share一些python實現的code

#!/usr/bin/env python
#coding=utf-8
 
import cv2
 
img = cv2.imread("trace_border2.bmp")
[img_h,img_w,img_channel] = img.shape
 
trace = []
start_x = 0
start_y = 0
 
gray = img[:,:,1]
for h in range(img_h):
  for w in range(img_w):
    if (gray[h,w] > 128):
      gray[h,w] = 255
    else:
      gray[h,w] = 0
 
#python 跳出多重迴圈
#https://www.cnblogs.com/xiaojiayu/p/5195316.html
class getoutofloop(Exception): pass
try:
  for h in range(img_h - 2):
    for w in range(img_w - 2):
      if gray[h,w] == 0:
        start_x = w
        start_y = h
        raise getoutofloop
except getoutofloop:
  pass
 
print("Start Point (%d %d)"%(start_x,start_y))
trace.append([start_x,start_y])
 
# 8鄰域 順時針方向搜尋
neighbor = [[-1,-1],[0,[1,0],1],[-1,0]]
neighbor_len = len(neighbor)
 
#先從當前點的左上方開始，
# 如果左上方也是黑點(邊界點)：
#     搜尋方向逆時針旋轉90 i-=2
# 否則：
#     搜尋方向順時針旋轉45 i+=1
i = 0
cur_x = start_x + neighbor[i][0]
cur_y = start_y + neighbor[i][1]
 
is_contour_point = 0
 
try:
  while not ((cur_x == start_x) and (cur_y == start_y)):
    is_contour_point = 0
    while is_contour_point == 0:
      #neighbor_x = cur_x +
      if gray[cur_y,cur_x] == 0:
        is_contour_point = 1
        trace.append([cur_x,cur_y])
        i -= 2
        if i < 0:
          i += neighbor_len
      else:
        i += 1
        if i >= neighbor_len:
          i -= neighbor_len
      #print(i)
      cur_x = cur_x + neighbor[i][0]
      cur_y = cur_y + neighbor[i][1]
except:
  print("throw error")
 
for i in range(len(trace)-1):
  cv2.line(img,(trace[i][0],trace[i][1]),(trace[i+1][0],trace[i+1][1]),(0,255),3)
  cv2.imshow("img",img)
  cv2.waitKey(10)
 
cv2.rectangle(img,(start_x,start_y),(start_x + 20,start_y + 20),(255,0),2)
cv2.imshow("img",img)
cv2.waitKey(0)
cv2.destroyWindow("img")

搜尋過程，紅色標記線如下：

補充知識：python實現目標跟蹤（opencv）

1.單目標跟蹤

import cv2
import sys
 
(major_ver,minor_ver,subminor_ver) = (cv2.__version__).split('.')
print(major_ver,subminor_ver)
 
if __name__ == '__main__':
  # 建立跟蹤器
  tracker_type = 'MIL'
  tracker = cv2.TrackerMIL_create()
  # 讀入視訊
  video = cv2.VideoCapture("./data/1.mp4")
  # 讀入第一幀
  ok,frame = video.read()
  if not ok:
    print('Cannot read video file')
    sys.exit()
  # 定義一個bounding box
  bbox = (287,23,86,320)
  bbox = cv2.selectROI(frame,False)
  # 用第一幀初始化
  ok = tracker.init(frame,bbox)
 
  while True:
    ok,frame = video.read()
    if not ok:
      break
    # Start timer
    timer = cv2.getTickCount()
    # Update tracker
    ok,bbox = tracker.update(frame)
    # Cakculate FPS
    fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
    # Draw bonding box
    if ok:
      p1 = (int(bbox[0]),int(bbox[1]))
      p2 = (int(bbox[0] + bbox[2]),int(bbox[1] + bbox[3]))
      cv2.rectangle(frame,p1,p2,2,1)
    else:
      cv2.putText(frame,"Tracking failed detected",(100,80),cv2.FONT_HERSHEY_SIMPLEX,0.75,2)
    # 展示tracker型別
    cv2.putText(frame,tracker_type+"Tracker",20),(50,170,50),2)
    # 展示FPS
    cv2.putText(frame,"FPS:"+str(fps),2)
    # Result
    cv2.imshow("Tracking",frame)
 
    # Exit
    k = cv2.waitKey(1) & 0xff
    if k ==27 : break

2.多目標跟蹤

使用GOTURN作為跟蹤器時，須將goturn.caffemodel和goturn.prototxt放到工作目錄才能執行，解決問題連結https://stackoverflow.com/questions/48802603/getting-deep-learning-tracker-goturn-to-run-opencv-python

import cv2
import sys
 
(major_ver,subminor_ver)
 
if __name__ == '__main__':
  # 建立跟蹤器
  # 'BOOSTING','MIL','KCF','TLD','MEDIANFLOW','GOTURN','MOSSE'
  tracker_type = 'MIL'
  tracker = cv2.MultiTracker_create()
  # 建立視窗
  cv2.namedWindow("Tracking")
  # 讀入視訊
  video = cv2.VideoCapture("./data/1.mp4")
  # 讀入第一幀
  ok,frame = video.read()
  if not ok:
    print('Cannot read video file')
    sys.exit()
  # 定義一個bounding box
  box1 = cv2.selectROI("Tracking",frame)
  box2 = cv2.selectROI("Tracking",frame)
  box3 = cv2.selectROI("Tracking",frame)
  # 用第一幀初始化
  ok = tracker.add(cv2.TrackerMIL_create(),frame,box1)
  ok1 = tracker.add(cv2.TrackerMIL_create(),box2)
  ok2 = tracker.add(cv2.TrackerMIL_create(),box3)
  while True:
    ok,boxes = tracker.update(frame)
    print(ok,boxes)
    # Cakculate FPS
    fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
    for box in boxes:
      # Draw bonding box
      if ok:
        p1 = (int(box[0]),int(box[1]))
        p2 = (int(box[0] + box[2]),int(box[1] + box[3]))
        cv2.rectangle(frame,1)
      else:
        cv2.putText(frame,frame)
 
    # Exit
    k = cv2.waitKey(1) & 0xff
    if k ==27 : break

以上這篇python實現影象外邊界跟蹤操作就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支援我們。