New AutoColor adjustment filter

[Selur]

Here's a AutoLevelsYUV444 version:

import vapoursynth as vs import numpy as np import ctypes import cv2 core = vs.core def AutoLevelsYUV444( clip: vs.VideoNode, method: int = 4, clip_limit: float = 1.0, gridsize: int = 8, strength: float = 0.5 ) -> vs.VideoNode: fmt = clip.format if fmt.color_family != vs.YUV or fmt.subsampling_w or fmt.subsampling_h: raise vs.Error("AutoLevelsYUV444: Only YUV444 formats are allowed") bits = fmt.bits_per_sample is_float = fmt.sample_type == vs.FLOAT peak = 1.0 if is_float else (1 << bits) - 1 # Choose NumPy and ctypes types based on bit depth if is_float: dtype = np.float32 ctype = ctypes.c_float else: dtype = np.uint8 if bits <= 8 else np.uint16 ctype = ctypes.c_uint8 if bits <= 8 else ctypes.c_uint16 def _process_plane(plane: np.ndarray, mode: str, algo: int) -> np.ndarray: # plane: 2D array with values in [0, peak] # → 8-bit for OpenCV p8 = np.clip((plane / peak) * 255, 0, 255).astype(np.uint8) if mode == "clahe": clahe = cv2.createCLAHE(clipLimit=clip_limit, tileGridSize=(gridsize, gridsize)) out8 = clahe.apply(p8) elif mode == "hist": out8 = cv2.equalizeHist(p8) else: # scale hist = cv2.calcHist([p8],[0],None,[256],[0,256]).ravel() cdf = hist.cumsum(); total = cdf[-1] clipv = clip_limit * total / 200.0 lo = np.searchsorted(cdf, clipv) hi = np.searchsorted(cdf, total - clipv) alpha = 255 / max(hi - lo, 1) beta = -lo * alpha out8 = (cv2.convertScaleAbs(p8, alpha=alpha, beta=beta) if algo==0 else np.clip(p8*alpha+beta,0,255).astype(np.uint8)) # back to original range return ((out8.astype(np.float32) / 255) * peak).astype(dtype) def read_plane(f: vs.VideoFrame, idx: int) -> np.ndarray: """Reads plane idx as (height×width) array via ctypes.from_address.""" w, h = clip.width, clip.height ptr = f.get_read_ptr(idx) # c_void_p addr = ptr if isinstance(ptr, int) else ptr.value buf_len = w * h # Create ctypes array and convert buf_type = ctype * buf_len buf = buf_type.from_address(addr) arr = np.ctypeslib.as_array(buf) # 1D array return arr.reshape((h, w)) def write_plane(f: vs.VideoFrame, idx: int, data: np.ndarray): """Writes data (h×w) back to plane idx.""" w, h = clip.width, clip.height ptr = f.get_write_ptr(idx) addr = ptr if isinstance(ptr, int) else ptr.value buf_len = w * h buf_type = ctype * buf_len buf = buf_type.from_address(addr) arr = np.ctypeslib.as_array(buf).reshape((h, w)) arr[:, :] = data def selector(n: int, f): # f can be VideoFrame or [VideoFrame]; ~> we take f[0] if list frame = f if isinstance(f, vs.VideoFrame) else f[0] # Read Y, U, V y = read_plane(frame, 0) u = read_plane(frame, 1) v = read_plane(frame, 2) # Apply method if method == 0: y2 = _process_plane(y, "clahe", 0) elif method == 1: y2 = _process_plane(y, "hist", 0) u = _process_plane(u, "hist", 0) v = _process_plane(v, "hist", 0) elif method == 2: y2 = _process_plane(y, "clahe", 0) u = _process_plane(u, "clahe", 0) v = _process_plane(v, "clahe", 0) elif method == 3: y1 = _process_plane(y, "clahe", 0) y3 = _process_plane(y, "hist", 0) y2 = ((y1 + y3) / 2).astype(dtype) elif method == 4: y2 = _process_plane(y, "scale", 0) else: # method == 5 y2 = _process_plane(y, "scale", 1) # Blend y_out = ((1 - strength)*y + strength*y2).astype(dtype) # Build new frame fout = frame.copy() write_plane(fout, 0, y_out) write_plane(fout, 1, u) write_plane(fout, 2, v) return fout # Use ModifyFrame (Selector returns VideoFrame) return core.std.ModifyFrame(clip=clip, clips=clip, selector=selector)

Which only works on Y.

Cu Selur