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- FaceFusion
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- ==========
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-
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- > Next generation face swapper and enhancer.
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-
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- [![Build Status](https://img.shields.io/github/actions/workflow/status/facefusion/facefusion/ci.yml.svg?branch=master)](https://github.com/facefusion/facefusion/actions?query=workflow:ci)
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- ![License](https://img.shields.io/badge/license-MIT-green)
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-
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-
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- Preview
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- -------
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-
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- ![Preview](https://raw.githubusercontent.com/facefusion/facefusion/master/.github/preview.png?sanitize=true)
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-
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-
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- Installation
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- ------------
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-
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- Be aware, the installation needs technical skills and is not for beginners. Please do not open platform and installation related issues on GitHub. We have a very helpful [Discord](https://join.facefusion.io) community that will guide you to complete the installation.
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-
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- Get started with the [installation](https://docs.facefusion.io/installation) guide.
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-
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-
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- Usage
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- -----
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-
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- Run the command:
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-
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- ```
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- python run.py [options]
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-
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- options:
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- -h, --help show this help message and exit
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- -s SOURCE_PATHS, --source SOURCE_PATHS choose single or multiple source images or audios
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- -t TARGET_PATH, --target TARGET_PATH choose single target image or video
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- -o OUTPUT_PATH, --output OUTPUT_PATH specify the output file or directory
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- -v, --version show program's version number and exit
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-
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- misc:
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- --force-download force automate downloads and exit
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- --skip-download omit automate downloads and remote lookups
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- --headless run the program without a user interface
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- --log-level {error,warn,info,debug} adjust the message severity displayed in the terminal
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-
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- execution:
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- --execution-providers EXECUTION_PROVIDERS [EXECUTION_PROVIDERS ...] accelerate the model inference using different providers (choices: cpu, ...)
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- --execution-thread-count [1-128] specify the amount of parallel threads while processing
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- --execution-queue-count [1-32] specify the amount of frames each thread is processing
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-
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- memory:
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- --video-memory-strategy {strict,moderate,tolerant} balance fast frame processing and low VRAM usage
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- --system-memory-limit [0-128] limit the available RAM that can be used while processing
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-
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- face analyser:
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- --face-analyser-order {left-right,right-left,top-bottom,bottom-top,small-large,large-small,best-worst,worst-best} specify the order in which the face analyser detects faces
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- --face-analyser-age {child,teen,adult,senior} filter the detected faces based on their age
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- --face-analyser-gender {female,male} filter the detected faces based on their gender
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- --face-detector-model {many,retinaface,scrfd,yoloface,yunet} choose the model responsible for detecting the face
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- --face-detector-size FACE_DETECTOR_SIZE specify the size of the frame provided to the face detector
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- --face-detector-score [0.0-1.0] filter the detected faces base on the confidence score
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- --face-landmarker-score [0.0-1.0] filter the detected landmarks base on the confidence score
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-
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- face selector:
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- --face-selector-mode {many,one,reference} use reference based tracking or simple matching
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- --reference-face-position REFERENCE_FACE_POSITION specify the position used to create the reference face
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- --reference-face-distance [0.0-1.5] specify the desired similarity between the reference face and target face
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- --reference-frame-number REFERENCE_FRAME_NUMBER specify the frame used to create the reference face
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-
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- face mask:
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- --face-mask-types FACE_MASK_TYPES [FACE_MASK_TYPES ...] mix and match different face mask types (choices: box, occlusion, region)
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- --face-mask-blur [0.0-1.0] specify the degree of blur applied the box mask
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- --face-mask-padding FACE_MASK_PADDING [FACE_MASK_PADDING ...] apply top, right, bottom and left padding to the box mask
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- --face-mask-regions FACE_MASK_REGIONS [FACE_MASK_REGIONS ...] choose the facial features used for the region mask (choices: skin, left-eyebrow, right-eyebrow, left-eye, right-eye, glasses, nose, mouth, upper-lip, lower-lip)
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-
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- frame extraction:
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- --trim-frame-start TRIM_FRAME_START specify the the start frame of the target video
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- --trim-frame-end TRIM_FRAME_END specify the the end frame of the target video
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- --temp-frame-format {bmp,jpg,png} specify the temporary resources format
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- --keep-temp keep the temporary resources after processing
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-
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- output creation:
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- --output-image-quality [0-100] specify the image quality which translates to the compression factor
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- --output-image-resolution OUTPUT_IMAGE_RESOLUTION specify the image output resolution based on the target image
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- --output-video-encoder {libx264,libx265,libvpx-vp9,h264_nvenc,hevc_nvenc,h264_amf,hevc_amf} specify the encoder use for the video compression
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- --output-video-preset {ultrafast,superfast,veryfast,faster,fast,medium,slow,slower,veryslow} balance fast video processing and video file size
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- --output-video-quality [0-100] specify the video quality which translates to the compression factor
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- --output-video-resolution OUTPUT_VIDEO_RESOLUTION specify the video output resolution based on the target video
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- --output-video-fps OUTPUT_VIDEO_FPS specify the video output fps based on the target video
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- --skip-audio omit the audio from the target video
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-
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- frame processors:
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- --frame-processors FRAME_PROCESSORS [FRAME_PROCESSORS ...] load a single or multiple frame processors. (choices: face_debugger, face_enhancer, face_swapper, frame_colorizer, frame_enhancer, lip_syncer, ...)
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- --face-debugger-items FACE_DEBUGGER_ITEMS [FACE_DEBUGGER_ITEMS ...] load a single or multiple frame processors (choices: bounding-box, face-landmark-5, face-landmark-5/68, face-landmark-68, face-landmark-68/5, face-mask, face-detector-score, face-landmarker-score, age, gender)
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- --face-enhancer-model {codeformer,gfpgan_1.2,gfpgan_1.3,gfpgan_1.4,gpen_bfr_256,gpen_bfr_512,gpen_bfr_1024,gpen_bfr_2048,restoreformer_plus_plus} choose the model responsible for enhancing the face
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- --face-enhancer-blend [0-100] blend the enhanced into the previous face
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- --face-swapper-model {blendswap_256,inswapper_128,inswapper_128_fp16,simswap_256,simswap_512_unofficial,uniface_256} choose the model responsible for swapping the face
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- --frame-colorizer-model {ddcolor,ddcolor_artistic,deoldify,deoldify_artistic,deoldify_stable} choose the model responsible for colorizing the frame
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- --frame-colorizer-blend [0-100] blend the colorized into the previous frame
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- --frame-colorizer-size {192x192,256x256,384x384,512x512} specify the size of the frame provided to the frame colorizer
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- --frame-enhancer-model {lsdir_x4,nomos8k_sc_x4,real_esrgan_x2,real_esrgan_x2_fp16,real_esrgan_x4,real_esrgan_x4_fp16,real_hatgan_x4,span_kendata_x4} choose the model responsible for enhancing the frame
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- --frame-enhancer-blend [0-100] blend the enhanced into the previous frame
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- --lip-syncer-model {wav2lip_gan} choose the model responsible for syncing the lips
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-
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- uis:
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- --ui-layouts UI_LAYOUTS [UI_LAYOUTS ...] launch a single or multiple UI layouts (choices: benchmark, default, webcam, ...)
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- ```
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-
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-
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- Documentation
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- -------------
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-
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- Read the [documentation](https://docs.facefusion.io) for a deep dive.
 
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+ ---
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+ title: Test
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+ emoji: 🐢
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+ colorFrom: pink
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+ colorTo: pink
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+ sdk: gradio
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+ sdk_version: 4.27.0
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+ app_file: app.py
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+ pinned: false
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+ license: mit
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference