Next (#436)

* 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>

facefusion/content_analyser.py

@@ -9,7 +9,7 @@ from tqdm import tqdm
 import facefusion.globals
 from facefusion import wording
 from facefusion.typing import VisionFrame, ModelValue, Fps
-from facefusion.execution_helper import apply_execution_provider_options
+from facefusion.execution import apply_execution_provider_options
 from facefusion.vision import get_video_frame, count_video_frame_total, read_image, detect_video_fps
 from facefusion.filesystem import resolve_relative_path
 from facefusion.download import conditional_download
@@ -62,23 +62,23 @@ def analyse_stream(vision_frame : VisionFrame, video_fps : Fps) -> bool:
 	return False
 
 
-def prepare_frame(vision_frame : VisionFrame) -> VisionFrame:
-	vision_frame = cv2.resize(vision_frame, (224, 224)).astype(numpy.float32)
-	vision_frame -= numpy.array([ 104, 117, 123 ]).astype(numpy.float32)
-	vision_frame = numpy.expand_dims(vision_frame, axis = 0)
-	return vision_frame
-
-
 def analyse_frame(vision_frame : VisionFrame) -> bool:
 	content_analyser = get_content_analyser()
 	vision_frame = prepare_frame(vision_frame)
 	probability = content_analyser.run(None,
 	{
-		'input:0': vision_frame
+		content_analyser.get_inputs()[0].name: vision_frame
 	})[0][0][1]
 	return probability > PROBABILITY_LIMIT
 
 
+def prepare_frame(vision_frame : VisionFrame) -> VisionFrame:
+	vision_frame = cv2.resize(vision_frame, (224, 224)).astype(numpy.float32)
+	vision_frame -= numpy.array([ 104, 117, 123 ]).astype(numpy.float32)
+	vision_frame = numpy.expand_dims(vision_frame, axis = 0)
+	return vision_frame
+
+
 @lru_cache(maxsize = None)
 def analyse_image(image_path : str) -> bool:
 	frame = read_image(image_path)