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hackassin
GitHub Repository: hackassin/learnopencv
 Path: blob/master/FaceDetectionComparison/face_detection_dlib_mmod.py
3118 views
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import argparse

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import os

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import time

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import cv2

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import dlib

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def detectFaceDlibMMOD(detector, frame, inHeight=300, inWidth=0):

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    frameDlibMMOD = frame.copy()

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    frameHeight = frameDlibMMOD.shape[0]

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    frameWidth = frameDlibMMOD.shape[1]

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    if not inWidth:

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        inWidth = int((frameWidth / frameHeight) * inHeight)

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    scaleHeight = frameHeight / inHeight

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    scaleWidth = frameWidth / inWidth

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    frameDlibMMODSmall = cv2.resize(frameDlibMMOD, (inWidth, inHeight))

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    frameDlibMMODSmall = cv2.cvtColor(frameDlibMMODSmall, cv2.COLOR_BGR2RGB)

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    faceRects = detector(frameDlibMMODSmall, 0)

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    print(frameWidth, frameHeight, inWidth, inHeight)

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    bboxes = []

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    for faceRect in faceRects:

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        cvRect = [

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            int(faceRect.rect.left() * scaleWidth),

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            int(faceRect.rect.top() * scaleHeight),

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            int(faceRect.rect.right() * scaleWidth),

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            int(faceRect.rect.bottom() * scaleHeight),

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        ]

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        bboxes.append(cvRect)

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        cv2.rectangle(

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            frameDlibMMOD,

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            (cvRect[0], cvRect[1]),

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            (cvRect[2], cvRect[3]),

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            (0, 255, 0),

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            int(round(frameHeight / 150)),

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            4,

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        )

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    return frameDlibMMOD, bboxes

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if __name__ == "__main__":

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    parser = argparse.ArgumentParser(description="Face detection")

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    parser.add_argument("--video", type=str, default="", help="Path to video file")

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    args = parser.parse_args()

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    source = args.video

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    mmodFaceDetector = dlib.cnn_face_detection_model_v1(

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        "models/mmod_human_face_detector.dat",

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    )

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    outputFolder = "output-mmod-videos"

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    if not os.path.exists(outputFolder):

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        os.makedirs(outputFolder)

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    if source:

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        cap = cv2.VideoCapture(source)

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        outputFile = os.path.basename(source)[:-4] + ".avi"

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    else:

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        cap = cv2.VideoCapture(0, cv2.CAP_V4L)

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        outputFile = "grabbed_from_camera.avi"

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    hasFrame, frame = cap.read()

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    vid_writer = cv2.VideoWriter(

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        os.path.join(outputFolder, outputFile),

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        cv2.VideoWriter_fourcc("M", "J", "P", "G"),

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        15,

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        (frame.shape[1], frame.shape[0]),

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    )

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    frame_count = 0

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    tt_dlibMmod = 0

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    while True:

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        hasFrame, frame = cap.read()

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        if not hasFrame:

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            break

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        frame_count += 1

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        t = time.time()

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        outDlibMMOD, bboxes = detectFaceDlibMMOD(mmodFaceDetector, frame)

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        tt_dlibMmod += time.time() - t

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        fpsDlibMmod = frame_count / tt_dlibMmod

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        label = "DLIB MMOD; FPS : {:.2f}".format(fpsDlibMmod)

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        cv2.putText(

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            outDlibMMOD,

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            label,

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            (10, 50),

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            cv2.FONT_HERSHEY_SIMPLEX,

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            1.3,

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            (0, 0, 255),

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            3,

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            cv2.LINE_AA,

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        )

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        cv2.imshow("Face Detection Comparison", outDlibMMOD)

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        vid_writer.write(outDlibMMOD)

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        if frame_count == 1:

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            tt_dlibMmod = 0

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        k = cv2.waitKey(5)

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        if k == 27:

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            break

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    cv2.destroyAllWindows()

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    vid_writer.release()

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