def main():
# Extract specific number of key frames from video
# if os.name == 'nt':
# multiprocessing.freeze_support()
vd = Video()
# folder to save extracted images
output_folder_video_image = "selectedframes"
out_dir_path = os.path.join(".", output_folder_video_image)
if not os.path.isdir(out_dir_path):
os.mkdir(out_dir_path)
# number of images to be returned
no_of_frames_to_returned = 20
# VIdeo file path
video_file_path = os.path.join(".", "tests", "data", "pos_video.mp4")
print(f"Input video file path = {video_file_path}")
imgs = vd.extract_video_keyframes(
no_of_frames=no_of_frames_to_returned, file_path=video_file_path
)
# Save it to disk
for counter, img in enumerate(imgs):
vd.save_frame_to_disk(
img,
file_path=out_dir_path,
file_name="test_" + str(counter),
file_ext=".jpeg",
)
print(f"Exracted key frames file path = {out_dir_path}")
def kframe_test():
vd = Video()
from datetime import datetime
dt_start = datetime.now()
test_video_path = '/Users/omelnyk/Work/vidiscovery-recognition/data/KALUSH feat alyona alyona Гори_v720P.mp4'
duration = vd._get_video_duration_with_ffmpeg(test_video_path)
print(int(duration))
imgs = vd.extract_video_keyframes(no_of_frames=int(duration), file_path=test_video_path)
print(len(imgs))
print("extraction time: " + str((datetime.now() - dt_start).total_seconds()))
_, axs = plt.subplots(4, 5, figsize=(20, 20))
axs = axs.flatten()
for img, ax in zip(imgs, axs):
ax.imshow(img)
plt.show()