Python my_video_capture 예제들

예제 #1

파일: show_mvmt_on_video.py 프로젝트: Frikster/pyESig2

##        mvmt[m:m+30] = 0
mvmt2 = np.zeros(mvmt.shape[0])
for m in range(0,mvmt.shape[0]-30):
    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m+30]>0)[0]+m])


mvmt2 = (mvmt2 - np.mean(mvmt2))/np.std(mvmt2)

for m in range(0,mvmt.shape[0]):
    if mvmt2[m]>3:
        mvmt2[m]/=3
    if mvmt2[m]<0:
        mvmt2[m]=0


cam = my_video_capture(video_file_loc + \
    "Timm~Katrina_497a1ff8-9b6f-4868-bd2d-752c6b86e192_0078_2.avi", 30)
cam = my_video_capture(video_file_loc + \
    "Lori~Grigor_a2f52bb6-db8b-4f4f-9763-344db14ef2ce_0027_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi = 10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0,4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt-15
    plt.plot(marker_on, 2, marker = '|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi = 100)

예제 #2

파일: face_detect.py 프로젝트: Frikster/pyESig2

                cascade_fns.append(
                    args.get(
                        "--cascade",
                        "C:\\Python27\\lib\\site-packages\\pyESig\\vid\\haarcascades\\haarcascade_profileface.xml",
                    )
                )
                nested_fn = args.get(
                    "--cascade", "C:\\Python27\\lib\\site-packages\\pyESig\\vid\\haarcascades\\haarcascade_eye.xml"
                )
                # cascade_fn  = args.get('--cascade', "C:\\Python27\\lib\\site-packages\\pyESig\\vid\\haarcascades\\Mouth.xml")

                for cascade_fn in cascade_fns:
                    cascades.append(cv2.CascadeClassifier(cascade_fn))
                nested = cv2.CascadeClassifier(nested_fn)

                cam = my_video_capture(video_src, 4)
                frame_cnt = 0
                while cam.has_next():
                    print "video:" + str(n) + " || frame:" + str(frame_cnt)
                    faces = []
                    for i in xrange(4):
                        if cam.has_next():
                            img = cam.read()
                            detected, face = crop_face(cascades, img)
                            face = cv2.resize(face, (32, 32))
                            if detected == True:
                                faces.append(face)
                    if len(faces) > 3:
                        cv2.imwrite(
                            "D:\\face\\" + sbj_id + "_" + day + "\\" + num + "_" + str(frame_cnt) + "_1.png", faces[0]
                        )

예제 #3

파일: face_detect.py 프로젝트: sunh20/pyESig2

                cascade_fns.append(
                    args.get(
                        '--cascade',
                        "C:\\Python27\\lib\\site-packages\\pyESig\\vid\\haarcascades\\haarcascade_profileface.xml"
                    ))
                nested_fn = args.get(
                    '--cascade',
                    "C:\\Python27\\lib\\site-packages\\pyESig\\vid\\haarcascades\\haarcascade_eye.xml"
                )
                #cascade_fn  = args.get('--cascade', "C:\\Python27\\lib\\site-packages\\pyESig\\vid\\haarcascades\\Mouth.xml")

                for cascade_fn in cascade_fns:
                    cascades.append(cv2.CascadeClassifier(cascade_fn))
                nested = cv2.CascadeClassifier(nested_fn)

                cam = my_video_capture(video_src, 4)
                frame_cnt = 0
                while cam.has_next():
                    print "video:" + str(n) + " || frame:" + str(frame_cnt)
                    faces = []
                    for i in xrange(4):
                        if cam.has_next():
                            img = cam.read()
                            detected, face = crop_face(cascades, img)
                            face = cv2.resize(face, (32, 32))
                            if (detected == True):
                                faces.append(face)
                    if (len(faces) > 3):
                        cv2.imwrite(
                            "D:\\face\\" + sbj_id + "_" + day + "\\" + num +
                            "_" + str(frame_cnt) + "_1.png", faces[0])

예제 #4

파일: show_mvmt_on_video_ecog_2.py 프로젝트: nancywang1991/pyESig2

    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m+30]>0)[0]+m])


mvmt2 = (mvmt2 - np.mean(mvmt2))/np.std(mvmt2)

for m in range(0,mvmt.shape[0]):
    if mvmt2[m]>3:
        mvmt2[m]/=3
    if mvmt2[m]<0:
        mvmt2[m]=0





cam = my_video_capture(video_file_loc + \
    "_0145_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi = 10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0,4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt-15
    plt.plot(marker_on, 2, marker = '|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi = 100)

예제 #5

파일: show_mvmt_on_video_ecog.py 프로젝트: Frikster/pyESig2

    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m+30]>0)[0]+m])


mvmt2 = (mvmt2 - np.mean(mvmt2))/np.std(mvmt2)

for m in range(0,mvmt.shape[0]):
    if mvmt2[m]>3:
        mvmt2[m]/=3
    if mvmt2[m]<0:
        mvmt2[m]=0





cam = my_video_capture(video_file_loc + \
    "Timm~Katrina_497a1ff8-9b6f-4868-bd2d-752c6b86e192_0145_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi = 10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0,4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt-15
    plt.plot(marker_on, 2, marker = '|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi = 100)
    

예제 #6

for m in range(0, mvmt.shape[0] - 30):
    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m + 30] > 0)[0] + m])

mvmt2 = (mvmt2 - np.mean(mvmt2)) / np.std(mvmt2)

for m in range(0, mvmt.shape[0]):
    if mvmt2[m] > 3:
        mvmt2[m] /= 3
    if mvmt2[m] < 0:
        mvmt2[m] = 0





cam = my_video_capture(video_file_loc + \
    "Timm~Katrina_497a1ff8-9b6f-4868-bd2d-752c6b86e192_0145_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi=10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0, 4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt - 15
    plt.plot(marker_on, 2, marker='|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi=100)

    img = cam.read()

예제 #7

##    if np.where(mvmt[m:m+30] > 1.1)[0].shape[0] < 5:
##        mvmt[m:m+30] = 0
mvmt2 = np.zeros(mvmt.shape[0])
for m in range(0, mvmt.shape[0] - 30):
    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m + 30] > 0)[0] + m])

mvmt2 = (mvmt2 - np.mean(mvmt2)) / np.std(mvmt2)

for m in range(0, mvmt.shape[0]):
    if mvmt2[m] > 3:
        mvmt2[m] /= 3
    if mvmt2[m] < 0:
        mvmt2[m] = 0


cam = my_video_capture(video_file_loc + \
    "497a1ff8-9b6f-4868-bd2d-752c6b86e192_0078_2.avi", 30)
cam = my_video_capture(video_file_loc + \
    "_a2f52bb6-db8b-4f4f-9763-344db14ef2ce_0027_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi=10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0, 4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt - 15
    plt.plot(marker_on, 2, marker='|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi=100)

예제 #8

파일: show_mvmt_on_video2.py 프로젝트: nancywang1991/pyESig2

##        mvmt[m:m+30] = 0
mvmt2 = np.zeros(mvmt.shape[0])
for m in range(0,mvmt.shape[0]-30):
    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m+30]>0)[0]+m])


mvmt2 = (mvmt2 - np.mean(mvmt2))/np.std(mvmt2)

for m in range(0,mvmt.shape[0]):
    if mvmt2[m]>3:
        mvmt2[m]/=3
    if mvmt2[m]<0:
        mvmt2[m]=0


cam = my_video_capture(video_file_loc + \
    "497a1ff8-9b6f-4868-bd2d-752c6b86e192_0078_2.avi", 30)
cam = my_video_capture(video_file_loc + \
    "_a2f52bb6-db8b-4f4f-9763-344db14ef2ce_0027_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi = 10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0,4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt-15
    plt.plot(marker_on, 2, marker = '|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi = 100)

예제 #9

for m in range(0, mvmt.shape[0] - 30):
    mvmt2[m] = np.mean(mvmt[np.where(mvmt[m:m + 30] > 0)[0] + m])

mvmt2 = (mvmt2 - np.mean(mvmt2)) / np.std(mvmt2)

for m in range(0, mvmt.shape[0]):
    if mvmt2[m] > 3:
        mvmt2[m] /= 3
    if mvmt2[m] < 0:
        mvmt2[m] = 0





cam = my_video_capture(video_file_loc + \
    "_0145_2.avi", 30)
frame_cnt = 1

while cam.has_next():
    plt.figure(figsize=(6.4, 0.5), dpi=10)
    plt.plot(range(mvmt2.shape[0]), mvmt2, mew=0.1)

    plt.ylim([0, 4])
    plt.axis('off')
    plt.text(0.1,1,"Movement\n levels\n", ha='right', \
                 va = 'center', fontsize=10)
    marker_on = frame_cnt - 15
    plt.plot(marker_on, 2, marker='|', mew=2, markersize=100)
    plt.savefig(output_file_loc + "tmp.png", dpi=100)

    img = cam.read()