File_Transfer/ag.prx at main · ParadoxAI-Co/File_Transfer · GitHub

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import copy
import argparse

import cv2 as cv
import numpy as np
import os
import math
import time
import random
import tkinter as tk
import datetime
from colorama import init, Fore
def getFaceBox(net, frame, conf_threshold=0.7):
    frameOpencvDnn = frame.copy()
    frameHeight = frameOpencvDnn.shape[0]
    frameWidth = frameOpencvDnn.shape[1]
    blob = cv.dnn.blobFromImage(frameOpencvDnn, 1.0, (300, 300), [104, 117, 123], True, False)

    net.setInput(blob)
    detections = net.forward()
    bboxes = []
    for i in range(detections.shape[2]):
        confidence = detections[0, 0, i, 2]
        if confidence > conf_threshold:
            x1 = int(detections[0, 0, i, 3] * frameWidth)
            y1 = int(detections[0, 0, i, 4] * frameHeight)
            x2 = int(detections[0, 0, i, 5] * frameWidth)
            y2 = int(detections[0, 0, i, 6] * frameHeight)
            bboxes.append([x1, y1, x2, y2])
    return frameOpencvDnn, bboxes

faceProto = "data/ag/ag_models/opencv_face_detector.pbtxt"
faceModel = "data/ag/ag_models/opencv_face_detector_uint8.pb"

ageProto = "data/ag/ag_models/age_deploy.prototxt"
ageModel = "data/ag/ag_models/age_net.caffemodel"

genderProto = "data/ag/ag_models/gender_deploy.prototxt"
genderModel = "data/ag/ag_models/gender_net.caffemodel"

MODEL_MEAN_VALUES = (78.4263377603, 87.7689143744, 114.895847746)
ageList = ['(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)']
genderList = ['Male', 'Female']


ageNet = cv.dnn.readNet(ageModel, ageProto)
genderNet = cv.dnn.readNet(genderModel, genderProto)
faceNet = cv.dnn.readNet(faceModel, faceProto)

cap = cv.VideoCapture(0)
padding = 20
os.chdir("data/ag")
while cv.waitKey(1) < 0:
    t = time.time()
    hasFrame, frame = cap.read()
    if not hasFrame:
        cv.waitKey()
        break

    frameFace, bboxes = getFaceBox(faceNet, frame)
    count = 0
    if not bboxes:
        print("No face Detected, try again")
        continue

    for bbox in bboxes:
        face = frame[max(0,bbox[1]-padding):min(bbox[3]+padding,frame.shape[0]-1),max(0,bbox[0]-padding):min(bbox[2]+padding, frame.shape[1]-1)]

        blob = cv.dnn.blobFromImage(face, 1.0, (227, 227), MODEL_MEAN_VALUES, swapRB=False)
        genderNet.setInput(blob)
        genderPreds = genderNet.forward()
        gender = genderList[genderPreds[0].argmax()]

        ageNet.setInput(blob)
        agePreds = ageNet.forward()
        age = ageList[agePreds[0].argmax()]
        global label
        label = "{},{}".format(gender, age)
    current_time = datetime.datetime.now()
    with open("{}{}.prx".format(current_time.day, current_time.hour), 'w') as f:
        f.write("Age: {} Gender: {}".format(age, gender))
    break
pd = os.path.dirname(os.getcwd())
os.chdir(pd)
pd = os.path.dirname(os.getcwd())
os.chdir(pd)