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1)新增M027:建筑物下行人检测及计数 2)密集人群计数模型及自研车牌模型优化 3)分类模型支持pt模型加载（巴中水利）

This commit is contained in:
th 2025-07-25 18:25:50 +08:00
parent d369031085 dadb4007ca
commit 98480b45d6
7 changed files with 227 additions and 0 deletions
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85
concurrency/FileUploadThread.py
View File

@ -27,6 +27,7 @@ class FileUpload(Thread):
super().__init__()
self._fb_queue, self._context, self._msg, self._image_queue, self._analyse_type, self._mqtt_list = args
self._storage_source = self._context['service']['storage_source']
<<<<<<< HEAD
self._algStatus = False # 默认关闭
# self._algStatus = True # 默认关闭
@ -34,6 +35,17 @@ class FileUpload(Thread):
# 0521:
default_enabled = str(self._msg.get("defaultEnabled", "True")).lower() == "true"
=======
self._algStatus = False # 默认关闭
# self._algStatus = True # 默认关闭
self._algSwitch = self._context['service']['algSwitch']
#0521:
default_enabled = str(self._msg.get("defaultEnabled", "True")).lower() == "true"
>>>>>>> origin/zsl
if default_enabled:
print("执行默认程序（defaultEnabled=True）")
self._algSwitch = True
@ -43,10 +55,17 @@ class FileUpload(Thread):
# 这里放非默认逻辑的代码
self._algSwitch = False
<<<<<<< HEAD
print("---line46 :FileUploadThread.py---", self._algSwitch)
# 如果任务是在线、离线处理，则用此类
=======
print("---line46 :FileUploadThread.py---",self._algSwitch)
#如果任务是在线、离线处理，则用此类
>>>>>>> origin/zsl
class ImageFileUpload(FileUpload):
__slots__ = ()
@ -66,6 +85,10 @@ class ImageFileUpload(FileUpload):
'''
print('*' * 100, ' mqtt_list:', len(self._mqtt_list))
<<<<<<< HEAD
=======
>>>>>>> origin/zsl
model_info = []
# 更加模型编码解析数据
for code, det_list in det_xywh.items():
@ -76,10 +99,19 @@ class ImageFileUpload(FileUpload):
for target in target_list:
# 自研车牌模型判断
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
<<<<<<< HEAD
draw_name_ocr(target[1], aFrame, target[4])
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
draw_name_crowd(target[1], aFrame, target[4])
=======
box = [target[1][0][0], target[1][0][1], target[1][3][0], target[1][3][1]]
draw_name_ocr(box, aFrame, target[4], target[0])
cls = 0
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
draw_name_crowd(target[3], aFrame, target[4], cls)
cls = 0
>>>>>>> origin/zsl
else:
draw_painting_joint(target[1], aFrame, target[3], target[2], target[4], font_config,
target[5])
@ -139,10 +171,15 @@ class ImageFileUpload(FileUpload):
if 'stop' == image_msg[1]:
logger.info("开始停止图片上传线程, requestId:{}", request_id)
break
<<<<<<< HEAD
if 'algStart' == image_msg[1]: self._algStatus = True; logger.info(
"图片上传线程,执行算法开启命令, requestId:{}", request_id)
if 'algStop' == image_msg[1]: self._algStatus = False; logger.info(
"图片上传线程,执行算法关闭命令, requestId:{}", request_id)
=======
if 'algStart' == image_msg[1]: self._algStatus = True; logger.info("图片上传线程,执行算法开启命令, requestId:{}", request_id)
if 'algStop' == image_msg[1]: self._algStatus = False; logger.info("图片上传线程,执行算法关闭命令, requestId:{}", request_id)
>>>>>>> origin/zsl
if image_msg[0] == 1:
image_result = self.handle_image(image_msg[1], frame_step)
@ -153,8 +190,13 @@ class ImageFileUpload(FileUpload):
image_result["last_frame"],
analyse_type,
"OR", "0", "0", request_id)
<<<<<<< HEAD
if self._storage_source == 1:
or_future = t.submit(minioSdk.put_object, or_image, or_image_name)
=======
if self._storage_source==1:
or_future = t.submit(minioSdk.put_object, or_image,or_image_name)
>>>>>>> origin/zsl
else:
or_future = t.submit(aliyunOssSdk.put_object, or_image_name, or_image.tobytes())
task.append(or_future)
@ -169,12 +211,20 @@ class ImageFileUpload(FileUpload):
model_info["modelCode"],
model_info["detectTargetCode"],
request_id)
<<<<<<< HEAD
if self._storage_source == 1:
=======
if self._storage_source==1:
>>>>>>> origin/zsl
ai_future = t.submit(minioSdk.put_object, ai_image,
ai_image_name)
else:
ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name,
<<<<<<< HEAD
ai_image.tobytes())
=======
ai_image.tobytes())
>>>>>>> origin/zsl
task.append(ai_future)
# msg_list.append(message_feedback(request_id,
@ -198,9 +248,15 @@ class ImageFileUpload(FileUpload):
model_info['detectTargetCode'],
longitude=model_info['gps'][0],
latitude=model_info['gps'][1],
<<<<<<< HEAD
))
if (not self._algSwitch) or (self._algStatus and self._algSwitch):
=======
) )
if (not self._algSwitch) or ( self._algStatus and self._algSwitch):
>>>>>>> origin/zsl
for msg in msg_list:
put_queue(fb_queue, msg, timeout=2, is_ex=False)
del task, msg_list
@ -225,6 +281,10 @@ def build_image_name(*args):
time_now = TimeUtils.now_date_to_str("%Y-%m-%d-%H-%M-%S")
return "%s/%s_frame-%s-%s_type_%s-%s-%s-%s_%s.jpg" % (request_id, time_now, current_frame, last_frame,
random_num, mode_type, modeCode, target, image_type)
<<<<<<< HEAD
=======
>>>>>>> origin/zsl
# 如果任务是图像处理，则用此类
@ -257,10 +317,16 @@ class ImageTypeImageFileUpload(Thread):
for target in target_list:
# 自研车牌模型判断
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
<<<<<<< HEAD
draw_name_ocr(target, aiFrame, font_config[cls])
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or \
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
draw_name_crowd(target, aiFrame, font_config[cls])
=======
draw_name_ocr(target[1], aiFrame, font_config[cls], target[0])
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
draw_name_crowd(target[1],aiFrame,font_config[cls],target[0])
>>>>>>> origin/zsl
else:
draw_painting_joint(target[1], aiFrame, target[3], target[2], target[4], font_config)
@ -315,8 +381,13 @@ class ImageTypeImageFileUpload(Thread):
ai_image_name = build_image_name(0, 0, analyse_type, "AI", result.get("modelCode"),
result.get("type"), request_id)
<<<<<<< HEAD
if self._storage_source == 1:
ai_future = t.submit(minioSdk.put_object, copy_frame, ai_image_name)
=======
if self._storage_source==1:
ai_future = t.submit(minioSdk.put_object, copy_frame,ai_image_name)
>>>>>>> origin/zsl
else:
ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name, copy_frame)
@ -338,12 +409,21 @@ class ImageTypeImageFileUpload(Thread):
if image_url is None:
or_result, or_image = cv2.imencode(".jpg", image_result.get("or_frame"))
image_url_0 = build_image_name(image_result.get("current_frame"),
<<<<<<< HEAD
image_result.get("last_frame"),
analyse_type,
"OR", "0", "O", request_id)
if self._storage_source == 1:
or_future = t.submit(minioSdk.put_object, or_image, image_url_0)
=======
image_result.get("last_frame"),
analyse_type,
"OR", "0", "O", request_id)
if self._storage_source==1:
or_future = t.submit(minioSdk.put_object, or_image,image_url_0)
>>>>>>> origin/zsl
else:
or_future = t.submit(aliyunOssSdk.put_object, image_url_0,
or_image.tobytes())
@ -359,8 +439,13 @@ class ImageTypeImageFileUpload(Thread):
model_info.get("modelCode"),
model_info.get("detectTargetCode"),
request_id)
<<<<<<< HEAD
if self._storage_source == 1:
ai_future = t.submit(minioSdk.put_object, ai_image, ai_image_name)
=======
if self._storage_source==1:
ai_future = t.submit(minioSdk.put_object, ai_image, ai_image_name)
>>>>>>> origin/zsl
else:
ai_future = t.submit(aliyunOssSdk.put_object, ai_image_name,
ai_image.tobytes())

30
concurrency/IntelligentRecognitionProcess.py
View File

@ -91,6 +91,10 @@ class IntelligentRecognitionProcess(Process):
hb_thread.start()
return hb_thread
<<<<<<< HEAD
=======
>>>>>>> origin/zsl
class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
@ -296,8 +300,12 @@ class OnlineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
for i, model in enumerate(model_array):
model_conf, code = model
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
<<<<<<< HEAD
ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
=======
ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
>>>>>>> origin/zsl
if draw_config.get(code) is None:
draw_config[code] = {}
draw_config["font_config"] = model_conf[4]
@ -623,8 +631,12 @@ class OfflineIntelligentRecognitionProcess(IntelligentRecognitionProcess):
for i, model in enumerate(model_array):
model_conf, code = model
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
<<<<<<< HEAD
ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
=======
ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
>>>>>>> origin/zsl
if draw_config.get(code) is None:
draw_config[code] = {}
draw_config["font_config"] = model_conf[4]
@ -941,7 +953,11 @@ class PhotosIntelligentRecognitionProcess(Process):
logger.error("模型分析异常: {}, requestId: {}", format_exc(), request_id)
raise e
<<<<<<< HEAD
#自研车牌模型
=======
#自研究车牌模型
>>>>>>> origin/zsl
def carplate_rec(self, imageUrl, mod, image_queue, request_id):
try:
# model_conf： modeType, allowedList, detpar, ocrmodel, rainbows
@ -980,6 +996,10 @@ class PhotosIntelligentRecognitionProcess(Process):
# param = [image, new_device, model, par, img_type, request_id]
# model_conf, frame, device, requestId
dataBack = MODEL_CONFIG[code][3]([[modeType, device, model, postPar], image, request_id])[0][2]
<<<<<<< HEAD
=======
logger.info("当前人数：{}", dataBack[0][0])
>>>>>>> origin/zsl
dets[code][0] = dataBack
if not dataBack:
logger.info("当前页面无人")
@ -1268,8 +1288,12 @@ class PhotosIntelligentRecognitionProcess(Process):
result = t.submit(self.carpalteRec, imageUrls, model, image_queue, request_id)
task_list.append(result)
# 人群计数模型
<<<<<<< HEAD
elif model[1] == ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] or \
model[1] == ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1]:
=======
elif model[1] == ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1]:
>>>>>>> origin/zsl
result = t.submit(self.denscrowdcountRec, imageUrls, model, image_queue, request_id)
task_list.append(result)
else:
@ -1484,9 +1508,15 @@ class ScreenRecordingProcess(Process):
clear_queue(self._hb_queue)
clear_queue(self._pull_queue)
<<<<<<< HEAD
def upload_video(self, base_dir, env, request_id, orFilePath):
if self._storage_source == 1:
minioSdk = MinioSdk(base_dir, env, request_id)
=======
def upload_video(self,base_dir, env, request_id, orFilePath):
if self._storage_source==1:
minioSdk = MinioSdk(base_dir, env, request_id )
>>>>>>> origin/zsl
upload_video_thread_ai = Common(minioSdk.put_object, aiFilePath, "%s/ai_online.mp4" % request_id)
else:
aliyunVodSdk = ThAliyunVodSdk(base_dir, env, request_id)

65
concurrency/PushVideoStreamProcess.py
View File

@ -151,6 +151,7 @@ class OnPushStreamProcess(PushStreamProcess):
# 自研车牌模型处理
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
cls = 0
<<<<<<< HEAD
box = xy2xyxy(qs[1])
score = None
color = rainbows[cls]
@ -159,10 +160,22 @@ class OnPushStreamProcess(PushStreamProcess):
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
cls = 0
=======
ocrlabel, xybox = qs
box = xy2xyxy(xybox)
score = None
color = rainbows[cls]
label_array = None
rr = t.submit(draw_name_ocr, xybox, copy_frame, color, ocrlabel)
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
cls = 0
crowdlabel, points = qs
>>>>>>> origin/zsl
box = [(0, 0), (0, 0), (0, 0), (0, 0)]
score = None
color = rainbows[cls]
label_array = None
<<<<<<< HEAD
rr = t.submit(draw_name_crowd, qs, copy_frame, color)
else:
try: # 应对NaN情况
@ -179,6 +192,24 @@ class OnPushStreamProcess(PushStreamProcess):
else:
rr = t.submit(draw_painting_joint, box, copy_frame, label_array,
score, color, font_config)
=======
rr = t.submit(draw_name_crowd, points, copy_frame, color, crowdlabel)
else:
try: # 应对NaN情况
box, score, cls = xywh2xyxy2(qs)
except:
continue
if cls not in allowedList or score < frame_score:
continue
label_array, color = label_arrays[cls], rainbows[cls]
if ModelType.CHANNEL2_MODEL.value[1] == str(code) and cls == 2:
rr = t.submit(draw_name_joint, box, copy_frame,
draw_config[code]["label_dict"], score, color,
font_config, qs[6])
else:
rr = t.submit(draw_painting_joint, box, copy_frame, label_array,
score, color, font_config)
>>>>>>> origin/zsl
thread_p.append(rr)
if det_xywh.get(code) is None:
@ -260,10 +291,18 @@ class OnPushStreamProcess(PushStreamProcess):
is_new = False
if q[11] == 1:
is_new = True
<<<<<<< HEAD
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
box = qs
=======
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
cls = ocrlabel
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
cls = crowdlabel
label_array = points
>>>>>>> origin/zsl
if cd is None:
det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]]
else:
@ -391,21 +430,38 @@ class OffPushStreamProcess(PushStreamProcess):
# 自研车牌模型处理
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
cls = 0
<<<<<<< HEAD
box = xy2xyxy(qs[1])
=======
ocrlabel, xybox = qs
box = xy2xyxy(xybox)
>>>>>>> origin/zsl
score = None
color = rainbows[cls]
label_array = None
label_arrays = [None]
<<<<<<< HEAD
rr = t.submit(draw_name_ocr, qs, copy_frame, color)
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
cls = 0
=======
rr = t.submit(draw_name_ocr,xybox,copy_frame,color,ocrlabel)
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
cls = 0
crowdlabel, points = qs
>>>>>>> origin/zsl
box = [(0,0),(0,0),(0,0),(0,0)]
score = None
color = rainbows[cls]
label_array = None
<<<<<<< HEAD
rr = t.submit(draw_name_crowd, qs, copy_frame, color)
=======
rr = t.submit(draw_name_crowd, points, copy_frame, color, crowdlabel)
>>>>>>> origin/zsl
else:
box, score, cls = xywh2xyxy2(qs)
@ -497,10 +553,19 @@ class OffPushStreamProcess(PushStreamProcess):
if q[11] == 1:
is_new = True
<<<<<<< HEAD
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code) or \
ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code) or\
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1] == str(code):
box = qs
=======
if ModelType.CITY_CARPLATE_MODEL.value[1] == str(code):
cls = ocrlabel
elif ModelType.CITY_DENSECROWDCOUNT_MODEL.value[1] == str(code):
cls = crowdlabel
label_array = points
>>>>>>> origin/zsl
if cd is None:
det_xywh2[code][cls] = [[cls, box, score, label_array, color, is_new]]
else:

12
enums/ModelTypeEnum.py
View File

@ -374,8 +374,13 @@ class ModelType(Enum):
},
'models':[
{
<<<<<<< HEAD
'weight':'../weights/trt/AIlib2/cityMangement3/yolov5_%s_fp16.engine'%(gpuName),
'name':'yolov5',
=======
'weight':'../weights/trt/AIlib2/cityMangement3/yolov5_%s_fp16.engine'%(gpuName),
'name':'yolov5',
>>>>>>> origin/zsl
'model':yolov5Model,
'par':{ 'half':True,'device':'cuda:0' ,'conf_thres':0.25,'iou_thres':0.45,'allowedList':[0,1,2,3,4,5,6,7],'segRegionCnt':1, 'trtFlag_det':True,'trtFlag_seg':True, "score_byClass":{"0":0.8,"1":0.4,"2":0.5,"3":0.5 } }
},
@ -974,7 +979,11 @@ class ModelType(Enum):
'row': 2,
'line': 2,
'point_loss_coef': 0.45,
<<<<<<< HEAD
'conf': 0.50,
=======
'conf': 0.25,
>>>>>>> origin/zsl
'gpu_id': 0,
'eos_coef': '0.5',
'set_cost_class': 1,
@ -1002,6 +1011,7 @@ class ModelType(Enum):
"rainbows": COLOR
},
<<<<<<< HEAD
})
CITY_UNDERBUILDCOUNT_MODEL = ("30", "306", "建筑物下人群计数", 'perUnderBuild', lambda device, gpuName: {
@ -1036,6 +1046,8 @@ class ModelType(Enum):
'backbone': 'vgg16_bn'
},
}],
=======
>>>>>>> origin/zsl
})
@staticmethod

BIN
test/__pycache__/__init__.cpython-38.pyc
View File

Binary file not shown.

8
util/ModelUtils.py
View File

@ -406,8 +406,13 @@ class DENSECROWDCOUNTModel:
par = modeType.value[4](str(device), gpu_name)
rainbows = par["rainbows"]
models=[ modelPar['model'](weights=modelPar['weight'],par=modelPar['par']) for modelPar in par['models'] ]
<<<<<<< HEAD
postPar = [pp['par'] for pp in par['models']]
self.model_conf = (modeType, device, models, postPar, rainbows)
=======
postPar = par['models'][0]['par']
self.model_conf = (modeType, device, models[0], postPar, rainbows)
>>>>>>> origin/zsl
except Exception:
logger.error("模型加载异常：{}, requestId:{}", format_exc(), requestId)
raise ServiceException(ExceptionType.MODEL_LOADING_EXCEPTION.value[0],
@ -756,6 +761,7 @@ MODEL_CONFIG = {
None,
lambda x: cc_process(x)
),
<<<<<<< HEAD
# 加载建筑物下行人检测模型
ModelType.CITY_UNDERBUILDCOUNT_MODEL.value[1]: (
lambda x, y, r, t, z, h: DENSECROWDCOUNTModel(x, y, r, ModelType.CITY_UNDERBUILDCOUNT_MODEL, t, z, h),
@ -763,4 +769,6 @@ MODEL_CONFIG = {
None,
lambda x: cc_process(x)
),
=======
>>>>>>> origin/zsl
}

27
util/PlotsUtils.py
View File

@ -225,11 +225,19 @@ def draw_name_joint(box, img, label_array_dict, score=0.5, color=None, config=No
cv2.putText(img, label, p3, 0, config[3], [225, 255, 255], thickness=config[4], lineType=cv2.LINE_AA)
return img, box
<<<<<<< HEAD
def draw_name_ocr(box, img, color, line_thickness=2, outfontsize=40):
font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
# (color=None, label=None, font=None, fontSize=40, unify=False)
label_zh = get_label_array(color, box[0], font, outfontsize)
return plot_one_box_auto(box[1], img, color, line_thickness, label_zh)
=======
def draw_name_ocr(box, img, color, label, line_thickness=2, outfontsize=40):
font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
#(color=None, label=None, font=None, fontSize=40, unify=False)
label_zh = get_label_array(color, label, font, outfontsize)
return plot_one_box_auto(box, img, color, line_thickness, label_zh)
>>>>>>> origin/zsl
def filterBox(det0, det1, pix_dis):
# det0为 (m1, 11) 矩阵
@ -317,6 +325,7 @@ def plot_one_box_auto(box, img, color=None, line_thickness=2, label_array=None):
return img, box
<<<<<<< HEAD
def draw_name_crowd(dets, img, color, line_thickness=2, outfontsize=20):
font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
if len(dets) == 1:
@ -363,5 +372,23 @@ def draw_name_crowd(dets, img, color, line_thickness=2, outfontsize=20):
cv2.polylines(img, [np.asarray(xy2xyxy(b), np.int32)], True, (0, 128, 255), 2)
img[y0:y1, x0:x1, :] = label_arr
=======
def draw_name_crowd(dets, img, color, label, line_thickness=2, outfontsize=20):
font = ImageFont.truetype(FONT_PATH, outfontsize, encoding='utf-8')
H,W = img.shape[:2]
# img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# img = Image.fromarray(img)
# width, height = img.size
Wrate = W // 128 * 128/W
Hrate = H // 128 * 128/H
# img = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
for p in dets:
img = cv2.circle(img, (int(p[0]/Wrate), int(p[1]/Hrate)), line_thickness, color, -1)
Calc_label_arr = get_label_array(color, label, font, outfontsize)
lh, lw = Calc_label_arr.shape[0:2]
img[0:lh, 0:lw, :] = Calc_label_arr
>>>>>>> origin/zsl
return img, dets