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Arg parser error :args = vars(ap.parse_args()) exception occured : python

ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
help="path to input image")
ap.add_argument("-d", "--dataset", required=True,
help="path to dataset")
ap.add_argument("-m", "--model", required=True,
help="path to Caffe pre-trained model")
ap.add_argument("-l", "--labels", required=True,
help="path to ImageNet labels (i.e., syn-sets)")
args = vars(ap.parse_args())
and I'm getting the output as
usage: train.py [-h] -i IMAGE -d DATASET -m MODEL -l LABELS
ipykernel_launcher.py: error: the following arguments are required: -i/--image, -p/--prototxt, -m/--model, -l/--labels.
An exception has occurred, use %tb to see the full traceback.
System Exit: 2

You have this error because you are running your script without passing the required parameters you defined.
You will not have the error if you run the script like this:
script_name.py -i image_path -d data_path -m model_path -l label_path

Python Error: the following arguments are required: -p/--shape-predictor

I'm new to work with python and i want to run this code , but get this error.
code:
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True, help="path to facial landmark predictor")
ap.add_argument("-v", "--video", type=str, default="", help="path to input video file")
args = vars(ap.parse_args())
enter image description here
usage:
detect_blinks.py [-h] -p SHAPE_PREDICTOR
Error I'm Getting is:
the following arguments are required: -p/--shape-predictor

As the usage says, You need pass the necessary parameter -p/--shape-predictor.
you can just run this scripts as follows:
python detect_blinks.py -p my/path/to/predictor

How to parse arguments in python (spyder)?

I am following this tutorial and trying to run the below part of the script. I am using python 3.7 and spyder 3.3.4.
ap = argparse.ArgumentParser()
ap.add_argument("-d", "--dataset", required=True,
help="path to input dataset (i.e., directory of images)")
ap.add_argument("-m", "--model", required=True,
help="path to output model")
ap.add_argument("-l", "--labelbin", required=True,
help="path to output label binarizer")
ap.add_argument("-p", "--plot", type=str, default="plot.png",
help="path to output accuracy/loss plot")
args = vars(ap.parse_args())
I have tried going to Run > Configuration per file and entering the arguments as advised by this post and and this post.
command line options: path1, path2, path3, path4
I filled out the appropriate paths for the arguments above and then ran the script, but go the error below.
usage: train.py [-h] -d DATASET -m MODEL -l LABELBIN [-p PLOT]
train.py: error: the following arguments are required: -d/--dataset,
-m/--model, -l/--labelbin An exception has occurred, use %tb to see the full traceback.
SystemExit: 2
How can I fix this error to run my script appropriately and pass the arguments in spyder?

You can parse arguments by doing a special run from the settings and putting in the order that the arguments are expected.

How to check cascade and shape predictor is in file same directory?

I'm Using Raspberry pi 3 in opencv python environment but getting this error. Is there an app to open .xml and .dat file in raspberry pi 3?
: error: the following arguments are required: -c/--cascade, -p/--shape-predictor
ap = argparse.ArgumentParser()
ap.add_argument("-c", "--cascade", required=True, help = "path to where the face cascade resides")
ap.add_argument("-p", "--shape-predictor", required=True, help="path to facial landmark predictor")
ap.add_argument("-a", "--alarm", type=int, default=0, help="boolean used to indicate if TrafficHat should be used")
args = vars(ap.parse_args())

View the complete args string while using pdb?

I need to view the complete string in the Argparse object args.networkModel
Original code is from https://github.com/cmusatyalab/openface/blob/master/demos/classifier.py
I only have access to the pdb in the terminal.
When I try the print(args.networkModel) I get
/home/aanilil/ml/openface/demos/../models/openargs.networkModelface/nn4.small2.v1.t7
Is there a way to Print the complete string?
I have also tried the pprint(args.networkModel)
Where I get the output
*** TypeError: 'module' object is not callable
The original parser is constructed like so
parser = argparse.ArgumentParser()
parser.add_argument(
'--dlibFacePredictor',
type=str,
help="Path to dlib's face predictor.",
default=os.path.join(
dlibModelDir,
"shape_predictor_68_face_landmarks.dat"))
parser.add_argument(
'--networkModel',
type=str,
help="Path to Torch network model.",
default=os.path.join(
openfaceModelDir,
'nn4.small2.v1.t7'))
parser.add_argument('--imgDim', type=int,
help="Default image dimension.", default=96)
parser.add_argument('--cuda', action='store_true')
parser.add_argument('--verbose', action='store_true')
subparsers = parser.add_subparsers(dest='mode', help="Mode")
trainParser = subparsers.add_parser('train',
help="Train a new classifier.")
trainParser.add_argument('--ldaDim', type=int, default=-1)
trainParser.add_argument(
'--classifier',
type=str,
choices=[
'LinearSvm',
'GridSearchSvm',
'GMM',
'RadialSvm',
'DecisionTree',
'GaussianNB',
'DBN'],
help='The type of classifier to use.',
default='LinearSvm')
trainParser.add_argument(
'workDir',
type=str,
help="The input work directory containing 'reps.csv' and 'labels.csv'. Obtained from aligning a directory with 'align-dlib' and getting the representations with 'batch-represent'.")
inferParser = subparsers.add_parser(
'infer', help='Predict who an image contains from a trained classifier.')
inferParser.add_argument(
'classifierModel',
type=str,
help='The Python pickle representing the classifier. This is NOT the Torch network model, which can be set with --networkModel.')
inferParser.add_argument('imgs', type=str, nargs='+',
help="Input image.")
inferParser.add_argument('--multi', help="Infer multiple faces in image",
action="store_true")
args = parser.parse_args()