从前景提取(grabcut)中检测目标的运动

Question

我是opencv python新手

现在，我正在做运动检测(在网络摄像头)的对象，我从前景提取(使用grabcut)。我已经从grabcut中获得了一个对象，但我不知道如何编写代码来检测该对象的运动并在摄像头屏幕上显示该运动。

提前谢谢你

Answer 1

这是带有运动跟踪的对象检测代码，但你需要下载一些外部文件，如mobilenet model,CentroidTracker

import datetime
import imutils
import numpy as np
import csv 
# from centroidtracker import CentroidTracker
from pyimagesearch.centroidtracker import CentroidTracker
protopath = "mobilenet_ss/MobileNetSSD_deploy.prototxt"
modelpath = "mobilenet_ss/MobileNetSSD_deploy.caffemodel"

detector = cv2.dnn.readNetFromCaffe(prototxt=protopath, caffeModel=modelpath)
# detector.setPreferableBackend(cv2.dnn.DNN_BACKEND_INFERENCE_ENGINE)
detector.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)
fields=['new_id_detected',"total_person_count"]
filename = "person_records.csv"

outputlist=[]        
CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
"bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
"dog", "horse", "motorbike", "person", "pottedplant", "sheep",
"sofa", "train", "tvmonitor"]
tracker = CentroidTracker(maxDisappeared=80, maxDistance=90)

def non_max_suppression_fast(boxes, overlapThresh):
try:
if len(boxes) == 0:
return []
if boxes.dtype.kind == "i":
boxes = boxes.astype("float")
pick = []
x1 = boxes[:, 0]
y1 = boxes[:, 1]
x2 = boxes[:, 2]
y2 = boxes[:, 3]
area = (x2 - x1 + 1) * (y2 - y1 + 1)
idxs = np.argsort(y2)
while len(idxs) > 0:
last = len(idxs) - 1
i = idxs[last]
pick.append(i)
xx1 = np.maximum(x1[i], x1[idxs[:last]])
yy1 = np.maximum(y1[i], y1[idxs[:last]])
xx2 = np.minimum(x2[i], x2[idxs[:last]])
yy2 = np.minimum(y2[i], y2[idxs[:last]])
w = np.maximum(0, xx2 - xx1 + 1)
h = np.maximum(0, yy2 - yy1 + 1)
overlap = (w * h) / area[idxs[:last]]
idxs = np.delete(idxs, np.concatenate(([last],
np.where(overlap > overlapThresh)[0])))
return boxes[pick].astype("int")
except Exception as e:
print("Exception occurred in non_max_suppression : {}".format(e))

def main():
cap = cv2.VideoCapture('project_video.mp4')
fourcc = cv2.VideoWriter_fourcc('m','p','4','v')
out = cv2.VideoWriter("output/output.mp4", fourcc, 5.0, (600,337))

fps_start_time = datetime.datetime.now()
fps = 0
total_frames = 0
lpc_count = 0
opc_count = 0
object_id_list = []

# dtime = dict()
# dwell_time = dict()
while True:
ret, frame = cap.read()
if not ret:
break
frame = imutils.resize(frame, width=600)
total_frames = total_frames + 1
(H, W) = frame.shape[:2]
#print("h,w",H,W)
blob = cv2.dnn.blobFromImage(frame, 0.007843, (W, H), 127.5)
detector.setInput(blob)
person_detections = detector.forward()
rects = []
for i in np.arange(0, person_detections.shape[2]):
confidence = person_detections[0, 0, i, 2]
if confidence > 0.5:
idx = int(person_detections[0, 0, i, 1])

person_box = person_detections[0, 0, i, 3:7] * np.array([W, H, W, H])
(startX, startY, endX, endY) = person_box.astype("int")
rects.append(person_box)
boundingboxes = np.array(rects)
boundingboxes = boundingboxes.astype(int)
rects = non_max_suppression_fast(boundingboxes, 0.3)
objects = tracker.update(rects)
for (objectId, bbox) in objects.items():
x1, y1, x2, y2 = bbox
x1 = int(x1)
y1 = int(y1)
x2 = int(x2)
y2 = int(y2)
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
text = "ID: {}".format(objectId)
cv2.putText(frame, text, (x1, y1-5), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
if objectId not in object_id_list:
object_id_list.append(objectId)
# dtime[objectId] = datetime.datetime.now()
# dwell_time[objectId] = 0
# else:
#     curr_time = datetime.datetime.now()
#     old_time = dtime[objectId]
#     time_diff = curr_time - old_time
#     dtime[objectId] = datetime.datetime.now()
#     sec = time_diff.total_seconds()
#     dwell_time[objectId] += sec
# text = "{}|{}".format(objectId, int(dwell_time[objectId]))
# cv2.putText(frame, text, (x1, y1-5), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
fps_end_time = datetime.datetime.now()
time_diff = fps_end_time - fps_start_time
if time_diff.seconds == 0:
fps = 0.0
else:
fps = (total_frames / time_diff.seconds)
fps_text = "FPS: {:.2f}".format(fps)

cv2.putText(frame, fps_text, (5, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
lpc_count = len(objects)
opc_count = len(object_id_list)
lpc_txt = "LPC: {}".format(lpc_count)
opc_txt = "OPC: {}".format(opc_count)
# writing to csv file  
outputlist.append([lpc_count,opc_count])


cv2.putText(frame, lpc_txt, (5, 60), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
cv2.putText(frame, opc_txt, (5, 90), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
out.write(frame)
cv2.imshow("Application", frame)
key = cv2.waitKey(1)
if key == ord('q'):
break

cv2.destroyAllWindows()
with open(filename, 'w') as csvfile:  
# creating a csv writer object  
csvwriter = csv.writer(csvfile)   
csvwriter.writerow(fields)
csvwriter.writerows(outputlist)
main()```