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算法识别结果尝试加入矩形框

This commit is contained in:
caoqianming 2022-10-27 12:03:09 +08:00
parent 19cbd6dd2a
commit c05add8952
6 changed files with 65 additions and 28 deletions
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4
apps/ai/client.py
View File

@ -83,13 +83,13 @@ def fire1(ip: str, pic_url: str):
return True, response
def fangtang(ip: str, pic_url: str):
def fangtangfu(ip: str, pic_url: str):
# 未穿防烫服事件
channel = grpc.insecure_channel(ip+':2003')
stub = BeiHangGrpc_pb2_grpc.FA_RegStub(channel)
image_id = 4
request = BeiHangGrpc_pb2.JinYu_Request(zzid=image_id, imgUrl=pic_url)
response = stub.sendFire_Info(request)
response = stub.sendFA_Info(request)
if response.FAinfo == False:
return True, response
return False, response

70
apps/ai/main.py
View File

@ -1,6 +1,8 @@
import importlib
from operator import is_
import os
import cv2
from django.conf import settings
import logging
@ -10,27 +12,28 @@ myLogger = logging.getLogger('log')
algo_dict = {
"helmet": "apps.ai.client.helmet",
"fire1": "apps.ai.client.fire1",
"fangtang": "apps.ai.client.fangtang",
"fangtangfu": "apps.ai.client.fangtangfu",
"jingjiedai": "apps.ai.client.jingjiedai",
"qiping": "apps.ai.client.qiping"
}
def ai_analyse(codes: list, global_img: str, face_img: str = None):
def ai_analyse(codes: list, global_img: str, face_img: str = None, is_dahua_pic: bool = True):
"""算法分析图片
Args:
codes: 算法列表
global_img (str): 全景图片地址
face_img (str): 人脸图片地址
global_img (str): 全景图片url地址
face_img (str): 人脸图片url地址
"""
from apps.ecm.service import save_dahua_pic
results = {} # dict key: 触发的事件标识字符 value: 多个矩形框坐标列表
global_img_path = save_dahua_pic(global_img)
global_img = settings.BASE_URL_OUT + global_img_path
if face_img:
face_img_path = save_dahua_pic(face_img)
face_img = settings.BASE_URL_OUT + face_img_path
results = {} # dict key: 触发的事件标识字符 value: 多个矩形框坐标列表; 有两个图片key值
if is_dahua_pic: # 先保存到本地/主要是现在算法必须得用可访问的远程地址
from apps.ecm.service import save_dahua_pic
global_img_path = save_dahua_pic(global_img)
global_img = settings.BASE_URL_OUT + global_img_path # 用新地址
if face_img:
face_img_path = save_dahua_pic(face_img)
face_img = settings.BASE_URL_OUT + face_img_path
for i in codes:
if i in algo_dict and i not in results: # 如果算法支持且没有识别过
module, func = algo_dict[i].rsplit(".", 1)
@ -53,18 +56,51 @@ def ai_analyse(codes: list, global_img: str, face_img: str = None):
for x in res.FireinfoList:
if x.fire == 3 and 'qiping' in codes: # 气瓶倾倒
qiping_qd = True
rectangle_dict['qiping'].append([x.coord.x, x.coord.y]) # 加入矩形框
rectangle_dict['qiping'].append([(x.coord.uleft.x, x.coord.uleft.y), (x.coord.lright.x, x.coord.lright.y)]) # 加入矩形框
if x.fire == 0:
has_fire = True
if x.fire == 2:
has_jingjiedai = True
if (i == 'fire1' and not has_fire) or (i == 'jingjiedai' and not has_jingjiedai) or (i == 'qiping' and qiping_qd):
results.update({i: {'rectangles': rectangle_dict.get(i, [])}})
results.update({i: rectangle_dict.get(i, [])})
if is_happend and (i not in results):
results.update({i: {'rectangles': rectangle_dict.get(i, [])}})
results.update({i: rectangle_dict.get(i, [])})
except Exception:
myLogger.error('算法处理错误', exc_info=True)
os.remove(settings.BASE_DIR + global_img_path) # 删除临时图片
if face_img:
os.remove(settings.BASE_DIR + face_img_path)
if is_dahua_pic:
os.remove(settings.BASE_DIR + global_img_path) # 删除临时图片
if face_img_path:
os.remove(settings.BASE_DIR + face_img_path)
return results
def ai_analyse_2(codes: list, global_img: str, face_img: str = None, is_dahua_pic: bool = True):
"""算法分析图片后保存并返回相对地址
Args:
codes: 算法列表
global_img (str): 全景图片url地址
face_img (str): 人脸图片url地址
"""
results = ai_analyse_2(codes, global_img, face_img, is_dahua_pic)
if results: # 如果触发事件先保存下来
from apps.ecm.service import save_dahua_pic
global_img_path = save_dahua_pic(global_img)
global_img_local = settings.BASE_DIR + global_img_path
draw(global_img_local, results)
results.update({'global_img': global_img_path})
return results
def draw(path, results):
rects = []
for i in results:
rects.extend(results[i])
if not rects:
img = cv2.imread(path)
font = cv2.FONT_HERSHEY_COMPLEX_SMALL
for i in results:
for m in results[i]:
cv2.rectangle(img, results[i][m][0], results[i][m][1], (0, 255, 0), 4)
cv2.putText(img, i, results[i][m][0], font, 2, (0,0,255), 1)
cv2.imwrite(path, img)

1
apps/develop/serializers.py
View File

@ -24,6 +24,7 @@ class TestAlgoSerializer(serializers.Serializer):
codes = serializers.ListField(child=serializers.CharField(), label='需要识别的算法')
face_img = serializers.CharField()
global_img = serializers.CharField()
is_dahua_pic = serializers.BooleanField()
class SpeakerSerializer(serializers.Serializer):

7
apps/develop/views.py
View File

@ -188,10 +188,11 @@ class TestViewSet(CustomGenericViewSet):
测试算法
"""
from apps.ai.main import ai_analyse
ret = ai_analyse(codes=request.data['codes'],
from apps.ai.main import ai_analyse_2
ret = ai_analyse_2(codes=request.data['codes'],
face_img=request.data.get('face_img', None),
global_img=request.data.get('global_img', None))
global_img=request.data.get('global_img', None),
is_dahua_pic=request.data.get('is_dahua_pic', True))
return Response(ret)
@action(methods=['post'], detail=False, serializer_class=Serializer)

10
apps/ecm/service.py
View File

@ -1,7 +1,7 @@
from datetime import timedelta
from apps.vm.models import Visit
from apps.ai.main import ai_analyse
from apps.ai.main import ai_analyse, ai_analyse_2
from apps.opm.models import Operation, Opl, OplWorker
from apps.utils.sms import send_sms
import requests
@ -317,7 +317,7 @@ def dispatch_dahua_event(data: dict):
else:
algo_codes.append(i['algo__code'])
if algo_codes:
ec_codes = ai_analyse(algo_codes, global_img=global_img_o, face_img=face_img_o) # 算法处理
ec_codes = ai_analyse_2(algo_codes, global_img=global_img_o, face_img=face_img_o) # 算法处理
for m in ec_codes.keys():
for n in algo_channels:
if m == n['algo__code']:
@ -331,7 +331,7 @@ def dispatch_dahua_event(data: dict):
cates.append(EventCate.objects.filter(code='miss_lcard').first().id)
if cates:
event = Event()
event.global_img = save_dahua_pic(global_img_o)
event.global_img = ec_codes['global_img'] if ec_codes.get('global_img', None) else save_dahua_pic(global_img_o)
if face_img_o:
event.face_img = save_dahua_pic(face_img_o)
event.area = area
@ -604,7 +604,7 @@ def get_area_from_point(x: int, y: int, floorNo: str, area_fix_id):
def snap_and_analyse(vchannel: TDevice, algo_codes: list, opl: Opl = None):
global_img_o = dhClient.snap(vchannel.code)
happen_time = timezone.now()
ec_codes = ai_analyse(algo_codes, global_img=global_img_o) # 算法处理返回的事件结果
ec_codes = ai_analyse_2(algo_codes, global_img=global_img_o) # 算法处理返回的事件结果
if ec_codes:
# 获取本次所有发生事件种类
ecs = EventCate.objects.filter(code__in=ec_codes.keys())
@ -619,7 +619,7 @@ def snap_and_analyse(vchannel: TDevice, algo_codes: list, opl: Opl = None):
# ep = Employee.objects.filter(id_number=res[0]['identity']).first()
pass
event = Event()
event.global_img = save_dahua_pic(global_img_o)
event.global_img = ec_codes['global_img'] if ec_codes.get('global_img', None) else save_dahua_pic(global_img_o)
event.vchannel = vchannel
event.area = vchannel.area
event.obj_cate = obj_cate

1
apps/ecm/tasks.py
View File

@ -2,7 +2,6 @@ from __future__ import absolute_import, unicode_literals
from threading import Thread
from celery import shared_task
from apps.ai.main import ai_analyse
from apps.am.models import Area
from apps.ecm.models import EventCate, Eventdo, Event