mask_detector_main.py

def validate_param(param_name):
    """
    Validating OS environment variables
    """
    if param_name not in os.environ:
        raise ValueError("missing environment variable " + param_name)
    return os.environ[param_name]

if __name__ == "__main__":

    port = validate_param('chrys_port')
    host = validate_param('chrys_host')
    password = validate_param('chrys_password')
    cert_path = validate_param('chrys_cert')

    chrys = chrysalis.Connect(host=host, port=port, password=password, ssl_ca_cert=cert_path)

    print("[INFO] loading face detector model...")
    prototxtPath ="deploy.prototxt"
    weightsPath = "res10_300x300_ssd_iter_140000.caffemodel"
    faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
    print("[INFO] loading face mask detector model...")
    maskNet = load_model("mask_detector.model")
    
    # initialize the video stream and allow the camera sensor to warm up
    print("[INFO] starting video stream...")

    while True:
        
        img = chrys.VideoLatestImage()
        if img is not None:
            frame = img.data
            frame = imutils.resize(frame, width=400)
            # detect faces in the frame and determine if they are wearing a
            # face mask or not
            (locs, preds) = detect_and_predict_mask(frame, faceNet, maskNet)

            # loop over the detected face locations and their corresponding locations
            for (box, pred) in zip(locs, preds):
            # unpack the bounding box and predictions
                (startX, startY, endX, endY) = box
                (mask, withoutMask) = pred

                # determine the class label and color we'll use to draw
                # the bounding box and text
                label = "Mask" if mask > withoutMask else "No Mask"
                color = (0, 255, 0) if label == "Mask" else (0, 0, 255)

                # include the probability in the label
                label = "{}: {:.2f}%".format(label, max(mask, withoutMask) * 100)

                # display the label and bounding box rectangle on the output frame
                cv2.putText(frame, label, (startX, startY - 10),
                cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2)
                cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)

            # show the output frame
            cv2.imshow("mask_detector", frame)
            key = cv2.waitKey(1) & 0xFF
	
            # if the `q` key was pressed, break from the loop
            if key == ord("q"):
                break