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https://github.com/facefusion/facefusion.git
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2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 henryruhs
|
a457214575 | ||
|
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b60ea40d26 |
Binary file not shown.
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Before Width: | Height: | Size: 1.1 MiB After Width: | Height: | Size: 1.1 MiB |
@@ -43,7 +43,7 @@ jobs:
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- name: Checkout
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uses: actions/checkout@v4
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- name: Set up FFmpeg
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uses: FedericoCarboni/setup-ffmpeg@v3
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uses: AnimMouse/setup-ffmpeg@v1
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- name: Set up Python 3.12
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uses: actions/setup-python@v5
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with:
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+4
-4
@@ -1,7 +1,3 @@
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[workflow]
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workflow_mode =
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workflow_strategy =
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[paths]
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temp_path =
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jobs_path =
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@@ -72,6 +68,10 @@ output_video_quality =
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output_video_scale =
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output_video_fps =
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[workflow]
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workflow_mode =
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workflow_strategy =
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[processors]
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processors =
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age_modifier_model =
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+2
-2
@@ -9,8 +9,6 @@ from facefusion.vision import detect_video_fps
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def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
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apply_state_item('command', args.get('command'))
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apply_state_item('workflow_mode', args.get('workflow_mode'))
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apply_state_item('workflow_strategy', args.get('workflow_strategy'))
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apply_state_item('temp_path', args.get('temp_path'))
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apply_state_item('jobs_path', args.get('jobs_path'))
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apply_state_item('source_paths', args.get('source_paths'))
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@@ -63,6 +61,8 @@ def apply_args(args : Args, apply_state_item : ApplyStateItem) -> None:
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output_video_fps = normalize_fps(args.get('output_video_fps')) or detect_video_fps(args.get('target_path'))
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apply_state_item('output_video_fps', output_video_fps)
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apply_state_item('workflow_mode', args.get('workflow_mode'))
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apply_state_item('workflow_strategy', args.get('workflow_strategy'))
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available_processors = [ get_file_name(file_path) for file_path in resolve_file_paths('facefusion/processors/modules') ]
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apply_state_item('processors', args.get('processors'))
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@@ -9,7 +9,7 @@ from facefusion.download import conditional_download_hashes, conditional_downloa
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from facefusion.filesystem import resolve_relative_path
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from facefusion.thread_helper import conditional_thread_semaphore
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from facefusion.types import Detection, DownloadScope, DownloadSet, Fps, InferencePool, ModelSet, VisionFrame
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from facefusion.vision import detect_video_fps, fit_contain_frame, read_image
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from facefusion.vision import detect_video_fps, fit_contain_frame, is_vision_frame, read_image
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STREAM_COUNTER = 0
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@@ -172,7 +172,7 @@ def analyse_video(video_path : str, trim_frame_start : int, trim_frame_end : int
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vision_frame = video_manager.read_video_frame(video_reader)
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if frame_number % int(video_fps) == 0:
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if numpy.any(vision_frame):
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if is_vision_frame(vision_frame):
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total += 1
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if analyse_frame(vision_frame):
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+12
-9
@@ -100,7 +100,7 @@ def pre_check() -> bool:
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def common_pre_check() -> bool:
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content_analyser_content = inspect.getsource(content_analyser).encode()
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return hash_helper.create_hash(content_analyser_content) == '0922c180'
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return hash_helper.create_hash(content_analyser_content) == '3c6ce25e'
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def processors_pre_check() -> bool:
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@@ -315,16 +315,19 @@ def conditional_process() -> ErrorCode:
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if state_manager.get_item('workflow_mode') == 'auto':
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state_manager.set_item('workflow_mode', detect_workflow_mode())
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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if not processor_module.pre_process('output'):
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return 2
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if state_manager.get_item('workflow_mode') == detect_workflow_mode():
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for processor_module in get_processors_modules(state_manager.get_item('processors')):
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if not processor_module.pre_process('output'):
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return 2
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if state_manager.get_item('workflow_mode') == 'image-to-image':
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return image_to_image.process(start_time)
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if state_manager.get_item('workflow_mode') == 'image-to-video':
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return image_to_video.process(start_time)
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if state_manager.get_item('workflow_mode') == 'image-to-image':
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return image_to_image.process(start_time)
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if state_manager.get_item('workflow_mode') == 'image-to-video':
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return image_to_video.process(start_time)
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return 0
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return 0
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return 2
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def detect_workflow_mode() -> WorkflowMode:
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@@ -10,6 +10,7 @@ from facefusion.face_helper import apply_nms, average_points, convert_to_face_la
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from facefusion.face_landmarker import detect_face_landmark, estimate_face_landmark_68_5
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from facefusion.face_recognizer import calculate_face_embedding
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from facefusion.types import BoundingBox, Face, FaceLandmark5, FaceLandmarkSet, FaceScoreSet, Score, VisionFrame
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from facefusion.vision import is_vision_frame
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def create_faces(vision_frame : VisionFrame, bounding_boxes : List[BoundingBox], face_scores : List[Score], face_landmarks_5 : List[FaceLandmark5]) -> List[Face]:
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@@ -73,7 +74,7 @@ def get_many_faces(vision_frames : List[VisionFrame]) -> List[Face]:
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many_faces : List[Face] = []
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for vision_frame in vision_frames:
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if numpy.any(vision_frame):
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if is_vision_frame(vision_frame):
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all_bounding_boxes = []
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all_face_scores = []
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all_face_landmarks_5 = []
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@@ -1,17 +1,16 @@
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import threading
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from typing import List, Optional
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import numpy
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from facefusion.hash_helper import create_hash
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from facefusion.types import Face, FaceStore, VisionFrame
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from facefusion.vision import is_vision_frame
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FACE_STORE : FaceStore = {}
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def get_faces(vision_frame : VisionFrame) -> Optional[List[Face]]:
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if numpy.any(vision_frame):
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vision_hash = create_hash(vision_frame.data)
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if is_vision_frame(vision_frame):
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vision_hash = create_hash(vision_frame.tobytes())
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if FACE_STORE.get(vision_hash):
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return FACE_STORE.get(vision_hash).get('faces')
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@@ -20,8 +19,8 @@ def get_faces(vision_frame : VisionFrame) -> Optional[List[Face]]:
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def set_faces(vision_frame : VisionFrame, faces : List[Face]) -> None:
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if numpy.any(vision_frame):
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vision_hash = create_hash(vision_frame.data)
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if is_vision_frame(vision_frame):
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vision_hash = create_hash(vision_frame.tobytes())
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FACE_STORE.setdefault(vision_hash,
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{
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'lock': threading.Lock()
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@@ -29,8 +28,8 @@ def set_faces(vision_frame : VisionFrame, faces : List[Face]) -> None:
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def resolve_lock(vision_frame : VisionFrame) -> threading.Lock:
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if numpy.any(vision_frame):
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vision_hash = create_hash(vision_frame.data)
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if is_vision_frame(vision_frame):
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vision_hash = create_hash(vision_frame.tobytes())
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return FACE_STORE.setdefault(vision_hash,
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{
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'lock': threading.Lock()
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@@ -66,7 +66,7 @@ def run_ffmpeg(commands : List[Command]) -> subprocess.Popen[bytes]:
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def open_ffmpeg(commands : List[Command]) -> subprocess.Popen[bytes]:
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commands = ffmpeg_builder.run(commands)
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return subprocess.Popen(commands, stdin = subprocess.PIPE, stdout = subprocess.PIPE, pipesize = 1024 * 1024)
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return subprocess.Popen(commands, stdin = subprocess.PIPE, stderr = subprocess.DEVNULL, stdout = subprocess.PIPE)
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def create_video_reader(video_path : str, frame_number : int, video_metadata : VideoReaderMetadata) -> subprocess.Popen[bytes]:
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@@ -28,8 +28,8 @@ if is_windows():
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ONNXRUNTIME_SET['directml'] = ('onnxruntime-directml', '1.24.4')
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ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '1.24.4')
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if is_linux():
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ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.25.0')
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ONNXRUNTIME_SET['rocm'] = ('onnxruntime-rocm', '1.22.2.post1')
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ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.26.0')
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ONNXRUNTIME_SET['rocm'] = ('onnxruntime-rocm', '1.22.2.post3')
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def cli() -> None:
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@@ -98,8 +98,6 @@ LOCALES : Locales =\
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{
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'install_dependency': 'choose the variant of {dependency} to install',
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'skip_conda': 'skip the conda environment check',
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'workflow_mode': 'choose the workflow mode',
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'workflow_strategy': 'choose the workflow strategy',
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'config_path': 'choose the config file to override defaults',
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'temp_path': 'specify the directory for the temporary resources',
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'jobs_path': 'specify the directory to store jobs',
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@@ -136,7 +134,7 @@ LOCALES : Locales =\
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'voice_extractor_model': 'choose the model responsible for extracting the voices',
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'trim_frame_start': 'specify the starting frame of the target video',
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'trim_frame_end': 'specify the ending frame of the target video',
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'temp_frame_format': 'specify the temporary resources format',
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'temp_frame_format': 'specify the temporary frame format',
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'temp_pixel_format': 'specify the temporary pixel format',
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'target_frame_amount': 'specify the amount of target frames forwarded to the processor',
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'output_image_quality': 'specify the image quality which translates to the image compression',
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@@ -149,6 +147,8 @@ LOCALES : Locales =\
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'output_video_quality': 'specify the video quality which translates to the video compression',
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'output_video_scale': 'specify the video scale based on the target video',
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'output_video_fps': 'specify the video fps based on the target video',
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'workflow_mode': 'detect or enforce the workflow mode',
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'workflow_strategy': 'process the temporary frames in memory or on disk',
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'processors': 'load a single or multiple processors (choices: {choices}, ...)',
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'background-remover-model': 'choose the model responsible for removing the background',
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'background-remover-color': 'apply red, green blue and alpha values of the background',
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@@ -204,7 +204,6 @@ LOCALES : Locales =\
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'clear_button': 'CLEAR',
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'download_providers_checkbox_group': 'DOWNLOAD PROVIDERS',
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'execution_providers_checkbox_group': 'EXECUTION PROVIDERS',
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'workflow_mode_dropdown': 'WORKFLOW MODE',
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'workflow_strategy_dropdown': 'WORKFLOW STRATEGY',
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'execution_thread_count_slider': 'EXECUTION THREAD COUNT',
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'face_detector_angles_checkbox_group': 'FACE DETECTOR ANGLES',
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@@ -4,7 +4,7 @@ METADATA =\
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{
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'name': 'FaceFusion',
|
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'description': 'Industry leading face manipulation platform',
|
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'version': 'NEXT',
|
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'version': '3.8.0',
|
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'license': 'OpenRAIL-AS',
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'author': 'Henry Ruhs',
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'url': 'https://facefusion.io'
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@@ -9,4 +9,4 @@ FrameEnhancerInputs = TypedDict('FrameEnhancerInputs',
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'temp_vision_mask' : Mask
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})
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FrameEnhancerModel = Literal['clear_reality_x4', 'face_dat_x4', 'lsdir_x4', 'nomos8k_sc_x4', 'real_esrgan_x2', 'real_esrgan_x2_fp16', 'real_esrgan_x4', 'real_esrgan_x4_fp16', 'real_esrgan_x8', 'real_esrgan_x8_fp16', 'real_hatgan_x4', 'real_web_photo_x4', 'realistic_rescaler_x4', 'remacri_x4', 'siax_x4', 'span_kendata_x4', 'swin2_sr_x4', 'tghq_face_x8', 'ultra_sharp_x4', 'ultra_sharp_2_x4']
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FrameEnhancerModel = Literal['clear_reality_x4', 'face_dat_x4', 'nomos8k_sc_x4', 'real_esrgan_x2', 'real_esrgan_x2_fp16', 'real_esrgan_x4', 'real_esrgan_x4_fp16', 'real_esrgan_x8', 'real_esrgan_x8_fp16', 'real_hatgan_x4', 'real_web_photo_x4', 'realistic_rescaler_x4', 'remacri_x4', 'siax_x4', 'span_kendata_x4', 'swin2_sr_x4', 'tghq_face_x8', 'ultra_sharp_x4', 'ultra_sharp_2_x4']
|
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|
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+10
-10
@@ -21,15 +21,6 @@ def create_help_formatter_large(prog : str) -> HelpFormatter:
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return HelpFormatter(prog, max_help_position = 300)
|
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|
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|
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def create_workflow_program() -> ArgumentParser:
|
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program = ArgumentParser(add_help = False)
|
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group_workflow = program.add_argument_group('workflow')
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group_workflow.add_argument('--workflow-mode', help = translator.get('help.workflow_mode'), default = config.get_str_value('workflow', 'workflow_mode', 'auto'), choices = facefusion.choices.workflow_modes)
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group_workflow.add_argument('--workflow-strategy', help = translator.get('help.workflow_strategy'), default = config.get_str_value('workflow', 'workflow_strategy', 'stream'), choices = facefusion.choices.workflow_strategies)
|
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job_store.register_step_keys([ 'workflow_mode', 'workflow_strategy' ])
|
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return program
|
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|
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|
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def create_config_path_program() -> ArgumentParser:
|
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program = ArgumentParser(add_help = False)
|
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group_paths = program.add_argument_group('paths')
|
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@@ -209,6 +200,15 @@ def create_output_creation_program() -> ArgumentParser:
|
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return program
|
||||
|
||||
|
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def create_workflow_program() -> ArgumentParser:
|
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program = ArgumentParser(add_help = False)
|
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group_workflow = program.add_argument_group('workflow')
|
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group_workflow.add_argument('--workflow-mode', help = translator.get('help.workflow_mode'), default = config.get_str_value('workflow', 'workflow_mode', 'auto'), choices = facefusion.choices.workflow_modes)
|
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group_workflow.add_argument('--workflow-strategy', help = translator.get('help.workflow_strategy'), default = config.get_str_value('workflow', 'workflow_strategy', 'memory'), choices = facefusion.choices.workflow_strategies)
|
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job_store.register_step_keys([ 'workflow_mode', 'workflow_strategy' ])
|
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return program
|
||||
|
||||
|
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def create_processors_program() -> ArgumentParser:
|
||||
program = ArgumentParser(add_help = False)
|
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available_processors = [ get_file_name(file_path) for file_path in resolve_file_paths('facefusion/processors/modules') ]
|
||||
@@ -309,7 +309,7 @@ def create_step_index_program() -> ArgumentParser:
|
||||
|
||||
|
||||
def collect_step_program() -> ArgumentParser:
|
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return ArgumentParser(parents = [ create_workflow_program(), create_face_detector_program(), create_face_landmarker_program(), create_face_selector_program(), create_face_tracker_program(), create_face_masker_program(), create_voice_extractor_program(), create_frame_extraction_program(), create_frame_distribution_program(), create_output_creation_program(), create_processors_program() ], add_help = False)
|
||||
return ArgumentParser(parents = [ create_face_detector_program(), create_face_landmarker_program(), create_face_selector_program(), create_face_tracker_program(), create_face_masker_program(), create_voice_extractor_program(), create_frame_extraction_program(), create_frame_distribution_program(), create_output_creation_program(), create_workflow_program(), create_processors_program() ], add_help = False)
|
||||
|
||||
|
||||
def collect_job_program() -> ArgumentParser:
|
||||
|
||||
@@ -5,7 +5,6 @@ from concurrent.futures import ThreadPoolExecutor
|
||||
from typing import Deque, Iterator, List
|
||||
|
||||
import cv2
|
||||
import numpy
|
||||
from tqdm import tqdm
|
||||
|
||||
from facefusion import ffmpeg_builder, logger, state_manager, translator
|
||||
@@ -15,7 +14,7 @@ from facefusion.ffmpeg import open_ffmpeg
|
||||
from facefusion.filesystem import is_directory
|
||||
from facefusion.processors.core import get_processors_modules
|
||||
from facefusion.types import Fps, StreamMode, VisionFrame
|
||||
from facefusion.vision import extract_vision_mask, read_static_images
|
||||
from facefusion.vision import extract_vision_mask, is_vision_frame, read_static_images
|
||||
|
||||
|
||||
def multi_process_capture(camera_capture : cv2.VideoCapture, camera_fps : Fps) -> Iterator[VisionFrame]:
|
||||
@@ -31,7 +30,7 @@ def multi_process_capture(camera_capture : cv2.VideoCapture, camera_fps : Fps) -
|
||||
if analyse_stream(capture_vision_frame, camera_fps):
|
||||
camera_capture.release()
|
||||
|
||||
if numpy.any(capture_vision_frame):
|
||||
if is_vision_frame(capture_vision_frame):
|
||||
future = executor.submit(process_stream_frame, source_vision_frames, capture_vision_frame)
|
||||
futures.append(future)
|
||||
|
||||
|
||||
+5
-5
@@ -65,7 +65,7 @@ Locales : TypeAlias = Dict[Language, Dict[str, Any]]
|
||||
LocalePoolSet : TypeAlias = Dict[str, Locales]
|
||||
|
||||
WorkflowMode = Literal['auto', 'image-to-image', 'image-to-video']
|
||||
WorkflowStrategy = Literal['disk', 'stream']
|
||||
WorkflowStrategy = Literal['disk', 'memory']
|
||||
|
||||
CameraCaptureSet : TypeAlias = Dict[str, cv2.VideoCapture]
|
||||
CameraPoolSet = TypedDict('CameraPoolSet',
|
||||
@@ -322,8 +322,6 @@ JobSet : TypeAlias = Dict[str, Job]
|
||||
StateKey = Literal\
|
||||
[
|
||||
'command',
|
||||
'workflow_mode',
|
||||
'workflow_strategy',
|
||||
'config_path',
|
||||
'temp_path',
|
||||
'jobs_path',
|
||||
@@ -378,6 +376,8 @@ StateKey = Literal\
|
||||
'output_video_quality',
|
||||
'output_video_scale',
|
||||
'output_video_fps',
|
||||
'workflow_mode',
|
||||
'workflow_strategy',
|
||||
'processors',
|
||||
'open_browser',
|
||||
'ui_layouts',
|
||||
@@ -395,8 +395,6 @@ StateKey = Literal\
|
||||
State = TypedDict('State',
|
||||
{
|
||||
'command' : str,
|
||||
'workflow_mode' : WorkflowMode,
|
||||
'workflow_strategy' : WorkflowStrategy,
|
||||
'config_path' : str,
|
||||
'temp_path' : str,
|
||||
'jobs_path' : str,
|
||||
@@ -451,6 +449,8 @@ State = TypedDict('State',
|
||||
'output_video_quality' : int,
|
||||
'output_video_scale' : Scale,
|
||||
'output_video_fps' : float,
|
||||
'workflow_mode' : WorkflowMode,
|
||||
'workflow_strategy' : WorkflowStrategy,
|
||||
'processors' : List[str],
|
||||
'open_browser' : bool,
|
||||
'ui_layouts' : List[str],
|
||||
|
||||
@@ -18,7 +18,7 @@ from facefusion.types import AudioFrame, Face, Mask, VisionFrame
|
||||
from facefusion.uis import choices as uis_choices
|
||||
from facefusion.uis.core import get_ui_component, get_ui_components, register_ui_component
|
||||
from facefusion.uis.types import ComponentOptions, PreviewMode
|
||||
from facefusion.vision import detect_frame_orientation, extract_vision_mask, fit_cover_frame, merge_vision_mask, obscure_frame, read_static_image, read_static_images, read_video_frame, restrict_frame, select_video_frames, unpack_resolution
|
||||
from facefusion.vision import detect_frame_orientation, extract_vision_mask, fit_cover_frame, is_vision_frame, merge_vision_mask, obscure_frame, read_static_image, read_static_images, read_video_frame, restrict_frame, select_video_frames, unpack_resolution
|
||||
|
||||
PREVIEW_IMAGE : Optional[gradio.Image] = None
|
||||
|
||||
@@ -277,7 +277,7 @@ def create_face_by_face(reference_vision_frame : VisionFrame, source_vision_fram
|
||||
target_crop_vision_frame = extract_crop_frame(target_vision_frame, target_face)
|
||||
output_crop_vision_frame = extract_crop_frame(temp_vision_frame, target_face)
|
||||
|
||||
if numpy.any(target_crop_vision_frame) and numpy.any(output_crop_vision_frame):
|
||||
if is_vision_frame(target_crop_vision_frame) and is_vision_frame(output_crop_vision_frame):
|
||||
target_crop_dimension = min(target_crop_vision_frame.shape[:2])
|
||||
target_crop_vision_frame = fit_cover_frame(target_crop_vision_frame, (target_crop_dimension, target_crop_dimension))
|
||||
output_crop_vision_frame = fit_cover_frame(output_crop_vision_frame, (target_crop_dimension, target_crop_dimension))
|
||||
|
||||
@@ -4,21 +4,14 @@ import gradio
|
||||
|
||||
import facefusion.choices
|
||||
from facefusion import state_manager, translator
|
||||
from facefusion.types import WorkflowMode, WorkflowStrategy
|
||||
from facefusion.types import WorkflowStrategy
|
||||
|
||||
WORKFLOW_MODE_DROPDOWN : Optional[gradio.Dropdown] = None
|
||||
WORKFLOW_STRATEGY_DROPDOWN : Optional[gradio.Dropdown] = None
|
||||
|
||||
|
||||
def render() -> None:
|
||||
global WORKFLOW_MODE_DROPDOWN
|
||||
global WORKFLOW_STRATEGY_DROPDOWN
|
||||
|
||||
WORKFLOW_MODE_DROPDOWN = gradio.Dropdown(
|
||||
label = translator.get('uis.workflow_mode_dropdown'),
|
||||
choices = facefusion.choices.workflow_modes,
|
||||
value = state_manager.get_item('workflow_mode')
|
||||
)
|
||||
WORKFLOW_STRATEGY_DROPDOWN = gradio.Dropdown(
|
||||
label = translator.get('uis.workflow_strategy_dropdown'),
|
||||
choices = facefusion.choices.workflow_strategies,
|
||||
@@ -27,13 +20,8 @@ def render() -> None:
|
||||
|
||||
|
||||
def listen() -> None:
|
||||
WORKFLOW_MODE_DROPDOWN.change(update_workflow_mode, inputs = WORKFLOW_MODE_DROPDOWN)
|
||||
WORKFLOW_STRATEGY_DROPDOWN.change(update_workflow_strategy, inputs = WORKFLOW_STRATEGY_DROPDOWN)
|
||||
|
||||
|
||||
def update_workflow_mode(workflow_mode : WorkflowMode) -> None:
|
||||
state_manager.set_item('workflow_mode', workflow_mode)
|
||||
|
||||
|
||||
def update_workflow_strategy(workflow_strategy : WorkflowStrategy) -> None:
|
||||
state_manager.set_item('workflow_strategy', workflow_strategy)
|
||||
|
||||
@@ -3,7 +3,7 @@ from functools import partial
|
||||
from facefusion import process_manager, state_manager
|
||||
from facefusion.types import ErrorCode
|
||||
from facefusion.workflows.core import clear, setup
|
||||
from facefusion.workflows.to_video import analyse_video, extract_frames, finalize_video, merge_frames, process_disk_frames, process_stream_frames, restore_audio
|
||||
from facefusion.workflows.to_video import analyse_video, extract_frames, finalize_video, merge_frames, process_disk_frames, process_memory_frames, restore_audio
|
||||
|
||||
|
||||
def process(start_time : float) -> ErrorCode:
|
||||
@@ -22,8 +22,8 @@ def process(start_time : float) -> ErrorCode:
|
||||
merge_frames
|
||||
])
|
||||
|
||||
if state_manager.get_item('workflow_strategy') == 'stream':
|
||||
tasks.append(process_stream_frames)
|
||||
if state_manager.get_item('workflow_strategy') == 'memory':
|
||||
tasks.append(process_memory_frames)
|
||||
|
||||
tasks.extend(
|
||||
[
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
from typing import Tuple
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from itertools import repeat
|
||||
|
||||
import cv2
|
||||
import numpy
|
||||
@@ -58,19 +58,8 @@ def process_disk_frames() -> ErrorCode:
|
||||
read_static_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
|
||||
|
||||
with ThreadPoolExecutor(max_workers = state_manager.get_item('execution_thread_count')) as executor:
|
||||
futures = []
|
||||
|
||||
for frame_number, temp_frame_path in temp_frame_set.items():
|
||||
future = executor.submit(process_disk_frame, temp_frame_path, frame_number)
|
||||
futures.append(future)
|
||||
|
||||
for future in as_completed(futures):
|
||||
if is_process_stopping():
|
||||
for pending_future in futures:
|
||||
pending_future.cancel()
|
||||
|
||||
if not future.cancelled():
|
||||
future.result()
|
||||
for temp_vision_frame_ in executor.map(process_disk_frame, temp_frame_set.values(), temp_frame_set.keys()):
|
||||
if not is_process_stopping():
|
||||
progress.update()
|
||||
|
||||
for processor_module in get_processors_modules(state_manager.get_item('processors')):
|
||||
@@ -84,7 +73,7 @@ def process_disk_frames() -> ErrorCode:
|
||||
return 0
|
||||
|
||||
|
||||
def process_stream_frame(frame_number : int, temp_video_resolution : Resolution) -> Tuple[int, VisionFrame]:
|
||||
def process_memory_frame(frame_number : int, temp_video_resolution : Resolution) -> VisionFrame:
|
||||
target_vision_frames = select_video_frames(state_manager.get_item('target_path'), frame_number, state_manager.get_item('target_frame_amount'))
|
||||
target_vision_frame = get_middle(target_vision_frames)
|
||||
temp_vision_frame = target_vision_frame.copy()
|
||||
@@ -100,10 +89,10 @@ def process_stream_frame(frame_number : int, temp_video_resolution : Resolution)
|
||||
if state_manager.get_item('temp_pixel_format') == 'bgr24':
|
||||
temp_vision_frame = temp_vision_frame[:, :, :3]
|
||||
|
||||
return frame_number, numpy.ascontiguousarray(temp_vision_frame)
|
||||
return numpy.ascontiguousarray(temp_vision_frame)
|
||||
|
||||
|
||||
def process_stream_frames() -> ErrorCode:
|
||||
def process_memory_frames() -> ErrorCode:
|
||||
trim_frame_start, trim_frame_end = restrict_trim_frame(state_manager.get_item('target_path'), state_manager.get_item('trim_frame_start'), state_manager.get_item('trim_frame_end'))
|
||||
output_video_resolution = scale_resolution(detect_video_resolution(state_manager.get_item('target_path')), state_manager.get_item('output_video_scale'))
|
||||
temp_video_resolution = restrict_video_resolution(state_manager.get_item('target_path'), output_video_resolution)
|
||||
@@ -119,19 +108,8 @@ def process_stream_frames() -> ErrorCode:
|
||||
read_static_video_frame(state_manager.get_item('target_path'), state_manager.get_item('reference_frame_number'))
|
||||
|
||||
with ThreadPoolExecutor(max_workers = state_manager.get_item('execution_thread_count')) as executor:
|
||||
futures = []
|
||||
|
||||
for frame_number in temp_frame_range:
|
||||
future = executor.submit(process_stream_frame, frame_number, temp_video_resolution)
|
||||
futures.append(future)
|
||||
|
||||
for future in futures:
|
||||
if is_process_stopping():
|
||||
for pending_future in futures:
|
||||
pending_future.cancel()
|
||||
|
||||
if not future.cancelled():
|
||||
_, temp_vision_frame = future.result()
|
||||
for temp_vision_frame in executor.map(process_memory_frame, temp_frame_range, repeat(temp_video_resolution)):
|
||||
if not is_process_stopping():
|
||||
video_manager.write_video_frame(video_writer, temp_vision_frame)
|
||||
progress.update()
|
||||
|
||||
|
||||
+5
-5
@@ -1,8 +1,8 @@
|
||||
gradio-rangeslider==0.0.8
|
||||
gradio==5.50.0
|
||||
numpy==2.2.1
|
||||
onnx==1.21.0
|
||||
numpy==2.4.6
|
||||
onnx==1.22.0
|
||||
onnxruntime==1.26.0
|
||||
opencv-python==4.13.0.92
|
||||
tqdm==4.67.3
|
||||
scipy==1.17.1
|
||||
opencv-python-headless==5.0.0.93
|
||||
tqdm==4.70.0
|
||||
scipy==1.18.0
|
||||
|
||||
@@ -50,34 +50,35 @@ def test_get_reader() -> None:
|
||||
assert video_metadata.get('resolution') == (426, 226)
|
||||
assert video_metadata.get('fps') == 25.0
|
||||
assert video_metadata.get('frame_total') == 270
|
||||
|
||||
assert get_reader(get_test_example_file('target-240p-25fps.mp4'), 'read_video_frame') is video_reader
|
||||
assert not get_reader(get_test_example_file('target-240p-25fps.mp4'), 'select_video_frames').get('id') == video_reader.get('id')
|
||||
|
||||
|
||||
def test_conditional_seek_video_reader() -> None:
|
||||
video_reader = get_reader(get_test_example_file('target-240p-25fps.mp4'), 'read_video_frame')
|
||||
sequential_frames = {}
|
||||
video_frames = {}
|
||||
|
||||
for frame_number in range(30):
|
||||
sequential_frames[frame_number] = read_video_frame(video_reader)
|
||||
video_frames[frame_number] = read_video_frame(video_reader)
|
||||
|
||||
for frame_number in [ 5, 17, 29 ]:
|
||||
conditional_seek_video_reader(video_reader, frame_number)
|
||||
|
||||
assert numpy.array_equal(read_video_frame(video_reader), sequential_frames.get(frame_number)) is True
|
||||
assert numpy.array_equal(read_video_frame(video_reader), video_frames.get(frame_number)) is True
|
||||
|
||||
|
||||
def test_seek_video_reader() -> None:
|
||||
video_reader = get_reader(get_test_example_file('target-240p-25fps.mp4'), 'read_video_frame')
|
||||
sequential_frames = {}
|
||||
video_frames = {}
|
||||
|
||||
for frame_number in range(30):
|
||||
sequential_frames[frame_number] = read_video_frame(video_reader)
|
||||
video_frames[frame_number] = read_video_frame(video_reader)
|
||||
|
||||
for frame_number in [ 5, 17, 29 ]:
|
||||
seek_video_reader(video_reader, frame_number)
|
||||
|
||||
assert numpy.array_equal(read_video_frame(video_reader), sequential_frames.get(frame_number)) is True
|
||||
assert numpy.array_equal(read_video_frame(video_reader), video_frames.get(frame_number)) is True
|
||||
|
||||
|
||||
def test_drain_video_reader() -> None:
|
||||
@@ -133,6 +134,7 @@ def test_collect_video_frames() -> None:
|
||||
|
||||
def test_close_video_reader() -> None:
|
||||
video_reader = get_reader(get_test_example_file('target-240p-25fps.mp4'), 'select_video_frames')
|
||||
|
||||
read_video_frames(video_reader, 0, 4)
|
||||
close_video_reader(video_reader)
|
||||
|
||||
@@ -176,6 +178,7 @@ def test_close_video_writer() -> None:
|
||||
create_temp_directory(target_path)
|
||||
video_reader = get_reader(target_path, 'read_video_frame')
|
||||
video_writer = get_writer(target_path, 30.0, (426, 226), (426, 226), 30.0)
|
||||
|
||||
write_video_frame(video_writer, read_video_frame(video_reader))
|
||||
|
||||
assert close_video_writer(video_writer) is True
|
||||
@@ -186,6 +189,7 @@ def test_clear_video_pool() -> None:
|
||||
create_temp_directory(target_path)
|
||||
video_reader = get_reader(target_path, 'select_video_frames')
|
||||
video_writer = get_writer(target_path, 25.0, (426, 226), (426, 226), 25.0)
|
||||
|
||||
read_video_frames(video_reader, 0, 4)
|
||||
write_video_frame(video_writer, read_video_frame(video_reader))
|
||||
clear_video_pool()
|
||||
|
||||
Reference in New Issue
Block a user