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Functions103 in github.com/Artificial-Sweetener/comfyui-WhiteRabbit

⨍ Functions 103◇ Types & classes 16
↓ 8 callersFunction_floor_mul
(x: int, k: int)
scaling.py:201
↓ 6 callersFunction_blur_nhwc
(x, sigma)
noise_control.py:52
↓ 6 callersMethodget
(self, key: Tuple)
post_process.py:170
↓ 4 callersFunction_get_rife_model
(ckpt_name: str)
interpolation.py:60
↓ 4 callersFunction_luma
(x)
noise_control.py:23
↓ 4 callersMethod_luma_linear
(x_lin)
interpolation.py:666
↓ 4 callersFunction_to_lin
(x)
noise_control.py:11
↓ 3 callersFunction_dilate
(mask01, r)
noise_control.py:98
↓ 3 callersMethod_dist
(self, A, B, kind="MSE")
interpolation.py:1008
↓ 3 callersFunction_divisible_box
(w: int, h: int, d: int)
scaling.py:385
↓ 3 callersFunction_fit_keep_aspect
(sw: int, sh: int, tw: int, th: int)
scaling.py:214
↓ 3 callersMethod_luma
(self, x_nchw)
video_loop.py:366
↓ 3 callersFunction_prep_frames
(frames: torch.Tensor)
interpolation.py:82
↓ 3 callersFunction_progress
(total_ticks: int)
interpolation.py:89
↓ 3 callersFunction_scale_list
(scale_factor: float)
interpolation.py:77
↓ 3 callersFunction_sobel_mag
(y)
noise_control.py:27
↓ 3 callersMethod_to_nchw
(self, x)
interpolation.py:1003
↓ 2 callersFunction_avgpool_tiles
(x1, tile)
noise_control.py:69
↓ 2 callersFunction_bhwc_to_nchw
(x: torch.Tensor)
post_process.py:31
↓ 2 callersFunction_ceil_mul
(x: int, k: int)
scaling.py:207
↓ 2 callersFunction_count_synth
(frames: torch.Tensor, multiplier: int)
interpolation.py:93
↓ 2 callersMethod_dist
(self, A, B, kind="L1")
video_loop.py:361
↓ 2 callersMethod_downsample
(self, x, s)
video_loop.py:351
↓ 2 callersFunction_mad_tiles
(x1, tile)
noise_control.py:75
↓ 2 callersFunction_make_rife_callback
()
interpolation.py:99
↓ 2 callersFunction_resize_lanczos
(img01, H, W)
noise_control.py:107
↓ 2 callersMethod_ssim_multiscale_batched
(self, x, y, scales)
video_loop.py:406
↓ 2 callersMethod_to_nchw
(self, x)
video_loop.py:330
↓ 2 callersFunction_to_srgb
(x)
noise_control.py:17
↓ 2 callersFunction_with_progress
(cb, pbar)
interpolation.py:112
↓ 1 callersMethod_adjacent_deltas
(self, clip_nchw, kind="MSE")
interpolation.py:1013
↓ 1 callersFunction_chunk_spans
(n: int, max_bs: int)
scaling.py:190
↓ 1 callersFunction_chunk_spans
(n: int, cap: int)
post_process.py:19
↓ 1 callersFunction_cover_keep_aspect
(sw: int, sh: int, tw: int, th: int)
scaling.py:300
↓ 1 callersFunction_crop_offsets
( pos: str, in_w: int, in_h: int, out_w: int, out_h: int )
scaling.py:321
↓ 1 callersMethod_dilate_mask_nhwc
(mask01, radius)
interpolation.py:689
↓ 1 callersMethod_exposure_match_ab
(out_lin, tgt_lin, a_cap, b_cap)
interpolation.py:673
↓ 1 callersFunction_fit_keep_ar_divisible
( sw: int, sh: int, tw: int, th: int, d: int )
scaling.py:226
↓ 1 callersMethod_flow_mag_mean
Mean optical-flow magnitude. Accepts NHWC with/without batch, RGB/RGBA/Gray. Soft-fails to 0.0 if OpenCV unavailable.
video_loop.py:498
↓ 1 callersFunction_gauss1d
(sigma, r)
noise_control.py:44
↓ 1 callersMethod_gaussian_kernel1d
(sigma, radius)
interpolation.py:625
↓ 1 callersMethod_gaussian_window
(self, C, k=7, sigma=1.5, device="cpu", dtype=None)
video_loop.py:374
↓ 1 callersFunction_load_rgba_from_path
Load an image from disk as RGBA in [0,1] and return (4,H,W) on the target device. No rotation or other processing happens here.
post_process.py:62
↓ 1 callersMethod_map_t
( self, t_scalar, t_mode, t_gamma, t_min, t_max, custom_sorted, m_effective )
interpolation.py:359
↓ 1 callersFunction_nchw_to_bhwc
(x: torch.Tensor)
post_process.py:35
↓ 1 callersFunction_nearest_interp
(x: torch.Tensor, size: Tuple[int, int])
scaling.py:378
↓ 1 callersFunction_normalize_mode
(mode: str)
scaling.py:391
↓ 1 callersFunction_pad_sides
(pos: str, pad_w: int, pad_h: int)
scaling.py:305
↓ 1 callersFunction_parse_pad_color
( s: str, c: int, device: torch.device, dtype: torch.dtype )
scaling.py:357
↓ 1 callersMethod_parse_scales
(self, csv)
video_loop.py:337
↓ 1 callersFunction_position_xy
( position: str, base_w: int, base_h: int, wm_w: int, wm_h: int, pad_x: int, pad_y
post_process.py:130
↓ 1 callersMethod_precompute_adjacent_metrics
Returns dict with vectors of length (B-1): D_adj (torch), S_adj (torch), E_adj (torch), F_adj (np, CPU) All torch tensors a
video_loop.py:414
↓ 1 callersMethod_precompute_seam_tables
For k = 0..W-1, precompute per-frame metrics vs first+k: D_to_firstk[k] : (B,) distances to frame k S_to_firstk[k] : (B,)
video_loop.py:468
↓ 1 callersFunction_rotate_bicubic_expand
x: (N,C,H,W). Rotate around center with bicubic sampling and EXPAND canvas (PIL-like `expand=True`). Parts outside input are zero/transparent
post_process.py:77
↓ 1 callersFunction_scale_then_crop_divisible
AR Scale + Divisible Crop: 1) Scale once (keep AR), locking the SOURCE long side to floor(requested_long/d)*d (>0). 2) Crop ONLY the
scaling.py:241
↓ 1 callersMethod_ssim_pair_batched
(self, x, y, k=7, sigma=1.5, C1=0.01**2, C2=0.03**2)
video_loop.py:389
↓ 1 callersFunction_upsample_mask
(mask_tile, H, W, mode="nearest")
noise_control.py:87
↓ 1 callersMethodanalyze
( self, full_clip, multiplier, use_first_two, use_last_two, us
interpolation.py:1039
↓ 1 callersMethodroll
(self, images, offset)
video_loop.py:93
MethodINPUT_TYPES
(cls)
scaling.py:28
MethodINPUT_TYPES
(cls)
scaling.py:410
MethodINPUT_TYPES
(s)
interpolation.py:134
MethodINPUT_TYPES
(s)
interpolation.py:248
MethodINPUT_TYPES
(cls)
interpolation.py:447
MethodINPUT_TYPES
(s)
interpolation.py:880
MethodINPUT_TYPES
(cls)
video_loop.py:11
MethodINPUT_TYPES
(cls)
video_loop.py:39
MethodINPUT_TYPES
(cls)
video_loop.py:71
MethodINPUT_TYPES
(cls)
video_loop.py:108
MethodINPUT_TYPES
(cls)
video_loop.py:170
MethodINPUT_TYPES
(cls)
video_loop.py:802
MethodINPUT_TYPES
(cls)
noise_control.py:116
MethodINPUT_TYPES
(cls)
noise_control.py:449
MethodINPUT_TYPES
(cls)
post_process.py:196
Method__init__
(self, capacity: int = 6)
post_process.py:166
Method_adv_t_mapper
(t_scalar: float)
interpolation.py:411
Function_cb
(frame_0, frame_1, timestep, model, scale_list, ensemble, t_mapper)
interpolation.py:100
Function_ensure_rgba_nchw
wm: (1,H,W,C) in [0,1] → return (4,H,W) float C may be 1,3,4; synthesize alpha=1 if missing.
post_process.py:39
Method_gaussian_blur_nhwc
(x, sigma)
interpolation.py:638
Method_linear_to_srgb
(x)
interpolation.py:617
Method_srgb_to_linear
(x)
interpolation.py:609
Function_wrapped
(*args, **kwargs)
interpolation.py:116
Method_write
(idx: int, frame_nhwc_cpu: torch.Tensor)
interpolation.py:780
Methodanalyze_wrapper
Safe entrypoint for Comfy mapping: - If 'multiplier' is omitted: default to 0 (passthrough). - If 'multiplier' is invalid/neg
interpolation.py:1020
Methodapply
( self, image: torch.Tensor, watermark: str, position: str, scale: int
post_process.py:330
Methodapply_hold
( self, frames, ref_source="external", ref_index=0, reference=None,
noise_control.py:305
Methodassemble
(self, original_images, interpolated_frames)
video_loop.py:60
Methodclean
( self, frames, linearize=True, detector="blackhat", radius=5,
noise_control.py:618
Methodcrop
(self, clip_frames, trim_start_frames, trim_end_frames)
video_loop.py:832
Methodfind_and_crop
( self, clip_frames, max_end_crop_frames, include_first_step, include_
video_loop.py:556
Methodprepare
(self, images)
video_loop.py:28
Methodprocess
( self, image: torch.Tensor, width: int, height: int, resize_mode: str
scaling.py:554
Methodput
(self, key: Tuple, value)
post_process.py:176
Methodresample
( self, ckpt_name, fps_in, fps_out, frames, scale_factor=1.0,
interpolation.py:698
Methodspans
(n, cap)
scaling.py:93
Methodsynth
(i: int, t_local: float)
interpolation.py:761
Methodsynth_at
(t_scalar: float)
interpolation.py:1136
Methodto_gray
(x: np.ndarray)
video_loop.py:516
Methodto_nchw_on_device
(idx: int)
interpolation.py:750
Methodunroll
(self, images, base_offset, m)
video_loop.py:143
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