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- import numpy as np
- import time,cv2
- def ms(t1,t0):
- return (t1-t0)*1000.0
- def center_coordinate(boundbxs):
- '''
- 输入：两个对角坐标xyxy
- 输出：矩形框重点坐标xy
- '''
- boundbxs_x1=boundbxs[0]
- boundbxs_y1=boundbxs[1]
- boundbxs_x2=boundbxs[2]
- boundbxs_y2=boundbxs[3]
- center_x=0.5*(boundbxs_x1+boundbxs_x2)
- center_y=0.5*(boundbxs_y1+boundbxs_y2)
- return center_x,center_y
-
- def fourcorner_coordinate(boundbxs):
- '''
- 输入：两个对角坐标xyxy
- 输出：矩形框四个角点坐标，以contours顺序。
- '''
- boundbxs_x1=boundbxs[0]
- boundbxs_y1=boundbxs[1]
- boundbxs_x2=boundbxs[2]
- boundbxs_y2=boundbxs[3]
- wid=boundbxs_x2-boundbxs_x1
- hei=boundbxs_y2-boundbxs_y1
- boundbxs_x3=boundbxs_x1+wid
- boundbxs_y3=boundbxs_y1
- boundbxs_x4=boundbxs_x1
- boundbxs_y4 = boundbxs_y1+hei
- contours_rec=[[boundbxs_x1,boundbxs_y1],[boundbxs_x3,boundbxs_y3],[boundbxs_x2,boundbxs_y2],[boundbxs_x4,boundbxs_y4]]
- return contours_rec
-
- def remove_simivalue(list1,list2):
- '''
- 将list1中属于list2的元素都删除。
- 输入：两个嵌套列表
- 返回：嵌套列表
- '''
- list33=list1.copy()
- for i in range(len(list1)):
- for j in range(len(list2)):
- if list2[j] == list1[i]:
- # list33.pop(list1[i])
- list33.remove(list1[i])
- return list33
-
- def remove_sameeleme_inalist(list3):
- '''
- 将list3中重复嵌套列表元素删除。
- 输入：嵌套列表
- 返回：嵌套列表
- '''
- list3=list3
- list4=[]
- list4.append(list3[0])
- for dict in list3:
- k=0
- for item in list4:
- if dict!=item:
- k=k+1
- else:
- break
- if k==len(list4):
- list4.append(dict)
- return list4
-
- def order_points(pts):
- ''' sort rectangle points by clockwise '''
- sort_x = pts[np.argsort(pts[:, 0]), :]
-
- Left = sort_x[:2, :]
- Right = sort_x[2:, :]
- # Left sort
- Left = Left[np.argsort(Left[:, 1])[::-1], :]
- # Right sort
- Right = Right[np.argsort(Right[:, 1]), :]
- return np.concatenate((Left, Right), axis=0)
-
- def mixDrowing_water_postprocess(preds,_mask_cv,pars ):
- '''还未考虑船上人过滤'''
- '''输入：落水人员的结果（类别+坐标）、原图、mask图像
- 过程：获得mask的轮廓，判断人员是否在轮廓内。
- 在，则保留且绘制；不在，舍弃。
- 返回：最终绘制的结果图、最终落水人员（坐标、类别、置信度），
- '''
-
- t0=time.time()
- '''1、最大分割水域作为判断依据'''
- img_gray = cv2.cvtColor(_mask_cv, cv2.COLOR_BGR2GRAY) if len(_mask_cv.shape)==3 else _mask_cv
- contours, thresh = cv2.threshold(img_gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
- # 寻找轮廓(多边界)
- contours, hierarchy = cv2.findContours(thresh, cv2.RETR_LIST, 2)
- contour_info = []
- for c in contours:
- contour_info.append((
- c,
- cv2.isContourConvex(c),
- cv2.contourArea(c),
- ))
- contour_info = sorted(contour_info, key=lambda c: c[2], reverse=True)
- max_contour = contour_info[0]
- #print(max_contour)
- t1=time.time()
- '''2、preds中head+person取出，boat取出。'''
- init_head_person=[]
- init_boat = []
- for i in range(len(preds)):
- #if preds[i][4]=='head' or preds[i][4]=='person':
- if preds[i][0]==0 or preds[i][0]==1:
- init_head_person.append(preds[i])
- else:
- init_boat.append(preds[i])
- t2=time.time()
- '''3、preds中head+person，通过1中水域过滤'''
- init_head_person_filterwater=init_head_person
- final_head_person_filterwater=[]
- for i in range(len(init_head_person_filterwater)):
- center_x, center_y=center_coordinate(init_head_person_filterwater[i])
- flag = cv2.pointPolygonTest(max_contour[0], (center_x, center_y), False) #若为False，会找点是否在内，外，或轮廓上(相应返回+1, -1, 0)。
- if flag==1:
- final_head_person_filterwater.append(init_head_person_filterwater[i])
- else:
- pass
- t3=time.time()
- '''4、水域过滤后的head+person，再通过船舶范围过滤'''
- init_head_person_filterboat=final_head_person_filterwater
- # final_head_person_filterboat=[]
- #获取船舶范围
- boat_contour=[]
- for i in range(len(init_boat)):
- boundbxs1=[init_boat[i][0],init_boat[i][1],init_boat[i][2],init_boat[i][3]]
- contour_temp=fourcorner_coordinate(boundbxs1) #得到boat预测框的顺序contour
- contour_temp_=np.array(contour_temp)
- contour_temp_=np.float32(contour_temp_)
- boat_contour.append(np.array(contour_temp_))
- # 遍历船舶范围，取出在船舶范围内的head和person（可能有重复元素）
- list_headperson_inboat=[]
- for i in range(len(init_head_person_filterboat)):
- for j in range(len(boat_contour)):
- center_x, center_y=center_coordinate(init_head_person_filterboat[i])
- # yyyyyyyy=boat_contour[j]
- flag = cv2.pointPolygonTest(boat_contour[j], (center_x, center_y), False) #若为False，会找点是否在内，外，或轮廓上(相应返回+1, -1, 0)。
- if flag==1:
- list_headperson_inboat.append(init_head_person_filterboat[i])
- else:
- pass
-
- if len(list_headperson_inboat)==0:
- pass
- else:
- list_headperson_inboat=remove_sameeleme_inalist(list_headperson_inboat) #将重复嵌套列表元素删除
- # 过滤船舶范围内的head和person
- final_head_person_filterboat=remove_simivalue(init_head_person_filterboat,list_headperson_inboat)
-
- t4=time.time()
- timeInfos = '%.1f (step1:%.1f step2:%.2f step3:%.3f step4:%.1f) ' %( ms(t4,t0), ms(t1,t0),ms(t2,t1),ms(t3,t2),ms(t4,t3) )
-
-
-
- return final_head_person_filterboat,timeInfos #返回最终绘制的结果图、最终落水人员（坐标、类别、置信度）
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