import cv2 import numpy as np from numpy.core.fromnumeric import size import ec.warningunit # 设置窗体大小 img_size=(1920,1080) # class names clsnames= [ '行 人', '自行车', '小汽车', '摩托车', 'airplane', '巴 士', 'train', '卡 车', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', '狗', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush' ] # class names # names= [ 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', # 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', # 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', # 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', # 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', # 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', # 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', # 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', # 'hair drier', 'toothbrush' ] # 根据视频尺寸，填充一个polygon，供撞线计算使用 mask_image_temp = np.zeros((1080, 1920), dtype=np.uint8) # 初始化2个撞线polygon # list_pts_blue = [[204, 305], [227, 431], [605, 522], [1101, 464], [1910, 491], [1910, 400], [1125, 379], [604, 437], # [299, 375], [267, 289]] top=300 height =50 # # 测试 list_pts_blue = [[10, 300], [560, 350], [1200, 400], [1910, 350], [1918, 500], [1250, 550], [580, 500], [10, 450]] # #横琴大桥 # list_pts_blue = [ [850,850], [1240, 510], # [1370, 580], [950, 950]] #横琴新家园 # list_pts_blue = [ [100,600], [1400, 600], # [1500, 700], [200, 700]] ndarray_pts_blue = np.array(list_pts_blue, np.int32) ndarray_pts_blue =ndarray_pts_blue+np.array([0,-260])# polygon_blue_value_1 = cv2.fillPoly(mask_image_temp, [ndarray_pts_blue], color=1) polygon_blue_value_1 = polygon_blue_value_1[:, :, np.newaxis] # 填充第二个polygon mask_image_temp = np.zeros((1080, 1920), dtype=np.uint8) # list_pts_yellow =list_pts_blue +[[0,30]] ndarray_pts_yellow =ndarray_pts_blue+np.array([0,160])# np.array(list_pts_yellow, np.int32) # ndarray_pts_yellow =ndarray_pts_blue+np.array([130,80])# np.array(list_pts_yellow, np.int32) # ndarray_pts_yellow =ndarray_pts_blue+np.array([100,100])# np.array(list_pts_yellow, np.int32) polygon_yellow_value_2 = cv2.fillPoly(mask_image_temp, [ndarray_pts_yellow], color=2) polygon_yellow_value_2 = polygon_yellow_value_2[:, :, np.newaxis] # 撞线检测用mask，包含2个polygon，（值范围 0、1、2），供撞线计算使用 polygon_mask_blue_and_yellow = polygon_blue_value_1 + polygon_yellow_value_2 # 缩小尺寸，1920x1080->960x540 polygon_mask_blue_and_yellow = cv2.resize(polygon_mask_blue_and_yellow, img_size) # 蓝 色盘 b,g,r blue_color_plate = [255, 0, 0] # 蓝 polygon图片 blue_image = np.array(polygon_blue_value_1 * blue_color_plate, np.uint8) # 黄 色盘 yellow_color_plate = [0, 255, 255] # 黄 polygon图片 yellow_image = np.array(polygon_yellow_value_2 * yellow_color_plate, np.uint8) # 彩色图片（值范围 0-255） color_polygons_image = blue_image + yellow_image # 缩小尺寸，1920x1080->960x540 color_polygons_image = cv2.resize(color_polygons_image,img_size) # list 与蓝色polygon重叠 list_overlapping_blue_polygon = [] # list 与黄色polygon重叠 list_overlapping_yellow_polygon = [] countlist=[] def addcountup( cls_id): for modex in countlist: if modex["key"]==cls_id: modex["up"]+=1 return modex modex ={} modex["key"]=cls_id modex["up"]=1 modex["down"]=0 countlist.append(modex) return modex def addcountdown(cls_id): for modex in countlist: if modex["key"]==cls_id: modex["down"]+=1 return modex modex ={} modex["key"]=cls_id modex["up"]=0 modex["down"]=1 countlist.append(modex) return modex font_draw_number =cv2.FONT_HERSHEY_SIMPLEX#FONT_HERSHEY_SIMPLEX # def drawcounttext(output_image_frame): # blk = np.zeros(output_image_frame.shape, np.uint8) # cv2.rectangle(blk,(0, 0), (250, 100), (255, 255, 255), -1) # 注意在 blk的基础上进行绘制； # # output_image_frame = cv2.addWeighted(output_image_frame, 1.0, blk, 0.5, 1) # alpha = 1 # # beta 为第二张图片的透明度 # beta = 0.5 # gamma = 0 # # cv2.addWeighted 将原始图片与 mask 融合 # output_image_frame = cv2.addWeighted(output_image_frame, alpha, blk, beta, gamma) # row =0 # for modex in countlist: # draw_text_postion = (10, int(20+row*25)) # # text_draw =tracker.names[modex["key"]]+" in:"+str(modex["up"])+": out:"+str(modex["down"]) # # cv2.putText(img=output_image_frame, text=text_draw, # # org=draw_text_postion, # # fontFace=font_draw_number, # # fontScale=0.8, color=(9,10, 240), thickness=2) # row+=1 # return output_image_frame # 添加抬头半透明框 def addtitlerectangle(im0): # im0= cv2.resize(im0,(1920,1080)) blk = np.zeros(im0.shape, np.uint8) cv2.rectangle(blk,(0, 0), (400, 200), (255, 255, 255), -1) # 注意在 blk的基础上进行绘制； # output_image_frame = cv2.addWeighted(output_image_frame, 1.0, blk, 0.5, 1) alpha = 1 # beta 为第二张图片的透明度 beta = 0.5 gamma = 0 # cv2.addWeighted 将原始图片与 mask 融合 im0 = cv2.addWeighted(im0, alpha, blk, beta, gamma) return im0 # def addcolorimg(im0): # # im0= cv2.resize(im0,(1920,1080)) # im0 = cv2.add(im0, color_polygons_image) # return im0 def addcolorimg(im0): alpha = 1 # beta 为第二张图片的透明度 beta = 0.5 gamma = 0 # cv2.addWeighted 将原始图片与 mask 融合 im0 = cv2.addWeighted(im0, alpha, color_polygons_image, beta, gamma) return im0 def addcount(list_bboxs,img): if len(list_bboxs) == 0: # 如果图像中没有任何的bbox，则清空list list_overlapping_blue_polygon.clear() list_overlapping_yellow_polygon.clear() return # ----------------------判断撞线---------------------- for item_bbox in list_bboxs: x1, y1, x2, y2, track_id,cls_id= item_bbox # 撞线检测点，(x1，y1)，y方向偏移比例 0.0~1.0 y1_offset = int(y1 + ((y2 - y1) * 0.6)) # 撞线的点 y = y1_offset x = int((x1+x2)*0.5) if polygon_mask_blue_and_yellow[y, x] == 1: # 如果撞 蓝polygon if track_id not in list_overlapping_blue_polygon: list_overlapping_blue_polygon.append(track_id) print('\033[34m') print("蓝色列表=",list_overlapping_blue_polygon) print(f'进入蓝色区域cls_id ={cls_id} track_id=' +str(track_id) ) pass # 判断 黄polygon list 里是否有此 track_id # 有此 track_id，则 认为是 外出方向 if track_id in list_overlapping_yellow_polygon: # 外出+1 # up_count += 1 countmodel= addcountup(cls_id) label=clsnames[cls_id] print(f'类别: {label} | id: {track_id} | 上行撞线 | 上行撞线总数: {countmodel["up"]} | 上行id列表: {list_overlapping_yellow_polygon}') # 删除 黄polygon list 中的此id list_overlapping_yellow_polygon.remove(track_id) ec.warningunit.filter(item_bbox,list_bboxs,1,img.shape) filename=f'out/up_{cls_id}_{track_id}.jpg' cv2.imwrite(filename,img) pass else: # 无此 track_id，不做其他操作 pass elif polygon_mask_blue_and_yellow[y, x] == 2: # 如果撞 黄polygon if track_id not in list_overlapping_yellow_polygon: list_overlapping_yellow_polygon.append(track_id) print('\033[33m') print("黄色列表=",list_overlapping_yellow_polygon) print(f'进入黄色区域 cls_id ={cls_id} track_id=' +str(track_id) ) pass # 判断 蓝polygon list 里是否有此 track_id # 有此 track_id，则 认为是 进入方向 if track_id in list_overlapping_blue_polygon: # 进入+1 # down_count += 1 countmodel= addcountdown(cls_id) label=clsnames[cls_id] print(f'类别: {label} | id: {track_id} | 下行撞线 | 下行撞线总数: {countmodel["down"]} | 下行id列表: {list_overlapping_blue_polygon}') # 删除 蓝polygon list 中的此id list_overlapping_blue_polygon.remove(track_id) ec.warningunit.filter(item_bbox,list_bboxs,2,img.shape) filename=f'out/down_{cls_id}_{track_id}.jpg' cv2.imwrite(filename,img) pass else: # 无此 track_id，不做其他操作 pass pass else: pass pass pass # ----------------------清除无用id---------------------- list_overlapping_all = list_overlapping_yellow_polygon + list_overlapping_blue_polygon for id1 in list_overlapping_all: is_found = False for _, _, _, _, bbox_id,_ in list_bboxs: if bbox_id == id1: is_found = True break pass pass if not is_found: # 如果没找到，删除id if id1 in list_overlapping_yellow_polygon: list_overlapping_yellow_polygon.remove(id1) pass if id1 in list_overlapping_blue_polygon: list_overlapping_blue_polygon.remove(id1) pass print('delete id1='+str(id1)) pass list_overlapping_all.clear() pass # 清空list # list_bboxs.clear()