我想使用 Python 和 Pycharm 使用網路攝像頭制作人/汽車/卡車計數程式。
視頻源來自網路攝像頭（私人鏈接）。
當點擊'Person'按鈕（在左側）時，從那一刻起，每一個人走過紅線（綠線是起始引數），程式將其計為1人并繼續計數直到相同單擊“人員”按鈕（在左側）。“汽車”按鈕和“卡車”按鈕也是如此。汽車和卡車的總數也顯示在視窗中。
我已經有一個作業代碼來執行此操作，但是每當我運行程式（py 檔案）時，由于未知原因，它會在啟動后大約 15 秒到 30 秒后崩潰/停止。錯誤是：
Traceback (most recent call last):
File "C:/Users/admin/Desktop/Fadhli/License Plate Recognition/Mark1/mark5_1.py", line 110, in <module>
frame = frame2.copy()
AttributeError: 'NoneType' object has no attribute 'copy'
Process finished with exit code 1
我測驗了相同的代碼，但我更改了代碼以使用我自己的網路攝像頭，它作業正常并且沒有崩潰。
我懷疑這個問題是因為私人網路攝像頭有一些過濾器或導致程式卡住然后崩潰的東西。
我的問題是，我該怎么做：
A）添加緩沖區或類似的東西，這樣程式就不會掛起或
B）完全繞過該私人相機的過濾器，以便
程式不會崩潰。
我的編碼：
import cv2
import numpy as np
# Resolution Pixel Size
# 640 x 480 - Standard Definition(SD)
# 1280 x 720 - High Definition(HD)
# 1920 x 1080 - Ultra High Definiion(HD )
# 3840 x 2160 - Ultra High Definition(UHD or 2K)
cyanColor = (255, 255, 0)
pinkColor = (255, 0, 255)
yellowColor = (0, 255, 255)
greenColor = (0, 255, 0)
blueColor = (255, 0, 0)
redColor = (0,0,255)
path_vid = "Resources/video/license_plate.mp4"
path_main_ent= 'rtsp://admin:~~~Streaming/Channels/101'
path_parking_Lot = 'rtsp://admin:~~~/Streaming/Channels/101'
button_person = False
button_car = False
button_truck = False
counter = 0
nmsThreshold = 0.3
confThreshold = 0.4
def rescale_frame(image, percentage):
width = int(image.shape[1] * percentage / 100)
height = int(image.shape[0] * percentage / 100)
new_frame = (width, height)
return cv2.resize(image, new_frame, interpolation=cv2.INTER_AREA)
def click_button(event,x,y,flags,params):
global button_person
global button_car
global button_truck
if event == cv2.EVENT_LBUTTONDOWN:
print(x,y)
# ------ Person Button Clicking ---------
polygon_person = np.array([[(20, 160), (200, 160), (200, 230), (20, 230)]])
is_inside_person_button = cv2.pointPolygonTest(polygon_person,(x,y),False)
if is_inside_person_button>0:
print("You've clicked a button",x,y)
if button_person is False:
button_person = True
else:
button_person = False
print("Now Person Button is: ",button_person)
# ------ Car Button Clicking ---------
polygon_car = np.array([[(20, 250), (200, 250), (200, 320), (20, 320)]])
is_inside_car_button = cv2.pointPolygonTest(polygon_car, (x, y), False)
if is_inside_car_button > 0:
print("You've clicked a button", x, y)
if button_car is False:
button_car = True
else:
button_car = False
print("Now Car Button is: ", button_car)
# ------ Truck Button Clicking ---------
polygon_truck = np.array([[(20, 340), (200, 340), (200, 410), (20, 410)]])
is_inside_truck_button = cv2.pointPolygonTest(polygon_truck, (x, y), False)
if is_inside_truck_button > 0:
print("You've clicked a button", x, y)
if button_truck is False:
button_truck = True
else:
button_truck = False
print("Now Truck Button is: ", button_truck)
# net = cv2.dnn.readNet("dnn_model/yolov3.weights", "dnn_model/yolov3.cfg")
# net = cv2.dnn.readNet("dnn_model/yolov3-spp.weights", "dnn_model/yolov3-spp.cfg")
# net = cv2.dnn.readNet("dnn_model/yolov3-tiny.weights", "dnn_model/yolov3-tiny.cfg")
# net = cv2.dnn.readNet("dnn_model/yolov4.weights", "dnn_model/yolov4.cfg")
net = cv2.dnn.readNet("dnn_model/yolov4-tiny.weights", "dnn_model/yolov4-tiny.cfg")
model = cv2.dnn_DetectionModel(net)
model.setInputParams(size=(640,480), scale=1/255)
classes = []
with open("dnn_model/classes.txt","r") as file_object:
for class_name in file_object.readlines():
class_name = class_name.strip()
classes.append(class_name)
# print("- Object List -")
# print(classes[0])
cap = cv2.VideoCapture(path_main_ent)
# cap = cv2.VideoCapture(path_parking_Lot)
cv2.namedWindow("Frame") # The name should be same with cv2.imshow("_Name_")
cv2.setMouseCallback("Frame",click_button)
ret,frame1 = cap.read()
while cap.isOpened():
ret,frame2 = cap.read()
frame = frame2.copy()
# print(type(frame))
if not ret:
break
img_frame_90 = rescale_frame(frame, 90)
line_frame_above = cv2.line(img_frame_90, (390, 430), (1220, 470), yellowColor, 2)
line_frame = cv2.line(img_frame_90, (380, 440), (1220, 480), blueColor, 4)
line_frame_bottom = cv2.line(img_frame_90, (370, 450), (1220, 490), yellowColor, 2)
polygon_person = np.array([[(20, 160), (200, 160), (200, 230), (20, 230)]])
cv2.fillPoly(img_frame_90, polygon_person, greenColor)
cv2.putText(img_frame_90, "Person", (50, 200), cv2.FONT_HERSHEY_PLAIN, 2, blueColor, 2)
polygon_car = np.array([[(20, 250), (200, 250), (200, 320), (20, 320)]])
cv2.fillPoly(img_frame_90, polygon_car, greenColor)
cv2.putText(img_frame_90, "Car", (50, 290), cv2.FONT_HERSHEY_PLAIN, 2, blueColor, 2)
polygon_truck = np.array([[(20, 340), (200, 340), (200, 410), (20, 410)]])
cv2.fillPoly(img_frame_90, polygon_truck, greenColor)
cv2.putText(img_frame_90, "Truck", (50, 380), cv2.FONT_HERSHEY_PLAIN, 2, blueColor, 2)
(class_ids, scores, bboxes) = model.detect(img_frame_90,nmsThreshold=nmsThreshold, confThreshold=confThreshold)
if len(class_ids) != 0:
for class_id, score, bbox in zip(class_ids,scores,bboxes):
(x,y,w,h) = bbox
class_name = classes[class_id]
xmid = int((x (x w)) / 2)
ymid = int((y (y h)) / 2)
if class_name == "person" and button_person is True:
cv2.rectangle(img_frame_90, (x, y), (x w, y h), pinkColor, 2)
cv2.circle(img_frame_90, (xmid, ymid), 3, redColor, -1)
# cv2.putText(img_frame_90,str(class_name),(x,y-10),cv2.FONT_HERSHEY_SIMPLEX,1,yellowColor,2)
if ymid > 431 and ymid < 507 and xmid > 370 and xmid <490:
line_frame = cv2.line(img_frame_90, (350, 440), (1220, 480), greenColor, 4)
counter = 1
if class_name == "car" and button_car is True:
cv2.rectangle(img_frame_90, (x, y), (x w, y h), greenColor, 2)
cv2.circle(img_frame_90, (xmid, ymid), 3, redColor, -1)
# cv2.putText(img_frame_90,str(class_name),(x,y-10),cv2.FONT_HERSHEY_SIMPLEX,1,yellowColor,2)
if ymid > 431 and ymid < 507:
line_frame = cv2.line(img_frame_90, (350, 440), (1220, 480), greenColor, 4)
counter = 1
if class_name == "truck" and button_truck is True:
cv2.rectangle(img_frame_90, (x, y), (x w, y h), cyanColor, 2)
cv2.circle(img_frame_90, (xmid, ymid), 3, redColor, -1)
# cv2.putText(img_frame_90,str(class_name),(x,y-10),cv2.FONT_HERSHEY_SIMPLEX,1,yellowColor,2)
if ymid > 431 and ymid < 507:
line_frame = cv2.line(img_frame_90, (350, 440), (1220, 480), greenColor, 4)
counter = 1
cv2.putText(img_frame_90, 'Total Vehicles : {}'.format(counter), (0, 100), cv2.FONT_HERSHEY_SIMPLEX, 2, yellowColor,2)
frame1 = frame2
cv2.imshow("Frame",img_frame_90)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
@KenY-N 根據建議，我將代碼（從第 169 行）修改為
cv2.putText(img_frame_90, 'Total Vehicles : {}'.format(counter), (0, 100), cv2.FONT_HERSHEY_SIMPLEX, 2, yellowColor,2)
frame1 = frame2
if not frame2:
continue
cv2.imshow("Frame",img_frame_90)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
print(ret)
cap.release()
cv2.destroyAllWindows()
結果仍然是崩潰和錯誤：
True
''
''
''
True
Traceback (most recent call last):
File "C:/Users/admin/Desktop/Fadhli/License Plate Recognition/Mark1/mark5_1.py", line 172, in <module>
if not frame2:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
Process finished with exit code 1
uj5u.com熱心網友回復：
這是問題所在：
ret,frame2 = cap.read()
frame = frame2.copy()
# print(type(frame))
if not ret:
break
frame2此代碼在檢查捕獲是否成功之前嘗試復制。只需重新安排操作以首先進行檢查：
ret,frame2 = cap.read()
# print(type(frame))
if not ret:
break
frame = frame2.copy()
當然break會在第一次捕獲失敗時跳出回圈，所以你可能想continue改用。
uj5u.com熱心網友回復：
嘗試使用此解決方案解決緩沖區問題。這使用最新的幀。
要解決錯誤，請嘗試使用：
ret,frame2 = cap.read()
if not ret:
continue
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