Use is vision frame everywhere (#1210)

* use is_vision_frame everywhere

* fix hash

* fix lint

facefusion/content_analyser.py

@@ -9,7 +9,7 @@ from facefusion.download import conditional_download_hashes, conditional_downloa
 from facefusion.filesystem import resolve_relative_path
 from facefusion.thread_helper import conditional_thread_semaphore
 from facefusion.types import Detection, DownloadScope, DownloadSet, Fps, InferencePool, ModelSet, VisionFrame
-from facefusion.vision import detect_video_fps, fit_contain_frame, read_image
+from facefusion.vision import detect_video_fps, fit_contain_frame, is_vision_frame, read_image
 
 STREAM_COUNTER = 0
 
@@ -172,7 +172,7 @@ def analyse_video(video_path : str, trim_frame_start : int, trim_frame_end : int
 			vision_frame = video_manager.read_video_frame(video_reader)
 
 			if frame_number % int(video_fps) == 0:
-				if numpy.any(vision_frame):
+				if is_vision_frame(vision_frame):
 					total += 1
 
 					if analyse_frame(vision_frame):

facefusion/core.py

@@ -100,7 +100,7 @@ def pre_check() -> bool:
 def common_pre_check() -> bool:
 	content_analyser_content = inspect.getsource(content_analyser).encode()
 
-	return hash_helper.create_hash(content_analyser_content) == '0922c180'
+	return hash_helper.create_hash(content_analyser_content) == '3c6ce25e'
 
 
 def processors_pre_check() -> bool:

facefusion/face_creator.py

@@ -10,6 +10,7 @@ from facefusion.face_helper import apply_nms, average_points, convert_to_face_la
 from facefusion.face_landmarker import detect_face_landmark, estimate_face_landmark_68_5
 from facefusion.face_recognizer import calculate_face_embedding
 from facefusion.types import BoundingBox, Face, FaceLandmark5, FaceLandmarkSet, FaceScoreSet, Score, VisionFrame
+from facefusion.vision import is_vision_frame
 
 
 def create_faces(vision_frame : VisionFrame, bounding_boxes : List[BoundingBox], face_scores : List[Score], face_landmarks_5 : List[FaceLandmark5]) -> List[Face]:
@@ -73,7 +74,7 @@ def get_many_faces(vision_frames : List[VisionFrame]) -> List[Face]:
 	many_faces : List[Face] = []
 
 	for vision_frame in vision_frames:
-		if numpy.any(vision_frame):
+		if is_vision_frame(vision_frame):
 			all_bounding_boxes = []
 			all_face_scores = []
 			all_face_landmarks_5 = []

facefusion/face_store.py

@@ -1,16 +1,15 @@
 import threading
 from typing import List, Optional
 
-import numpy
-
 from facefusion.hash_helper import create_hash
 from facefusion.types import Face, FaceStore, VisionFrame
+from facefusion.vision import is_vision_frame
 
 FACE_STORE : FaceStore = {}
 
 
 def get_faces(vision_frame : VisionFrame) -> Optional[List[Face]]:
-	if numpy.any(vision_frame):
+	if is_vision_frame(vision_frame):
 		vision_hash = create_hash(vision_frame.data)
 
 		if FACE_STORE.get(vision_hash):
@@ -20,7 +19,7 @@ def get_faces(vision_frame : VisionFrame) -> Optional[List[Face]]:
 
 
 def set_faces(vision_frame : VisionFrame, faces : List[Face]) -> None:
-	if numpy.any(vision_frame):
+	if is_vision_frame(vision_frame):
 		vision_hash = create_hash(vision_frame.data)
 		FACE_STORE.setdefault(vision_hash,
 		{
@@ -29,7 +28,7 @@ def set_faces(vision_frame : VisionFrame, faces : List[Face]) -> None:
 
 
 def resolve_lock(vision_frame : VisionFrame) -> threading.Lock:
-	if numpy.any(vision_frame):
+	if is_vision_frame(vision_frame):
 		vision_hash = create_hash(vision_frame.data)
 		return FACE_STORE.setdefault(vision_hash,
 		{

facefusion/streamer.py

@@ -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)
 

facefusion/uis/components/preview.py

@@ -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))