口罩佩戴检测 /Mask_detect

Version1.0

写在前面的 /Readig before you use this code

• 本实例利用卷积神经网络实现了图像定位，图像分类。如果你正在这找寻目标检测（yolo ssd ）的相关资源，该模型不适用于你的工作。
• Tips： this case is built by Covn net through image classification and image location .if you need some resource of object detection such as yovo or ssd ,this is not suit for you.

框架/Framework

TensorFlow 2.0

如何使用/How to use

在demo.py 文件中提供了调用笔记本摄像头实现实时检测的实例，此处作简单说明：

Code

#loading model /加载模型
 model =tf.keras.models.load_model('model.h5')  在mask_detect.ipynb 你将了解到该模型如何生成
laoding vedio or use your computer camera
cap = cv2.VideoCapture(0)    #computer camera
cap = cv2.VideoCapture('test_Trim.mp4')   #loacl file  使用本地文件
while(cap.isOpened()):
ret, frame = cap.read()
    #openccv BGR / tensorflow RGB transform
    # preprocess before input the model
frame =cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
image=tf.image.resize(frame,[360,360])
image =tf.cast(image,tf.float32)
image =image/127.5-1
print(frame.shape)
image=np.expand_dims(image,0)
# convey image into our model
[out1,out2,out3,out4,index]  = model.predict(image)  #input_shape[ None None 3] 
# out1 =>xmin
# out2 =>ymin
# out3 =>xmax
# out4 =>ymax
#index weaar mask or not
#print(out1*460,out2*460,out3*640,out4*640,index)
ptLeftTop = (int(out1*640),int(out4*480))   # xmin ymax
ptRightBottom = (int(out3*640),int(out2*480)) # xmax ymin
#print(ptLeftTop,ptRightBottom)
if index>0.5:
    point_color = (0, 0, 255) # BGR
    frame_id='Mask'
else:
    point_color = (0, 255, 0)
    frame_id='No Mask'
#draw rectangle
cv2.rectangle(frame, ptLeftTop,ptRightBottom, point_color,5)
cv2.putText(frame, '%s' %frame_id,ptLeftTop , cv2.FONT_HERSHEY_SIMPLEX, 1, (55,255,155), 2)
frame =cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
cv2.imshow('frame',frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
    break
cap.release()
#out.release()
cv2.destroyAllWindows()

PS:模型可以接受任意形状的数据输入上述对输入数据的resize是为了加快计算过程

Version2.0

基于目标检测实现的口罩佩戴检测

https://github.com/Linaom1214/mask-detection-of-object-detection