c77493ff9a
* feat/yoloface (#334) * added yolov8 to face_detector (#323) * added yolov8 to face_detector * added yolov8 to face_detector * Initial cleanup and renaming * Update README * refactored detect_with_yoloface (#329) * refactored detect_with_yoloface * apply review * Change order again * Restore working code * modified code (#330) * refactored detect_with_yoloface * apply review * use temp_frame in detect_with_yoloface * reorder * modified * reorder models * Tiny cleanup --------- Co-authored-by: tamoharu <133945583+tamoharu@users.noreply.github.com> * include audio file functions (#336) * Add testing for audio handlers * Change order * Fix naming * Use correct typing in choices * Update help message for arguments, Notation based wording approach (#347) * Update help message for arguments, Notation based wording approach * Fix installer * Audio functions (#345) * Update ffmpeg.py * Create audio.py * Update ffmpeg.py * Update audio.py * Update audio.py * Update typing.py * Update ffmpeg.py * Update audio.py * Rename Frame to VisionFrame (#346) * Minor tidy up * Introduce audio testing * Add more todo for testing * Add more todo for testing * Fix indent * Enable venv on the fly * Enable venv on the fly * Revert venv on the fly * Revert venv on the fly * Force Gradio to shut up * Force Gradio to shut up * Clear temp before processing * Reduce terminal output * include audio file functions * Enforce output resolution on merge video * Minor cleanups * Add age and gender to face debugger items (#353) * Add age and gender to face debugger items * Rename like suggested in the code review * Fix the output framerate vs. time * Lip Sync (#356) * Cli implementation of wav2lip * - create get_first_item() - remove non gan wav2lip model - implement video memory strategy - implement get_reference_frame() - implement process_image() - rearrange crop_mask_list - implement test_cli * Simplify testing * Rename to lip syncer * Fix testing * Fix testing * Minor cleanup * Cuda 12 installer (#362) * Make cuda nightly (12) the default * Better keep legacy cuda just in case * Use CUDA and ROCM versions * Remove MacOS options from installer (CoreML include in default package) * Add lip-syncer support to source component * Add lip-syncer support to source component * Fix the check in the source component * Add target image check * Introduce more helpers to suite the lip-syncer needs * Downgrade onnxruntime as of buggy 1.17.0 release * Revert "Downgrade onnxruntime as of buggy 1.17.0 release" This reverts commit f4a7ae6824fed87f0be50906bbc7e2d61d00617b. * More testing and add todos * Fix the frame processor API to at least not throw errors * Introduce dict based frame processor inputs (#364) * Introduce dict based frame processor inputs * Forgot to adjust webcam * create path payloads (#365) * create index payload to paths for process_frames * rename to payload_paths * This code now is poetry * Fix the terminal output * Make lip-syncer work in the preview * Remove face debugger test for now * Reoder reference_faces, Fix testing * Use inswapper_128 on buggy onnxruntime 1.17.0 * Undo inswapper_128_fp16 duo broken onnxruntime 1.17.0 * Undo inswapper_128_fp16 duo broken onnxruntime 1.17.0 * Fix lip_syncer occluder & region mask issue * Fix preview once in case there was no output video fps * fix lip_syncer custom fps * remove unused import * Add 68 landmark functions (#367) * Add 68 landmark model * Add landmark to face object * Re-arrange and modify typing * Rename function * Rearrange * Rearrange * ignore type * ignore type * change type * ignore * name * Some cleanup * Some cleanup * Opps, I broke something * Feat/face analyser refactoring (#369) * Restructure face analyser and start TDD * YoloFace and Yunet testing are passing * Remove offset from yoloface detection * Cleanup code * Tiny fix * Fix get_many_faces() * Tiny fix (again) * Use 320x320 fallback for retinaface * Fix merging mashup * Upload wave2lip model * Upload 2dfan2 model and rename internal to face_predictor * Downgrade onnxruntime for most cases * Update for the face debugger to render landmark 68 * Try to make detect_face_landmark_68() and detect_gender_age() more uniform * Enable retinaface testing for 320x320 * Make detect_face_landmark_68() and detect_gender_age() as uniform as … (#370) * Make detect_face_landmark_68() and detect_gender_age() as uniform as possible * Revert landmark scale and translation * Make box-mask for lip-syncer adjustable * Add create_bbox_from_landmark() * Remove currently unused code * Feat/uniface (#375) * add uniface (#373) * Finalize UniFace implementation --------- Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com> * My approach how todo it * edit * edit * replace vertical blur with gaussian * remove region mask * Rebase against next and restore method * Minor improvements * Minor improvements * rename & add forehead padding * Adjust and host uniface model * Use 2dfan4 model * Rename to face landmarker * Feat/replace bbox with bounding box (#380) * Add landmark 68 to 5 convertion * Add landmark 68 to 5 convertion * Keep 5, 5/68 and 68 landmarks * Replace kps with landmark * Replace bbox with bounding box * Reshape face_landmark5_list different * Make yoloface the default * Move convert_face_landmark_68_to_5 to face_helper * Minor spacing issue * Dynamic detector sizes according to model (#382) * Dynamic detector sizes according to model * Dynamic detector sizes according to model * Undo false commited files * Add lib syncer model to the UI * fix halo (#383) * Bump to 2.3.0 * Update README and wording * Update README and wording * Fix spacing * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix * Apply _vision suffix, Move mouth mask to face_masker.py * Apply _vision suffix * Apply _vision suffix * increase forehead padding --------- Co-authored-by: tamoharu <133945583+tamoharu@users.noreply.github.com> Co-authored-by: Harisreedhar <46858047+harisreedhar@users.noreply.github.com>
85 lines
2.7 KiB
Python
85 lines
2.7 KiB
Python
import subprocess
|
|
import pytest
|
|
|
|
import facefusion.globals
|
|
from facefusion.download import conditional_download
|
|
from facefusion.face_analyser import clear_face_analyser, get_one_face
|
|
from facefusion.typing import Face
|
|
from facefusion.vision import read_static_image
|
|
|
|
|
|
@pytest.fixture(scope = 'module', autouse = True)
|
|
def before_all() -> None:
|
|
conditional_download('.assets/examples',
|
|
[
|
|
'https://github.com/facefusion/facefusion-assets/releases/download/examples/source.jpg'
|
|
])
|
|
subprocess.run([ 'ffmpeg', '-i', '.assets/examples/source.jpg', '-vf', 'crop=iw*0.8:ih*0.8', '.assets/examples/source-80crop.jpg' ])
|
|
subprocess.run([ 'ffmpeg', '-i', '.assets/examples/source.jpg', '-vf', 'crop=iw*0.7:ih*0.7', '.assets/examples/source-70crop.jpg' ])
|
|
subprocess.run([ 'ffmpeg', '-i', '.assets/examples/source.jpg', '-vf', 'crop=iw*0.6:ih*0.6', '.assets/examples/source-60crop.jpg' ])
|
|
|
|
|
|
@pytest.fixture(autouse = True)
|
|
def before_each() -> None:
|
|
clear_face_analyser()
|
|
|
|
|
|
def test_get_one_face_with_retinaface() -> None:
|
|
facefusion.globals.face_detector_model = 'retinaface'
|
|
facefusion.globals.face_detector_size = '320x320'
|
|
facefusion.globals.face_detector_score = 0.5
|
|
facefusion.globals.face_recognizer_model = 'arcface_inswapper'
|
|
|
|
source_paths =\
|
|
[
|
|
'.assets/examples/source.jpg',
|
|
'.assets/examples/source-80crop.jpg',
|
|
'.assets/examples/source-70crop.jpg',
|
|
'.assets/examples/source-60crop.jpg'
|
|
]
|
|
for source_path in source_paths:
|
|
source_frame = read_static_image(source_path)
|
|
face = get_one_face(source_frame)
|
|
|
|
assert isinstance(face, Face)
|
|
|
|
|
|
def test_get_one_face_with_yoloface() -> None:
|
|
facefusion.globals.face_detector_model = 'yoloface'
|
|
facefusion.globals.face_detector_size = '640x640'
|
|
facefusion.globals.face_detector_score = 0.5
|
|
facefusion.globals.face_recognizer_model = 'arcface_inswapper'
|
|
|
|
source_paths =\
|
|
[
|
|
'.assets/examples/source.jpg',
|
|
'.assets/examples/source-80crop.jpg',
|
|
'.assets/examples/source-70crop.jpg',
|
|
'.assets/examples/source-60crop.jpg'
|
|
]
|
|
for source_path in source_paths:
|
|
source_frame = read_static_image(source_path)
|
|
face = get_one_face(source_frame)
|
|
|
|
assert isinstance(face, Face)
|
|
|
|
|
|
def test_get_one_face_with_yunet() -> None:
|
|
facefusion.globals.face_detector_model = 'yunet'
|
|
facefusion.globals.face_detector_size = '640x640'
|
|
facefusion.globals.face_detector_score = 0.5
|
|
facefusion.globals.face_recognizer_model = 'arcface_inswapper'
|
|
|
|
source_paths =\
|
|
[
|
|
'.assets/examples/source.jpg',
|
|
'.assets/examples/source-80crop.jpg',
|
|
'.assets/examples/source-70crop.jpg',
|
|
'.assets/examples/source-60crop.jpg'
|
|
]
|
|
for source_path in source_paths:
|
|
source_frame = read_static_image(source_path)
|
|
face = get_one_face(source_frame)
|
|
|
|
assert isinstance(face, Face)
|