Next (#107)

* Allow passing the onnxruntime to install.py

* Fix CI

* Disallow none execution providers in the UI

* Use CV2 to detect fps

* Respect trim on videos with audio

* Respect trim on videos with audio (finally)

* Implement caching to speed up preview and webcam

* Define webcam UI and webcam performance

* Remove layout from components

* Add primary buttons

* Extract benchmark and webcam settings

* Introduce compact UI settings

* Caching for IO and **** prediction

* Caching for IO and **** prediction

* Introduce face analyser caching

* Fix some typing

* Improve setup for benchmark

* Clear image cache via post process

* Fix settings in UI, Simplify restore_audio() using shortest

* Select resolution and fps via webcam ui

* Introduce read_static_image() to stop caching temp images

* Use DirectShow under Windows

* Multi-threading for webcam

* Fix typing

* Refactor frame processor

* Refactor webcam processing

* Avoid warnings due capture.isOpened()

* Resume downloads (#110)

* Introduce resumable downloads

* Fix CURL commands

* Break execution_settings into pieces

* Cosmetic changes on cv2 webcam

* Update Gradio

* Move face cache to own file

* Uniform namings for threading

* Fix sorting of get_temp_frame_paths(), extend get_temp_frames_pattern()

* Minor changes from the review

* Looks stable to tme

* Update the disclaimer

* Update the disclaimer

* Update the disclaimer

facefusion/vision.py

@@ -1,27 +1,38 @@
 from typing import Optional
+from functools import lru_cache
 import cv2
 
 from facefusion.typing import Frame
 
 
 def get_video_frame(video_path : str, frame_number : int = 0) -> Optional[Frame]:
-	capture = cv2.VideoCapture(video_path)
-	if capture.isOpened():
-		frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
-		capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
-		has_frame, frame = capture.read()
-		capture.release()
-		if has_frame:
-			return frame
+	if video_path:
+		capture = cv2.VideoCapture(video_path)
+		if capture.isOpened():
+			frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
+			capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
+			has_frame, frame = capture.read()
+			capture.release()
+			if has_frame:
+				return frame
+	return None
+
+
+def detect_fps(video_path : str) -> Optional[float]:
+	if video_path:
+		capture = cv2.VideoCapture(video_path)
+		if capture.isOpened():
+			return capture.get(cv2.CAP_PROP_FPS)
 	return None
 
 
 def count_video_frame_total(video_path : str) -> int:
-	capture = cv2.VideoCapture(video_path)
-	if capture.isOpened():
-		video_frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
-		capture.release()
-		return video_frame_total
+	if video_path:
+		capture = cv2.VideoCapture(video_path)
+		if capture.isOpened():
+			video_frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
+			capture.release()
+			return video_frame_total
 	return 0
 
 
@@ -36,3 +47,20 @@ def resize_frame_dimension(frame : Frame, max_height : int) -> Frame:
 		max_width = int(width * scale)
 		frame = cv2.resize(frame, (max_width, max_height))
 	return frame
+
+
+@lru_cache(maxsize = 128)
+def read_static_image(image_path : str) -> Optional[Frame]:
+	return read_image(image_path)
+
+
+def read_image(image_path : str) -> Optional[Frame]:
+	if image_path:
+		return cv2.imread(image_path)
+	return None
+
+
+def write_image(image_path : str, frame : Frame) -> bool:
+	if image_path:
+		return cv2.imwrite(image_path, frame)
+	return False