Произошла ошибка при попытке запустить python распознавание лиц с использованием CNN / HOG - PullRequest
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Произошла ошибка при попытке запустить python распознавание лиц с использованием CNN / HOG

0 голосов
/ 25 апреля 2020 
# import the necessary packages
from imutils.video import VideoStream
import face_recognition
import argparse
import imutils
import pickle
import time
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-e", "--encodings", required=True,
    help="path to serialized db of facial encodings")
ap.add_argument("-o", "--output", type=str,
    help="path to output video")
ap.add_argument("-y", "--display", type=int, default=1,
    help="whether or not to display output frame to screen")
ap.add_argument("-d", "--detection-method", type=str, default="cnn",
    help="face detection model to use: either `hog` or `cnn`")
args = vars(ap.parse_args())

# load the known faces and embeddings
print("[INFO] loading encodings...")
data = pickle.loads(open(args["encodings"], "rb").read())

# initialize the video stream and pointer to output video file, then
# allow the camera sensor to warm up
print("[INFO] starting video stream...")
vs = VideoStream(src=0).start()
writer = None
time.sleep(2.0)

# loop over frames from the video file stream
while True:
    # grab the frame from the threaded video stream
    frame = vs.read()

    # convert the input frame from BGR to RGB then resize it to have
    # a width of 750px (to speedup processing)
    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    rgb = imutils.resize(frame, width=750)
    r = frame.shape[1] / float(rgb.shape[1])

    # detect the (x, y)-coordinates of the bounding boxes
    # corresponding to each face in the input frame, then compute
    # the facial embeddings for each face
    boxes = face_recognition.face_locations(rgb,
        model=args["detection_method"])
    encodings = face_recognition.face_encodings(rgb, boxes)
    names = []

    # loop over the facial embeddings
    for encoding in encodings:
        # attempt to match each face in the input image to our known
        # encodings
        matches = face_recognition.compare_faces(data["encodings"],
            encoding)
        name = "Unknown"

        # check to see if we have found a match
        if True in matches:
            # find the indexes of all matched faces then initialize a
            # dictionary to count the total number of times each face
            # was matched
            matchedIdxs = [i for (i, b) in enumerate(matches) if b]
            counts = {}

            # loop over the matched indexes and maintain a count for
            # each recognized face face
            for i in matchedIdxs:
                name = data["names"][i]
                counts[name] = counts.get(name, 0) + 1

            # determine the recognized face with the largest number
            # of votes (note: in the event of an unlikely tie Python
            # will select first entry in the dictionary)
            name = max(counts, key=counts.get)

        # update the list of names
        names.append(name)

    # loop over the recognized faces
    for ((top, right, bottom, left), name) in zip(boxes, names):
        # rescale the face coordinates
        top = int(top * r)
        right = int(right * r)
        bottom = int(bottom * r)
        left = int(left * r)

        # draw the predicted face name on the image
        cv2.rectangle(frame, (left, top), (right, bottom),
            (0, 255, 0), 2)
        y = top - 15 if top - 15 > 15 else top + 15
        cv2.putText(frame, name, (left, y), cv2.FONT_HERSHEY_SIMPLEX,
            0.75, (0, 255, 0), 2)

    # if the video writer is None *AND* we are supposed to write
    # the output video to disk initialize the writer
    if writer is None and args["output"] is not None:
        fourcc = cv2.VideoWriter_fourcc(*"MJPG")
        writer = cv2.VideoWriter(args["output"], fourcc, 20,
            (frame.shape[1], frame.shape[0]), True)

    # if the writer is not None, write the frame with recognized
    # faces t odisk
    if writer is not None:
        writer.write(frame)

    # check to see if we are supposed to display the output frame to
    # the screen
    if args["display"] > 0:
        cv2.imshow("Frame", frame)
        key = cv2.waitKey(1) & 0xFF

        # if the `q` key was pressed, break from the loop
        if key == ord("q"):
            break

# do a bit of cleanup
cv2.destroyAllWindows()
vs.stop()

# check to see if the video writer point needs to be released
if writer is not None:
    writer.release()

Это код, который я написал для распознавания лиц с использованием opencv, cnn и hog, но я получил эту ошибку, я не знаю, как ее решить

Выдает ошибку 

usage: recognize_faces_video.py [-h] -e ENCODINGS [-o OUTPUT] [-y DISPLAY]
                                [-d DETECTION_METHOD]
recognize_faces_video.py: error: the following arguments are required: -e/--encodings

Эта ошибка возникает, когда я пытаюсь запустить этот файл

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