871, 0.0032102 , 0.20312519, 0.02999607, -0.11646006, 0.09432904, 0.02774341, 0.22102901, 0.26725179, 0.06896867, -0.00490024, -0.09441824, 0.11115381, -0.22592428, 0.06230862, 0.16559327, 0.06232892, 0.03458837, 0.09459756, -0.18777156, 0.00654241, 0.08582542, -0.13578284, 0.0150229 , 0.00670836, -0.08195844, -0.04346499, 0.03347827, 0.20310158, 0.09987706, -0.12370517, -0.06683611, 0.12704916, -0.02160804, 0.00984683, 0.00766284, -0.18980607, -0.19641446, -0.22800779, 0.09010898, 0.39178532, 0.18818057, -0.20875394, 0.03097027, -0.21300618, 0.02532415, 0.07938635, 0.01000703, -0.07719778, -0.12651891, -0.04318593, 0.06219772, 0.09163868, 0.05039065, -0.04922386, 0.21839413, -0.02394437, 0.06173781, 0.0292527 , 0.06160797, -0.15553983, -0.02440624, -0.17509389, -0.0630486 , 0.01428208, -0.03637431, 0.03971229, 0.13983178, -0.23006812, 0.04999552, 0.0108454 , -0.03970895, 0.02501768, 0.08157793, -0.03224047, -0.04502571, 0.0556995 , -0.24374914, 0.25514284, 0.24795187, 0.04060191, 0.17597422, 0.07966681, 0.01920104, -0.01194376, -0.02300822, -0.17204897, -0.0596558 , 0.05307484, 0.07417042, 0.07126575, 0.00209804] # biden_image = face_recognition.load_image_file("zhanghui.jpg") # known_face_encoding = face_recognition.face_encodings(biden_image)[0] # Load the uploaded image file img = face_recognition.load_image_file(file1) # Get face encodings for any faces in the uploaded image unknown_face_encodings = face_recognition.face_encodings(img) print('##############################################################'); print(unknown_face_encodings); print('##############################################################'); # Load the uploaded image file biden_image = face_recognition.load_image_file(file2) # Get face encodings for any faces in the uploaded image known_face_encoding = face_recognition.face_encodings(biden_image) print(known_face_encoding); print('##############################################################'); face_found = False is_user = False if len(unknown_face_encodings) > 0 and len(known_face_encoding) > 0: face_found = True # See if the first face in the uploaded image matches the known face of Obama # match_results = face_recognition.compare_faces([known_face_encoding], unknown_face_encodings[0],0.50) match_results = face_recognition.compare_faces([known_face_encoding[0]], unknown_face_encodings[0],0.40) print('############################aaaa##################################'); print(match_results); print('############################aaaaa##################################'); if match_results[0]: is_user = True # Return the result as json result = { "是否都为人脸图片": face_found, "是否一个人": is_user } return jsonify(result) if __name__ == "__main__": app.run(host='0.0.0.0', port=5001, debug=True) ``` ``