diff --git a/concurrency/FileUploadThread.py b/concurrency/FileUploadThread.py index 1be5139..0a49de6 100644 --- a/concurrency/FileUploadThread.py +++ b/concurrency/FileUploadThread.py @@ -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()) diff --git a/concurrency/IntelligentRecognitionProcess.py b/concurrency/IntelligentRecognitionProcess.py index bec1d9e..6053baa 100644 --- a/concurrency/IntelligentRecognitionProcess.py +++ b/concurrency/IntelligentRecognitionProcess.py @@ -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) diff --git a/concurrency/PushVideoStreamProcess.py b/concurrency/PushVideoStreamProcess.py index 930db86..2b4ba3e 100644 --- a/concurrency/PushVideoStreamProcess.py +++ b/concurrency/PushVideoStreamProcess.py @@ -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: diff --git a/enums/ModelTypeEnum.py b/enums/ModelTypeEnum.py index 71afb62..23039ec 100644 --- a/enums/ModelTypeEnum.py +++ b/enums/ModelTypeEnum.py @@ -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 diff --git a/test/__pycache__/__init__.cpython-38.pyc b/test/__pycache__/__init__.cpython-38.pyc deleted file mode 100644 index 1335fd3..0000000 Binary files a/test/__pycache__/__init__.cpython-38.pyc and /dev/null differ diff --git a/util/ModelUtils.py b/util/ModelUtils.py index 4dd2f7e..c710ca5 100644 --- a/util/ModelUtils.py +++ b/util/ModelUtils.py @@ -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 } diff --git a/util/PlotsUtils.py b/util/PlotsUtils.py index b2a95f9..d66f494 100644 --- a/util/PlotsUtils.py +++ b/util/PlotsUtils.py @@ -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 \ No newline at end of file