* Rename landmark 5 variables * Mark as NEXT * Render tabs for multiple ui layout usage * Allow many face detectors at once, Add face detector tweaks * Remove face detector tweaks for now (kinda placebo) * Fix lint issues * Allow rendering the landmark-5 and landmark-5/68 via debugger * Fix naming * Convert face landmark based on confidence score * Convert face landmark based on confidence score * Add scrfd face detector model (#397) * Add scrfd face detector model * Switch to scrfd_2.5g.onnx model * Just some renaming * Downgrade OpenCV, Add SYSTEM_VERSION_COMPAT=0 for MacOS * Improve naming * prepare detect frame outside of semaphore * Feat/process manager (#399) * Minor naming * Introduce process manager to start and stop * Introduce process manager to start and stop * Introduce process manager to start and stop * Introduce process manager to start and stop * Introduce process manager to start and stop * Remove useless test for now * Avoid useless variables * Show stop once is_processing is True * Allow to stop ffmpeg processing too * Implement output image resolution (#403) * Implement output image resolution * Reorder code * Simplify output logic and therefore fix bug * Frame-enhancer-onnx (#404) * changes * changes * changes * changes * add models * update workflow * Some cleanup * Some cleanup * Feat/frame enhancer polishing (#410) * Some cleanup * Polish the frame enhancer * Frame Enhancer: Add more models, optimize processing * Minor changes * Improve readability of create_tile_frames and merge_tile_frames * We don't have enough models yet * Feat/face landmarker score (#413) * Introduce face landmarker score * Fix testing * Fix testing * Use release for score related sliders * Reduce face landmark fallbacks * Scores and landmarks in Face dict, Change color-theme in face debugger * Scores and landmarks in Face dict, Change color-theme in face debugger * Fix some naming * Add 8K support (for whatever reasons) * Fix testing * Using get() for face.landmarks * Introduce statistics * More statistics * Limit the histogram equalization * Enable queue() for default layout * Improve copy_image() * Fix error when switching detector model * Always set UI values with globals if possible * Use different logic for output image and output video resolutions * Enforce re-download if file size is off * Remove unused method * Remove unused method * Remove unused warning filter * Improved output path normalization (#419) * Handle some exceptions * Handle some exceptions * Cleanup * Prevent countless thread locks * Listen to user feedback * Fix webp edge case * Feat/cuda device detection (#424) * Introduce cuda device detection * Introduce cuda device detection * it's gtx * Move logic to run_nvidia_smi() * Finalize execution device naming * Finalize execution device naming * Merge execution_helper.py to execution.py * Undo lowercase of values * Undo lowercase of values * Finalize naming * Add missing entry to ini * fix lip_syncer preview (#426) * fix lip_syncer preview * change * Refresh preview on trim changes * Cleanup frame enhancers and remove useless scale in merge_video() (#428) * Keep lips over the whole video once lip syncer is enabled (#430) * Keep lips over the whole video once lip syncer is enabled * changes * changes * Fix spacing * Use empty audio frame on silence * Use empty audio frame on silence * Fix ConfigParser encoding (#431) facefusion.ini is UTF8 encoded but config.py doesn't specify encoding which results in corrupted entries when non english characters are used. Affected entries: source_paths target_path output_path * Adjust spacing * Improve the GTX 16 series detection * Use general exception to catch ParseError * Use general exception to catch ParseError * Host frame enhancer models4 * Use latest onnxruntime * Minor changes in benchmark UI * Different approach to cancel ffmpeg process * Add support for amd amf encoders (#433) * Add amd_amf encoders * remove -rc cqp from amf encoder parameters * Improve terminal output, move success messages to debug mode * Improve terminal output, move success messages to debug mode * Minor update * Minor update * onnxruntime 1.17.1 matches cuda 12.2 * Feat/improved scaling (#435) * Prevent useless temp upscaling, Show resolution and fps in terminal output * Remove temp frame quality * Remove temp frame quality * Tiny cleanup * Default back to png for temp frames, Remove pix_fmt from frame extraction due mjpeg error * Fix inswapper fallback by onnxruntime * Fix inswapper fallback by major onnxruntime * Fix inswapper fallback by major onnxruntime * Add testing for vision restrict methods * Fix left / right face mask regions, add left-ear and right-ear * Flip right and left again * Undo ears - does not work with box mask * Prepare next release * Fix spacing * 100% quality when using jpg for temp frames * Use span_kendata_x4 as default as of speed * benchmark optimal tile and pad * Undo commented out code * Add real_esrgan_x4_fp16 model * Be strict when using many face detectors --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> Co-authored-by: aldemoth <159712934+aldemoth@users.noreply.github.com>
183 lines
6.7 KiB
Python
183 lines
6.7 KiB
Python
from typing import Optional, Generator, Deque, List
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import os
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import platform
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import subprocess
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import cv2
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import gradio
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from time import sleep
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from concurrent.futures import ThreadPoolExecutor
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from collections import deque
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from tqdm import tqdm
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import facefusion.globals
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from facefusion import logger, wording
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from facefusion.audio import create_empty_audio_frame
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from facefusion.content_analyser import analyse_stream
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from facefusion.filesystem import filter_image_paths
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from facefusion.typing import VisionFrame, Face, Fps
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from facefusion.face_analyser import get_average_face
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from facefusion.processors.frame.core import get_frame_processors_modules, load_frame_processor_module
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from facefusion.ffmpeg import open_ffmpeg
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from facefusion.vision import normalize_frame_color, read_static_images, unpack_resolution
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from facefusion.uis.typing import StreamMode, WebcamMode, ComponentName
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from facefusion.uis.core import get_ui_component
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WEBCAM_CAPTURE : Optional[cv2.VideoCapture] = None
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WEBCAM_IMAGE : Optional[gradio.Image] = None
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WEBCAM_START_BUTTON : Optional[gradio.Button] = None
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WEBCAM_STOP_BUTTON : Optional[gradio.Button] = None
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def get_webcam_capture() -> Optional[cv2.VideoCapture]:
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global WEBCAM_CAPTURE
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if WEBCAM_CAPTURE is None:
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if platform.system().lower() == 'windows':
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webcam_capture = cv2.VideoCapture(0, cv2.CAP_DSHOW)
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else:
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webcam_capture = cv2.VideoCapture(0)
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if webcam_capture and webcam_capture.isOpened():
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WEBCAM_CAPTURE = webcam_capture
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return WEBCAM_CAPTURE
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def clear_webcam_capture() -> None:
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global WEBCAM_CAPTURE
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if WEBCAM_CAPTURE:
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WEBCAM_CAPTURE.release()
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WEBCAM_CAPTURE = None
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def render() -> None:
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global WEBCAM_IMAGE
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global WEBCAM_START_BUTTON
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global WEBCAM_STOP_BUTTON
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WEBCAM_IMAGE = gradio.Image(
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label = wording.get('uis.webcam_image')
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)
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WEBCAM_START_BUTTON = gradio.Button(
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value = wording.get('uis.start_button'),
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variant = 'primary',
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size = 'sm'
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)
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WEBCAM_STOP_BUTTON = gradio.Button(
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value = wording.get('uis.stop_button'),
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size = 'sm'
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)
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def listen() -> None:
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start_event = None
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webcam_mode_radio = get_ui_component('webcam_mode_radio')
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webcam_resolution_dropdown = get_ui_component('webcam_resolution_dropdown')
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webcam_fps_slider = get_ui_component('webcam_fps_slider')
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if webcam_mode_radio and webcam_resolution_dropdown and webcam_fps_slider:
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start_event = WEBCAM_START_BUTTON.click(start, inputs = [ webcam_mode_radio, webcam_resolution_dropdown, webcam_fps_slider ], outputs = WEBCAM_IMAGE)
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WEBCAM_STOP_BUTTON.click(stop, cancels = start_event)
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change_two_component_names : List[ComponentName] =\
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[
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'frame_processors_checkbox_group',
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'face_swapper_model_dropdown',
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'face_enhancer_model_dropdown',
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'frame_enhancer_model_dropdown',
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'lip_syncer_model_dropdown',
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'source_image'
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]
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for component_name in change_two_component_names:
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component = get_ui_component(component_name)
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if component:
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component.change(update, cancels = start_event)
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def start(webcam_mode : WebcamMode, webcam_resolution : str, webcam_fps : Fps) -> Generator[VisionFrame, None, None]:
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facefusion.globals.face_selector_mode = 'one'
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facefusion.globals.face_analyser_order = 'large-small'
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source_image_paths = filter_image_paths(facefusion.globals.source_paths)
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source_frames = read_static_images(source_image_paths)
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source_face = get_average_face(source_frames)
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stream = None
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if webcam_mode in [ 'udp', 'v4l2' ]:
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stream = open_stream(webcam_mode, webcam_resolution, webcam_fps) # type: ignore[arg-type]
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webcam_width, webcam_height = unpack_resolution(webcam_resolution)
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webcam_capture = get_webcam_capture()
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if webcam_capture and webcam_capture.isOpened():
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webcam_capture.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*'MJPG')) # type: ignore[attr-defined]
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webcam_capture.set(cv2.CAP_PROP_FRAME_WIDTH, webcam_width)
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webcam_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, webcam_height)
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webcam_capture.set(cv2.CAP_PROP_FPS, webcam_fps)
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for capture_frame in multi_process_capture(source_face, webcam_capture, webcam_fps):
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if webcam_mode == 'inline':
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yield normalize_frame_color(capture_frame)
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else:
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try:
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stream.stdin.write(capture_frame.tobytes())
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except Exception:
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clear_webcam_capture()
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yield None
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def multi_process_capture(source_face : Face, webcam_capture : cv2.VideoCapture, webcam_fps : Fps) -> Generator[VisionFrame, None, None]:
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with tqdm(desc = wording.get('processing'), unit = 'frame', ascii = ' =', disable = facefusion.globals.log_level in [ 'warn', 'error' ]) as progress:
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with ThreadPoolExecutor(max_workers = facefusion.globals.execution_thread_count) as executor:
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futures = []
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deque_capture_frames : Deque[VisionFrame] = deque()
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while webcam_capture and webcam_capture.isOpened():
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_, capture_frame = webcam_capture.read()
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if analyse_stream(capture_frame, webcam_fps):
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return
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future = executor.submit(process_stream_frame, source_face, capture_frame)
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futures.append(future)
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for future_done in [ future for future in futures if future.done() ]:
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capture_frame = future_done.result()
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deque_capture_frames.append(capture_frame)
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futures.remove(future_done)
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while deque_capture_frames:
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progress.update()
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yield deque_capture_frames.popleft()
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def update() -> None:
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for frame_processor in facefusion.globals.frame_processors:
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frame_processor_module = load_frame_processor_module(frame_processor)
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while not frame_processor_module.post_check():
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logger.disable()
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sleep(0.5)
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logger.enable()
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def stop() -> gradio.Image:
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clear_webcam_capture()
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return gradio.Image(value = None)
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def process_stream_frame(source_face : Face, target_vision_frame : VisionFrame) -> VisionFrame:
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source_audio_frame = create_empty_audio_frame()
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for frame_processor_module in get_frame_processors_modules(facefusion.globals.frame_processors):
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logger.disable()
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if frame_processor_module.pre_process('stream'):
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logger.enable()
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target_vision_frame = frame_processor_module.process_frame(
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{
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'source_face': source_face,
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'source_audio_frame': source_audio_frame,
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'target_vision_frame': target_vision_frame
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})
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return target_vision_frame
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def open_stream(stream_mode : StreamMode, stream_resolution : str, stream_fps : Fps) -> subprocess.Popen[bytes]:
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commands = [ '-f', 'rawvideo', '-pix_fmt', 'bgr24', '-s', stream_resolution, '-r', str(stream_fps), '-i', '-']
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if stream_mode == 'udp':
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commands.extend([ '-b:v', '2000k', '-f', 'mpegts', 'udp://localhost:27000?pkt_size=1316' ])
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if stream_mode == 'v4l2':
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try:
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device_name = os.listdir('/sys/devices/virtual/video4linux')[0]
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if device_name:
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commands.extend([ '-f', 'v4l2', '/dev/' + device_name ])
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except FileNotFoundError:
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logger.error(wording.get('stream_not_loaded').format(stream_mode = stream_mode), __name__.upper())
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return open_ffmpeg(commands)
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