def get_shots(video_path, downscale_factor=None, threshold=30):
"""
Parameters
----------
video_path : scenedetect VideoManager object.
downscale_factor : Factor by which to downscale video to improve speed.
threshold : Cut detection threshold.
Returns
-------
cut_tuples : A list of tuples where each tuple contains the in- and out-frame of each shot.
"""
#print('Detecting cuts...')
video = VideoManager([video_path])
video.set_downscale_factor(downscale_factor)
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
video.start()
scene_manager.detect_scenes(frame_source=video)
shot_list = scene_manager.get_scene_list()
cut_tuples = []
for shot in shot_list:
cut_tuples.append((shot[0].get_frames(), shot[1].get_frames()))
video.release()
return cut_tuples
def capture_video(video_path, capture_path, default_path):
print("\n[전환장면 캡처 시작] 영상 내 전환 시점을 기준으로 이미지 추출을 시작합니다")
video_manager = VideoManager([video_path])
stats_manager = StatsManager()
scene_manager = SceneManager(stats_manager)
# 가장 예민하게 잡아내도록 1~100 중 1로 설정
scene_manager.add_detector(ContentDetector(threshold=1))
video_manager.set_downscale_factor()
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
scene_list = scene_manager.get_scene_list()
print(">>>", f'{len(scene_list)} scenes detected!') # 전환 인식이 된 장면의 수
save_images(scene_list,
video_manager,
num_images=1,
image_name_template='$SCENE_NUMBER',
output_dir=capture_path)
write_scene_list_html(default_path + 'SceneDetectResult.html', scene_list)
captured_timeline_list = [] # 전환된 시점을 저장할 리스트 함수
for scene in scene_list:
start, end = scene
# 전환 시점 저장
captured_timeline_list.append(start.get_seconds())
print("[전환장면 캡처 종료] 영상 내 전환 시점을 기준으로 이미지 추출을 종료합니다\n")
return captured_timeline_list
def find_scenes(video_path, threshold=30.0):
# Create our video & scene managers, then add the detector.
video_manager = VideoManager([video_path])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
# Improve processing speed by downscaling before processing.
video_manager.set_downscale_factor()
# Start the video manager and perform the scene detection.
video_manager.start()
time = scene_manager.detect_scenes(frame_source=video_manager)
# Each returned scene is a tuple of the (start, end) timecode.
times = scene_manager.get_scene_list(time)
video_splitter.split_video_ffmpeg(
video_path,
times,
'$VIDEO_NAME - Scene $SCENE_NUMBER',
video_path,
arg_override='-c:v libx264 -preset fast -crf 21 -c:a aac',
hide_progress=False,
suppress_output=False)
def keyframe_detection_with_scenedetect(parameters): video = VideoManager([parameters.input_file]) scene = SceneManager() scene.add_detector(ContentDetector(threshold = 30.0)) video.set_downscale_factor() video.start() scene.detect_scenes(frame_source = video) return scene.get_scene_list()
def calculate_scene_list(video: Message, threshold: int = 30) -> List[Tuple[FrameTimecode, FrameTimecode]]:
video_manager = VideoManager([video.message_data.file_path])
stats_manager = StatsManager()
scene_manager = SceneManager(stats_manager)
scene_manager.add_detector(ContentDetector(threshold=threshold))
try:
video_manager.start()
base_timecode = video_manager.get_base_timecode()
scene_manager.detect_scenes(frame_source=video_manager)
scene_list = scene_manager.get_scene_list(base_timecode)
return scene_list
finally:
video_manager.release()
def find_scenes(video_path, threshold=30.0):
# Create our video & scene managers, then add the detector.
video_manager = VideoManager([video_path])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
# Base timestamp at frame 0 (required to obtain the scene list).
base_timecode = video_manager.get_base_timecode()
# Improve processing speed by downscaling before processing.
video_manager.set_downscale_factor()
# Start the video manager and perform the scene detection.
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
# Each returned scene is a tuple of the (start, end) timecode.
return scene_manager.get_scene_list(base_timecode)
def find_scene(video, results):
video_manager = VideoManager([video])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=THRESHOLD))
base_timecode = video_manager.get_base_timecode()
video_manager.set_downscale_factor()
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
scene_list = scene_manager.get_scene_list(base_timecode)
# Each scene is a tuple of (start, end) FrameTimecodes.
for i, scene in enumerate(scene_list):
#scene[0].get_timecode(), scene[0].get_frames(),
#scene[1].get_timecode(), scene[1].get_frames(),))
results.append((scene[0].get_timecode()))
video_manager.release()
def find_scenes(video_path, framerate):
# Create our video & scene managers, then add the detector.
video_manager = VideoManager([str(video_path)])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(THRESHOLD, MINIMUM))
# Improve processing speed by downscaling before processing.
video_manager.set_downscale_factor(DOWNSCALE)
# Start the video manager and perform the scene detection.
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
# Each returned scene is a tuple of the (start, end) timecode.
return scene_manager.get_scene_list(framerate)
def find_scenes(
video_path: str, threshold: float = 30.0
) -> List[Tuple[FrameTimecode, FrameTimecode]]:
# Create our video & scene managers, then add the detector.
video_manager = VideoManager([video_path])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
# Improve processing speed by downscaling before processing.
video_manager.set_downscale_factor()
# Start the video manager and perform the scene detection.
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager, show_progress=False)
# Each returned scene is a tuple of the (start, end) timecode.
return scene_manager.get_scene_list()
def find_scenes(video_path, threshold=30.0):
try:
# Create our video & scene managers, then add the detector.
video_manager = VideoManager([video_path])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
# Improve processing speed by downscaling before processing.
video_manager.set_downscale_factor()
# Start the video manager and perform the scene detection.
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
# Each returned scene is a tuple of the (start, end) timecode.
return scene_manager.get_scene_list()
except Exception as e:
logging.error(e)
def find_scenes(videoURL):
threshold = 30.0
video_path = settings.MEDIA_ROOT
video_path = video_path.replace('\\', '/')
video_manager = VideoManager([video_path + videoURL])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
base_timecode = video_manager.get_base_timecode()
#base_timecode = video_manager.get(cv2.CAP_PROP_POS_MSEC)
video_manager.set_downscale_factor()
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
scene_list = scene_manager.get_scene_list(base_timecode)
return scene_manager.get_scene_list(base_timecode)
def _find_scenes(self, video_path, threshold=30.0):
"""https://pyscenedetect.readthedocs.io/en/latest/
Args:
video_path ([type]): [description]
threshold (float, optional): [description]. Defaults to 30.0.
Returns:
[type]: [description]
"""
video_manager = VideoManager([video_path])
scene_manager = SceneManager()
scene_manager.add_detector(ContentDetector(threshold=threshold))
base_timecode = video_manager.get_base_timecode()
video_manager.set_downscale_factor()
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
time_frames = scene_manager.get_scene_list(base_timecode)
return [(frame[0].get_frames(), frame[1].get_frames())
for frame in time_frames]
for game in tqdm(random.sample(l, len(l))):
# for game in getListGames("v1", task="camera-changes"):
for half in [1, 2]:
filename = f"{SOCCERNET_PATH}/{game}/{half}.mkv"
outname = f"{SOCCERNET_PATH}/{game}/{half}_camerachanges"
# video_path.append(filename)
# ThresholdDetector
# ThresholdDetector
if algo_name == "ContentDetector":
list_param = [10, 20, 30, 40, 50, 60]
for threshold in random.sample(list_param, len(list_param)):
algo = f"{algo_name}{threshold}"
if os.path.exists(f"{outname}_{algo}.json"):
continue
video_manager = VideoManager([filename])
scene_manager = SceneManager()
# for threshold in [10,20,30,40,50,60]:
if algo_name == "ContentDetector":
scene_manager.add_detector(
ContentDetector(threshold=threshold))
# list_param = [64, 128, 256, 32, 16, 8, 4]
# Base timestamp at frame 0 (required to obtain the scene list).
base_timecode = video_manager.get_base_timecode()
# Improve processing speed by downscaling before processing.
video_manager.set_downscale_factor()
from scenedetect import VideoManager, SceneManager, StatsManager
from scenedetect.detectors import ContentDetector
from scenedetect.scene_manager import save_images, write_scene_list_html
# video_path = '/Users/madchick/Desktop/Dropbox/동영상/싸이클01.mp4'
video_path = '/Users/madchick/Projects/test02.mp4'
stats_path = 'result.csv'
video_manager = VideoManager([video_path])
stats_manager = StatsManager()
scene_manager = SceneManager(stats_manager)
scene_manager.add_detector(ContentDetector(threshold=50))
video_manager.set_downscale_factor()
video_manager.start()
scene_manager.detect_scenes(frame_source=video_manager)
# result
with open(stats_path, 'w') as f:
stats_manager.save_to_csv(f, video_manager.get_base_timecode())
scene_list = scene_manager.get_scene_list()
print(f'{len(scene_list)} scenes detected!')
save_images(scene_list,
video_manager,
num_images=1,
image_name_template='$SCENE_NUMBER',
output_dir='scenes')
def test_api(test_video_file):
# (str) -> None
""" Test overall PySceneDetect API functionality.
Can be considered a high level integration/black-box test.
"""
print("Running PySceneDetect API test...")
print("PySceneDetect version being used: %s" %
str(scenedetect.__version__))
# Create a video_manager point to video file testvideo.mp4. Note that multiple
# videos can be appended by simply specifying more file paths in the list
# passed to the VideoManager constructor. Note that appending multiple videos
# requires that they all have the same frame size, and optionally, framerate.
video_manager = VideoManager([test_video_file])
stats_manager = StatsManager()
scene_manager = SceneManager(stats_manager)
# Add ContentDetector algorithm (constructor takes detector options like threshold).
scene_manager.add_detector(ContentDetector())
base_timecode = video_manager.get_base_timecode()
try:
# If stats file exists, load it.
if os.path.exists(STATS_FILE_PATH):
# Read stats from CSV file opened in read mode:
with open(STATS_FILE_PATH, 'r') as stats_file:
stats_manager.load_from_csv(stats_file)
start_time = base_timecode + 20 # 00:00:00.667
end_time = base_timecode + 20.0 # 00:00:20.000
# Set video_manager duration to read frames from 00:00:00 to 00:00:20.
video_manager.set_duration(start_time=start_time, end_time=end_time)
# Set downscale factor to improve processing speed.
video_manager.set_downscale_factor()
# Start video_manager.
video_manager.start()
# Perform scene detection on video_manager.
scene_manager.detect_scenes(frame_source=video_manager)
# Obtain list of detected scenes.
scene_list = scene_manager.get_scene_list()
# Like FrameTimecodes, each scene in the scene_list can be sorted if the
# list of scenes becomes unsorted.
print('List of scenes obtained:')
for i, scene in enumerate(scene_list):
print(' Scene %2d: Start %s / Frame %d, End %s / Frame %d' % (
i + 1,
scene[0].get_timecode(),
scene[0].get_frames(),
scene[1].get_timecode(),
scene[1].get_frames(),
))
# We only write to the stats file if a save is required:
if stats_manager.is_save_required():
with open(STATS_FILE_PATH, 'w') as stats_file:
stats_manager.save_to_csv(stats_file, base_timecode)
finally:
video_manager.release()