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0d9713a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 | # from flask import Flask, render_template, Response
# import cv2
# from mtcnn import MTCNN
# import base64
# import numpy as np
# import concurrent.futures
# app = Flask(__name__)
# class FaceDetector:
# def __init__(self):
# self.detector = MTCNN()
# self.face_count = 0
# def detect_faces(self, frame):
# faces = self.detector.detect_faces(frame)
# self.face_count = len(faces)
# return faces
# face_detector = FaceDetector()
# def generate_frames():
# camera = cv2.VideoCapture(0) # 0 indicates the default camera (you can change it to the camera index you want to use)
# while True:
# success, frame = camera.read()
# if not success:
# break
# gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# # Perform face detection
# faces = face_detector.detect_faces(frame)
# for face in faces:
# x, y, w, h = face['box']
# cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
# # Display face count on each frame
# font = cv2.FONT_HERSHEY_SIMPLEX
# cv2.putText(frame, f'Faces: {face_detector.face_count}', (10, 30), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
# _, buffer = cv2.imencode(".jpg", cv2.resize(frame, (0, 0), fx=0.5, fy=0.5))
# img_data = buffer.tobytes()
# yield (b'--frame\r\n'
# b'Content-Type: image/jpeg\r\n\r\n' + img_data + b'\r\n\r\n')
# camera.release()
# @app.route('/')
# def index():
# return render_template('index.html')
# @app.route('/detect_faces')
# def detect_faces():
# return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
# if __name__ == '__main__':
# app.run(debug=True)
from flask import Flask, render_template, Response, request
import cv2
from mtcnn import MTCNN
import numpy as np
import concurrent.futures
app = Flask(__name__)
class FaceDetector:
def __init__(self):
self.detector = MTCNN()
self.face_count = 0
def detect_faces(self, frame):
faces = self.detector.detect_faces(frame)
self.face_count = len(faces)
return faces
face_detector = FaceDetector()
def generate_frames(camera_index):
camera = cv2.VideoCapture(camera_index)
while True:
success, frame = camera.read()
if not success:
break
# Perform face detection
faces = face_detector.detect_faces(frame)
for face in faces:
x, y, w, h = face['box']
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
# Display face count on each frame
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame, f'Faces: {face_detector.face_count}', (10, 30), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
_, buffer = cv2.imencode(".jpg", cv2.resize(frame, (0, 0), fx=0.5, fy=0.5))
img_data = buffer.tobytes()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + img_data + b'\r\n\r\n')
camera.release()
@app.route('/')
def index():
return render_template('pg2.html')
@app.route('/detect_faces')
def detect_faces():
camera_index = int(request.args.get('camera_index', 1))
return Response(generate_frames(camera_index), mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
app.run(debug=True)
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