jnhg_ai_code/utils/renwu0122.py

from pathlib import Path
import matplotlib.path as mat
from utils.general import strtolstl
from utils.general import compute_IOU
from torchvision import transforms
from PIL import Image
import torch
import torch.nn.functional as F
import numpy as np
from ultralytics.engine.results import Results
from shapely.geometry import Point

from shapely.geometry.polygon import Polygon
mean, std = [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]
test = transforms.Compose([transforms.Resize((224,224)),
        #transforms.CenterCrop(224),
        transforms.ToTensor(),
        transforms.Normalize(mean=mean, std=std)
                           ])
def clapre(modelcla,claimg,clapoint):
    imgten = torch.stack(claimg,dim=0)
    clapoint = torch.stack(clapoint,dim=0)
    imgten = imgten.to(0)
    result = modelcla(imgten)
    result = F.softmax(result)
    print(result)
    index = result.argmax(1)
    index = index.cpu().numpy()
    index = np.argwhere(index<5)
    index = index.reshape(-1)
    print(index)
    if len(index)>0:
        print(clapoint[index])
        return clapoint[index]
    else:
        return None

class Helmet:
    def __init__(self):
        self.flag = False
    def getflag(self,det,persondet,annotator,fence=0,point=None,names=None,rname=None,num=1):
        #print(type(det))
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag
class Uniform:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                          xyxy[3].cpu().item())
                                    p2 = (
                                    int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                    xyxy[3].cpu().item())
                                    pt = [p1, p2]
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag

class Fall:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag

class Personcount:
    def __init__(self):
        self.flag = False

    def getflag(self, det,persondet, annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        detnum = 0
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                #self.flag = True
                                detnum = detnum+1
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        detnum = detnum+1
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        #self.flag = True
                else:
                    if persondet is None:
                        #self.flag = True
                        detnum = detnum+1
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                detnum = detnum+1
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                #self.flag = True
        if detnum >= num:
            self.flag = True
        return self.flag
    
class Arm:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                            # c = int(cls)  # integer class
                            # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0,0,255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag
    
class Bag:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag
    
class Cross:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        detnum = 0
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                detnum = detnum+1
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        detnum = detnum+1
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        detnum = detnum+1
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                detnum = detnum +1 
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag

class Extinguisher:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag

def calculate_iou(box1, box2):

    # 计算交集区域 也就是找到次左上 次右下

    x1_int = max(box1[0], box2[0])

    y1_int = max(box1[1], box2[1])

    x2_int = min(box1[2], box2[2])

    y2_int = min(box1[3], box2[3])



    # 交集区域的宽高

    width_int = max(0, x2_int - x1_int)

    height_int = max(0, y2_int - y1_int)

    area_int = width_int * height_int



    # 计算两个框的面积

    area_box1 = (box1[2] - box1[0]) * (box1[3] - box1[1])

    area_box2 = (box2[2] - box2[0]) * (box2[3] - box1[1])



    # 计算并集面积

    area_union = area_box1 + area_box2 - area_int



    # 计算IoU

    iou = area_int / area_union if area_union > 0 else 0

    return iou

class Persontre1:
    def __init__(self):
        self.flag = False
        self.classifier_model = torch.load('/home/h3c/yolo/persontrecls.pt') 
    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1,im0=None):
        self.flag = False
        dirp = {}
        dirf = {}
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:
                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                              xyxy[3].cpu().item())
                        p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              xyxy[3].cpu().item())
                        pt = [p1, p2]
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                            if c==0:
                                dirp.setdefault(0,[])
                                dirp[0].append(xyxy)
                            elif c in [1,2]:
                                dirp.setdefault(1,[])
                                dirp[1].append(xyxy)
                                dirf.setdefault(1,[])
                                dirf[1].append(xyxy)
                            elif c==3:
                                dirp.setdefault(1,[])
                                dirp[1].append(xyxy)
                            elif c==4:
                                dirf.setdefault(0,[])
                                dirf[0].append(xyxy)
                                #annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        #annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        #self.flag = True
                                        if c==0:
                                            dirp.setdefault(0,[])
                                            dirp[0].append(xyxy)
                                        elif c in [1,2]:
                                            dirp.setdefault(1,[])
                                            dirp[1].append(xyxy)
                                            dirf.setdefault(1,[])
                                            dirf[1].append(xyxy)
                                        elif c==3:
                                            dirp.setdefault(1,[])
                                            dirp[1].append(xyxy)
                                        elif c==4:
                                            dirf.setdefault(0,[])
                                            dirf[0].append(xyxy)
                else:
                    if persondet is None:
                        #self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        #label = None
                        #annotator.box_label(xyxy, None, color=(0, 0, 255))
                        if c==0:
                            dirp.setdefault(0,[])
                            dirp[0].append(xyxy)
                        elif c in [1,2]:
                            dirp.setdefault(1,[])
                            dirp[1].append(xyxy)
                            dirf.setdefault(1,[])
                            dirf[1].append(xyxy)
                        elif c==3:
                            dirp.setdefault(1,[])
                            dirp[1].append(xyxy)
                        elif c==4:
                            dirf.setdefault(0,[])
                            dirf[0].append(xyxy)
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                #annotator.box_label(xyxy, None, color=(0, 0, 255))
                                #self.flag = True
                                if c==0:
                                    dirp.setdefault(0,[])
                                    dirp[0].append(xyxy)
                                elif c in [1,2]:
                                    dirp.setdefault(1,[])
                                    dirp[1].append(xyxy)
                                    dirf.setdefault(1,[])
                                    dirf[1].append(xyxy)
                                elif c==3:
                                    dirp.setdefault(1,[])
                                    dirp[1].append(xyxy)
                                elif c==4:
                                    dirf.setdefault(0,[])
                                    dirf[0].append(xyxy)
        if len(dirp.keys()) == 2:
            claimg = []
            clapoint = []
            for person in dirp[0]:
                for other in dirp[1]:
                    iou, newxyxy = compute_IOU(person, other)
                    if iou>0.1:
                        print(newxyxy)
                        imgtmp = im0[int(newxyxy[1]):int(newxyxy[3]),int(newxyxy[0]):int(newxyxy[2])]
                        imgtmp = imgtmp[...,::-1]
                        imgtmp = Image.fromarray(imgtmp)
                        imgten1 = test(imgtmp)
                        claimg.append(imgten1)
                        clapoint.append((newxyxy))
                        result = clapre(self.classifier_model,claimg,clapoint)
                        #imgten = imgten1[None]
                        #imgten = imgten.to(0)
                        #result = modelcla(imgten)
                        #result = F.softmax(result, dim=1)
                        #cla = result.argmax(1)
                        if result is not None:
                            self.flag = True
                            for res in result:
                                print(res)
                                annotator.box_label(res, None, color=(0,0,255))
        if len(dirp.keys()) == 2:
            claimg = []
            clapoint = []
            for person in dirp[0]:
                for other in dirp[1]:
                    iou, newxyxy = compute_IOU(person, other)
                    if iou>0.1:
                        print(newxyxy)
                        imgtmp = im0[int(newxyxy[1]):int(newxyxy[3]),int(newxyxy[0]):int(newxyxy[2])]
                        imgtmp = imgtmp[...,::-1]
                        imgtmp = Image.fromarray(imgtmp)
                        imgten1 = test(imgtmp)
                        claimg.append(imgten1)
                        clapoint.append((newxyxy))
                        result = clapre(self.classifier_model,claimg,clapoint)
                        #imgten = imgten1[None]
                        #imgten = imgten.to(0)
                        #result = modelcla(imgten)
                        #result = F.softmax(result, dim=1)
                        #cla = result.argmax(1)
                        if result is not None:
                            self.flag = True
                            for res in result:
                                print(res)
                                annotator.box_label(res, None, color=(0,0,255))
        return self.flag

class Persontre:
    def __init__(self):
        self.flag = False
        self.classifier_model = torch.load('/home/h3c/yolo/persontrecls.pt') 
    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1,im0=None):
        self.flag = False
        target_classes = [1, 2, 3]
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        boxes = results.boxes
        person_boxes = []

        target_boxes = []

        cls4_boxes = []



        # 处理检测结果

        for i in range(len(boxes)):

            cls = int(boxes.cls[i].item())

            con = boxes.conf[i].item()



            if cls == 0 and con > 0.1:  # 如果是 "person" 类别

                x1, y1, x2, y2 = boxes.xyxy[i].tolist()

                person_boxes.append([x1, y1, x2, y2])



            if cls in target_classes and con > 0.1:  # 目标类别（bag, box, cart）

                x1, y1, x2, y2 = boxes.xyxy[i].tolist()

                target_boxes.append([x1, y1, x2, y2])



            if cls == 4 and con > 0.1:  # 如果是 "cls 4" 类别

                x1, y1, x2, y2 = boxes.xyxy[i].tolist()

                cls4_boxes.append([x1, y1, x2, y2])



        # 如果检测到 "person" 类别和目标框，计算IoU

        if person_boxes and target_boxes:

            for i, person_box in enumerate(person_boxes):

                person_center_y = (person_box[1] + person_box[3]) / 2



                for j, target_box in enumerate(target_boxes):

                    target_center_y = (target_box[1] + target_box[3]) / 2



                    # 判断目标框的中心点是否在person框的下方

                    if target_center_y + 20 > person_center_y:  # 根据需要调整此阈值

                        iou = calculate_iou(person_box, target_box)



                        if iou > 0:  # IoU大于0，进入新的判断

                            # 创建一个包围person和target框的区域 本来思路是判断脚是否在这个大框框里面 但是这个不合理 应该判断脚是不是在这个交集里面，再检测脚和人与物交集有没有交集

                            min_x = max(person_box[0], target_box[0])

                            min_y = max(person_box[1], target_box[1])

                            max_x = min(person_box[2], target_box[2])

                            max_y = min(person_box[3], target_box[3])



                            target_area = (min_x, min_y, max_x, max_y)





                            # 检查是否有cls 4物体在这个区域内

                            for cls4_box in cls4_boxes: #比较巧妙 提前存储这个变量 然后检测这个物体是不是在这里面

                                # 判断cls 4框是否与这个区域有交集

                                inter_x1 = max(cls4_box[0], target_area[0])

                                inter_y1 = max(cls4_box[1], target_area[1])

                                inter_x2 = min(cls4_box[2], target_area[2])

                                inter_y2 = min(cls4_box[3], target_area[3])



                                if inter_x1 < inter_x2 and inter_y1 < inter_y2:

                                    # 计算交集区域的面积

                                    intersection_area = (inter_x2 - inter_x1) * (inter_y2 - inter_y1)



                                    # 计算 cls4_box 的面积

                                    cls4_area = (cls4_box[2] - cls4_box[0]) * (cls4_box[3] - cls4_box[1])



                                    # 计算交集区域占 cls4_box 面积的比例

                                    overlap_ratio = intersection_area / cls4_area
                                    if overlap_ratio > 0.5:
                                        self.flag = True
        return self.flag
class Danager:
    def __init__(self):
        self.flag = False

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        for *xyxy, conf, cls in reversed(det):
            c = int(cls)
            labelname = names[c]
            if labelname in rname:
                if fence == 1:

                    pointa = strtolstl(point)
                    for poi in pointa:
                        p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 2),
                              int(xyxy[1].cpu().item() + (xyxy[3].cpu().item() - xyxy[1].cpu().item()) / 2))
                        #p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                              #xyxy[3].cpu().item())
                        pt = [p1]
                        print(f'pt = {pt}')
                        print(f'poi = {poi}')
                        inflag = mat.Path(poi).contains_points(pt)
                        if inflag.any():
                            if persondet is None:
                                self.flag = True
                                # c = int(cls)  # integer class
                                # label = f'{self.names[c]} {conf:.2f}'
                                label = None
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                            else:
                                for person in persondet:
                                    personinflag = mat.Path(person).contains_points(pt)
                                    if personinflag.any():
                                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                                        self.flag = True
                else:
                    if persondet is None:
                        self.flag = True
                        # c = int(cls)  # integer class
                        # label = f'{self.names[c]} {conf:.2f}'
                        label = None
                        annotator.box_label(xyxy, None, color=(0, 0, 255))
                    else:
                        for person in persondet:
                            p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  xyxy[3].cpu().item())
                            p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                                  xyxy[3].cpu().item())
                            pt = [p1, p2]
                            personinflag = mat.Path(person).contains_points(pt)
                            if personinflag.any():
                                annotator.box_label(xyxy, None, color=(0, 0, 255))
                                self.flag = True
        return self.flag

class CarHelmetBelt:
    def __init__(self):
        self.flag = False

    def selectNoBeltPerson(self, person_objs, belt_objs):
        objs = []
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_belt = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in belt_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            with_belt = False
            for belt in polygon_belt:
                if person.intersection(belt).area / belt.area > 0.5:
                    with_belt = True
                    break
            if not with_belt:
                objs.append(person_obj)
        return objs

    def selectWithPersonHead(self, person_objs, head_objs):
        objs = []
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, top + (bottom - top)/2), (left, top + (bottom - top)/2)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_head = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in head_objs]
        for head_obj, head in zip(head_objs, polygon_head):
            with_person = False
            for person in polygon_person:
                print('head')
                if person.intersection(head).area / head.area > 0.5:
                    with_person = True
                    break
            if with_person:
                objs.append(head_obj)
        return objs

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        person_objs = []
        head_objs = []
        belt_objs = []
        self.polygon_areas = [Polygon(strtolstl(point)[0])]
        for result in results:
            boxes = result.boxes
            for box in boxes:
                #print(box.conf.cpu())
                left, top, right, bottom = box.xyxy.cpu().numpy().tolist()[0]
                polygon_box = Polygon([(left, top), (right, top), (right, bottom), (left, bottom)])

                intersection_areas = [polygon_area.intersection(polygon_box).area for polygon_area in self.polygon_areas ]
                if sum(intersection_areas) == 0:
                    continue

                intersection_areas_ratio = sorted([intersection_area / polygon_box.area for intersection_area in intersection_areas])
                if intersection_areas_ratio[-1] < 0.9:
                    continue

                conf = box.conf.cpu().numpy().tolist()[0]
                cls = box.cls.cpu().numpy().tolist()[0]
                if cls == 0:
                    person_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls == 1:
                    head_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls == 3:
                    belt_objs.append([left, top, right, bottom, conf, names[cls]])
                #print(head_objs)
                #print(person_objs)
        illegal_objs = self.selectNoBeltPerson(person_objs, belt_objs) + self.selectWithPersonHead(person_objs, head_objs)
        if len(illegal_objs)>0:
            for obj in illegal_objs:
                annotator.box_label(obj[:4], None, color=(0, 0, 255))
            self.flag = True
        return self.flag

class newUniform:
    def __init__(self):
        self.flag = False

    def selectNoUniformPerson(self, person_objs, uniform_objs):
        objs = []
        print(person_objs)
        print(uniform_objs)
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_uniform = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in uniform_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            with_uniform = False
            for uniform in polygon_uniform:
                if person.intersection(uniform).area / uniform.area > 0.3:
                    with_uniform = True
                    break
            if not with_uniform:
                print(f'illperson_obj {person_obj} illpolygon_uniform {polygon_uniform}')
                objs.append(person_obj)
        return objs


    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        print(results.boxes)
        person_objs = []
        uniform_objs = []
        #belt_objs = []
        if len(point)>1:
            self.polygon_areas = [Polygon(strtolstl(point)[0])]
        else:
            self.polygon_areas = None
        for result in results:
            boxes = result.boxes
            for box in boxes:
                left, top, right, bottom = box.xyxy.cpu().numpy().tolist()[0]
                if self.polygon_areas is not None and box.cls.cpu().numpy().tolist()[0]==4:
                    polygon_box = Polygon([(left, top), (right, top), (right, bottom), (left, bottom)])

                    intersection_areas = [polygon_area.intersection(polygon_box).area for polygon_area in self.polygon_areas ]
                    if sum(intersection_areas) == 0:
                        continue

                    intersection_areas_ratio = sorted([intersection_area / polygon_box.area for intersection_area in intersection_areas])
                    print(f'inter = {intersection_areas_ratio}')
                    if intersection_areas_ratio[-1] < 0.9:
                        continue

                conf = box.conf.cpu().numpy().tolist()[0]
                cls = box.cls.cpu().numpy().tolist()[0]
                if cls == 4 and conf >=0.7:
                    width = right - left
                    height = bottom - top
                    if width * height >10000:
                        person_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls in [1,2]:
                    #width = right - left
                    #height = bottom - top
                    #if width * height >4096:
                    uniform_objs.append([left, top, right, bottom, conf, names[cls]])
                
        illegal_objs = self.selectNoUniformPerson(person_objs, uniform_objs) 
        if len(illegal_objs)>0:
            for obj in illegal_objs:
                annotator.box_label(obj[:4], None, color=(0, 0, 255))
            self.flag = True
        return self.flag

class newHelmet:
    def __init__(self):
        self.flag = False

    def selectNoHelmetPerson(self, person_objs, head_objs):
        objs = []
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_head = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in head_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            with_head = False
            for head in polygon_head:
                print('head')
                if person.intersection(head).area / head.area > 0.3:
                    with_head = True
                    break
            if  with_head:
                objs.append(person_obj)
        return objs


    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        person_objs = []
        head_objs = []
        helmet_objs = []
        headtmp = []
        #belt_objs = []
        if len(point)>1:
            self.polygon_areas = [Polygon(strtolstl(point)[0])]
        else:
            self.polygon_areas = None
        for result in results:
            boxes = result.boxes
            for box in boxes:
                left, top, right, bottom = box.xyxy.cpu().numpy().tolist()[0]
                if self.polygon_areas is not None and box.cls.cpu().numpy().tolist()[0]==4:
                    polygon_box = Polygon([(left, top), (right, top), (right, bottom), (left, bottom)])

                    intersection_areas = [polygon_area.intersection(polygon_box).area for polygon_area in self.polygon_areas ]
                    if sum(intersection_areas) == 0:
                        continue

                    intersection_areas_ratio = sorted([intersection_area / polygon_box.area for intersection_area in intersection_areas])
                    if intersection_areas_ratio[-1] < 0.3:
                        continue
                conf = box.conf.cpu().numpy().tolist()[0]
                cls = box.cls.cpu().numpy().tolist()[0]
                if cls == 4 and conf >=0.7:
                    width = right - left
                    height = bottom - top
                    if width * height >4096:
                        person_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls == 0:
                    #width = right - left
                    #height = bottom - top
                    #if width * height >4096:
                    print('------')
                    headtmp.append([left, top, right, bottom, conf, names[cls]])
                elif cls in [5,6,7,8,9,10]:
                    helmet_objs.append([(left, top), (right, top), (right, bottom), (left, bottom)])
        print(headtmp)
        print(helmet_objs)
        for left, top, right, bottom, conf, name  in headtmp:
            flag = False
            pt = [(int((left+right)/2),int((top+bottom)/2))]
            for helmet in helmet_objs:
                pflag = mat.Path(helmet).contains_points(pt)
                if pflag.any():
                    flag = True
                    break
            if not flag:
                head_objs.append([left, top, right, bottom, conf, name])
        illegal_objs = self.selectNoHelmetPerson(person_objs, head_objs) 
        if len(illegal_objs)>0:
            for obj in illegal_objs:
                annotator.box_label(obj[:4], None, color=(0, 0, 255))
            self.flag = True
        return self.flag
        
class newHelmetn:
    def __init__(self):
        self.flag = False

    def selectNoHelmetPerson(self, person_objs, head_objs):
        objs = []
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_head = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in head_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            with_head = False
            for head in polygon_head:
                if person.intersection(head).area / head.area > 0.3:
                    with_head = True
                    break
            if  with_head:
                objs.append(person_obj)
        return objs


    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        person_objs = []
        head_objs = []
        #belt_objs = []
        if len(point)>1:
            self.polygon_areas = [Polygon(strtolstl(point)[0])]
        else:
            self.polygon_areas = None
        for result in results:
            boxes = result.boxes
            for box in boxes:
                left, top, right, bottom = box.xyxy.cpu().numpy().tolist()[0]
                if self.polygon_areas is not None:
                    polygon_box = Polygon([(left, top), (right, top), (right, bottom), (left, bottom)])

                    intersection_areas = [polygon_area.intersection(polygon_box).area for polygon_area in self.polygon_areas ]
                    if sum(intersection_areas) == 0:
                        continue

                    intersection_areas_ratio = sorted([intersection_area / polygon_box.area for intersection_area in intersection_areas])
                    if intersection_areas_ratio[-1] < 0.9:
                        continue
                conf = box.conf.cpu().numpy().tolist()[0]
                cls = box.cls.cpu().numpy().tolist()[0]
                if cls == 4:
                    width = right - left
                    height = bottom - top
                    if width * height >4096:
                        person_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls == 0:
                    #width = right - left
                    #height = bottom - top
                    #if width * height >4096:
                    head_objs.append([left, top, right, bottom, conf, names[cls]])
                
        illegal_objs = self.selectNoHelmetPerson(person_objs, head_objs) 
        if len(illegal_objs)>0:
            for obj in illegal_objs:
                annotator.box_label(obj[:4], None, color=(0, 0, 255))
            self.flag = True
        return self.flag
        
class newUniformt:
    def __init__(self):
        self.flag = False

    def selectNoUniformPerson(self, person_objs, uniform_objs):
        objs = []
        print(person_objs)
        print(uniform_objs)
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_uniform = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in uniform_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            with_uniform = False
            for uniform in polygon_uniform:
                if person.intersection(uniform).area / uniform.area > 0.3:
                    with_uniform = True
                    break
            if not with_uniform:
                print(f'illperson_obj {person_obj} illpolygon_uniform {polygon_uniform}')
                objs.append(person_obj)
        return objs

    def selectHeadPerson(self, person_objs, head_objs):
        objs = []
        print(person_objs)
        print(head_objs)
        #personlist = []
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_head = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in uniform_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            #with_uniform = False
            for head in polygon_head:
                if person.intersection(head).area / head.area > 0.3:
                    #with_uniform = True
                    #break
            #if not with_uniform:
            #    print(f'illperson_obj {person_obj} illpolygon_uniform {polygon_uniform}')
                    objs.append(person_obj)
                    break
        return objs

    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        print(results.boxes)
        person_objs = []
        uniform_objs = []
        head_objs = []
        #belt_objs = []
        if len(point)>1:
            self.polygon_areas = [Polygon(strtolstl(point)[0])]
        else:
            self.polygon_areas = None
        for result in results:
            boxes = result.boxes
            for box in boxes:
                left, top, right, bottom = box.xyxy.cpu().numpy().tolist()[0]
                if self.polygon_areas is not None:
                    polygon_box = Polygon([(left, top), (right, top), (right, bottom), (left, bottom)])

                    intersection_areas = [polygon_area.intersection(polygon_box).area for polygon_area in self.polygon_areas ]
                    if sum(intersection_areas) == 0:
                        continue

                    intersection_areas_ratio = sorted([intersection_area / polygon_box.area for intersection_area in intersection_areas])
                    if intersection_areas_ratio[-1] < 0.9:
                        continue

                conf = box.conf.cpu().numpy().tolist()[0]
                cls = box.cls.cpu().numpy().tolist()[0]
                if cls == 4:
                    width = right - left
                    height = bottom - top
                    if width * height >4096:
                        person_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls in [1,2]:
                    #width = right - left
                    #height = bottom - top
                    #if width * height >4096:
                    uniform_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls != 3:
                    head_objs.append([left, top, right, bottom, conf, names[cls]])
                
        person_objs = self.selectNoUniformPerson(person_objs, head_objs)
        illegal_objs = self.selectNoUniformPerson(person_objs, uniform_objs) 
        if len(illegal_objs)>0:
            for obj in illegal_objs:
                annotator.box_label(obj[:4], None, color=(0, 0, 255))
            self.flag = True
        return self.flag
        
class newUniformi1:
    def __init__(self):
        self.flag = False

    def selectNoUniformPerson(self, person_objs, uniform_objs):
        objs = []
        print(person_objs)
        print(uniform_objs)
        polygon_person = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in person_objs]
        polygon_uniform = [Polygon(
            [(left, top), (right, top), (right, bottom), (left, bottom)]) for left, top, right, bottom, _, _ in uniform_objs]
        for person_obj, person in zip(person_objs, polygon_person):
            with_uniform = False
            for uniform in polygon_uniform:
                if person.intersection(uniform).area / uniform.area > 0.3:
                    with_uniform = True
                    break
            if not with_uniform:
                print(f'illperson_obj {person_obj} illpolygon_uniform {polygon_uniform}')
                objs.append(person_obj)
        return objs


    def getflag(self, det, persondet,annotator, fence=0, point=None, names=None, rname=None,num=1):
        self.flag = False
        results = Results(annotator.result(),path=None,names=names,boxes=det)
        print(results.boxes)
        person_objs = []
        uniform_objs = []
        print(f'persondet = {persondet}')
        #belt_objs = []
        if len(point)>1:
            self.polygon_areas = [Polygon(strtolstl(point)[0])]
        else:
            self.polygon_areas = None
        for result in results:
            boxes = result.boxes
            for box in boxes:
                left, top, right, bottom = box.xyxy.cpu().numpy().tolist()[0]
                if self.polygon_areas is not None:
                    polygon_box = Polygon([(left, top), (right, top), (right, bottom), (left, bottom)])

                    intersection_areas = [polygon_area.intersection(polygon_box).area for polygon_area in self.polygon_areas ]
                    if sum(intersection_areas) == 0:
                        continue

                    intersection_areas_ratio = sorted([intersection_area / polygon_box.area for intersection_area in intersection_areas])
                    if intersection_areas_ratio[-1] < 0.9:
                        continue

                conf = box.conf.cpu().numpy().tolist()[0]
                cls = box.cls.cpu().numpy().tolist()[0]
                print(conf)
                print(cls)
                if cls == 4 and conf >=0.7:
                    width = right - left
                    height = bottom - top
                    print(width*height)
                    if width * height >10000:
                        for person in persondet:
                            #p1 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3),
                                  #xyxy[3].cpu().item())
                            #p2 = (int(xyxy[0].cpu().item() + (xyxy[2].cpu().item() - xyxy[0].cpu().item()) / 3 * 2),
                            #      xyxy[3].cpu().item())
                            personcenterx = int((person[0][0]+person[1][0])/2)
                            personcentery = int((person[0][1]+person[2][1])/2)
                            p1 = (personcenterx,personcentery)
                            print(p1)
                            pt = [p1]
                            print(f'p1 = {p1}')
                            print(f'person = {person}')
                            personinflag = mat.Path([(left, top), (right, top), (right, bottom), (left, bottom)]).contains_points(pt)
                            if personinflag.any():
                                person_objs.append([left, top, right, bottom, conf, names[cls]])
                elif cls in [1,2]:
                    #width = right - left
                    #height = bottom - top
                    #if width * height >4096:
                    uniform_objs.append([left, top, right, bottom, conf, names[cls]])
                
        illegal_objs = self.selectNoUniformPerson(person_objs, uniform_objs) 
        if len(illegal_objs)>0:
            for obj in illegal_objs:
                annotator.box_label(obj[:4], None, color=(0, 0, 255))
            self.flag = True
        return self.flag