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def gen_frames(): # generate frame by frame from camera | |
while True: | |
# Capture frame by frame | |
success, frame = camera.read() | |
if not success: | |
break | |
else: | |
gray_img= cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) | |
faces_detected = face_haar_cascade.detectMultiScale(gray_img, 1.32, 5) |
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<!doctype html> | |
<html lang="en"> | |
<head> | |
<meta name="viewport" content="width=device-width, initial-scale=1"> | |
<!-- Required meta tags --> | |
<meta charset="utf-8"> | |
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> | |
<meta charset="utf-8"> |
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flask | |
flask-cors | |
nlpcloud | |
trafilatura |
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flask | |
flask-cors | |
trafilatura | |
nlpcloud | |
python-dotenv |
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import json | |
from flask import Flask, request, jsonify, Response | |
import nlpcloud | |
from flask_cors import CORS, cross_origin | |
import trafilatura | |
from dotenv import load_dotenv | |
import os | |
app = Flask(__name__) | |
CORS(app, support_credentials=True) |
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fetch("http://127.0.0.1:5000/getSummary", { | |
"body": JSON.stringify({"url":"https://owasp.org/www-community/attacks/csrf"}), | |
"method": "POST", | |
"headers":{ | |
"Content-Type": "application/json" | |
} | |
}).then(response=> response.body). then(rb => { | |
const reader = rb.getReader(); | |
return new ReadableStream({ | |
start(controller) { |
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token = "API_KEY" |
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