我有这个python程序,它在OpenCV (cv2)
的帮助下打开了摄像头 session 。我已经设置了一个感兴趣的区域,在该区域中,将从摄像机记录中提取图像,并在经过训练的keras
模型中将其作为参数进行预测。我的问题是,我怎样才能每10秒检查一次模型?我尝试使用time.sleep(10)
将整个窗口冻结(因为它在while循环内发生)了10秒钟。这意味着整个记录每10秒停止一次,而我希望能够持续记录并仅每10秒检查一次模型。
到目前为止,这是我的代码:
import cv2
import numpy as np
from tensorflow import keras
import time
#import playsound
# wait for the sound to finish playing?
blocking = True
model = keras.models.load_model("model2.h5")
cam = cv2.VideoCapture(0)
####region of interest dimensions
startX = 800
startY = 0
finishX = 1200
finishY = 400
while(1):
ret, frame = cam.read()
if ret:
### displays video recording and region of interest
frame = cv2.flip(frame,1)
display = cv2.rectangle(frame.copy(),(startX,startY),(finishX,finishY),(0,0,255),2)
cv2.imshow('Total Input',display)
ROI = frame[startY:finishY, startX:finishX].copy()
cv2.imshow('Region of Interest', ROI)
#pauses for 10 seconds
time.sleep(10)
img = cv2.resize(display, (128, 128)) #R
img = img.reshape(1, 128, 128, 3)
predictions = model.predict(img) # Make predictions towards the test set
predicted_label = np.argmax(predictions) # Get index of the predicted label from prediction
print(predicted_label)
if cv2.waitKey(10) & 0xFF == ord('q'):
break
cam.release()
cv2.destroyAllWindows()
我在想是否应该使用线程,但是我对python中的线程不是很熟悉。有谁知道如何做到这一点?
最佳答案
我通常为此使用框架ID。基本上,您的模型只会在n帧后预测。这是如何使用它的代码。您可以编辑要跳过的帧数:
frame_id =0
while(1):
frame_id +=1
ret, frame = cam.read()
if ret:
### displays video recording and region of interest
frame = cv2.flip(frame,1)
display = cv2.rectangle(frame.copy(),(startX,startY),(finishX,finishY),(0,0,255),2)
cv2.imshow('Total Input',display)
ROI = frame[startY:finishY, startX:finishX].copy()
cv2.imshow('Region of Interest', ROI)
#pauses for 10 seconds
time.sleep(10)
img = cv2.resize(display, (128, 128)) #R
img = img.reshape(1, 128, 128, 3)
if fram_id % 10 == 0:
predictions = model.predict(img) # Make predictions towards the test set
predicted_label = np.argmax(predictions) # Get index of the predicted label from prediction
print(predicted_label)
if cv2.waitKey(10) & 0xFF == ord('q'):
break
关于python - 如何在仍然显示摄像机记录的同时根据训练有素的模型检查图像?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/65347405/