diff options
Diffstat (limited to 'smart_photo_node.py')
| -rw-r--r-- | smart_photo_node.py | 62 |
1 files changed, 56 insertions, 6 deletions
diff --git a/smart_photo_node.py b/smart_photo_node.py index b7b57ae..f48e5d1 100644 --- a/smart_photo_node.py +++ b/smart_photo_node.py @@ -367,15 +367,26 @@ class AdaptivePhotoGrade: def _apply_detail(self, img: np.ndarray, mult: float, denoise: float) -> np.ndarray: """ - Clarity / structure boost via guided-filter edge-preserving decomposition. - Separates base (low-freq) from detail (high-freq), scales detail by mult, - optionally denoises the base layer via bilateral filter. + Clarity / structure boost via edge-preserving decomposition. + + Uses cv2.ximgproc.guidedFilter when opencv-contrib is available + (provides the best edge-preserving base layer separation). + Falls back to a bilateral filter base when ximgproc is absent. + + Separates base (low-freq) from detail (high-freq), scales detail by + mult, optionally denoises the base layer via bilateral filter. """ u8 = (img * 255).astype(np.uint8) - # Guided filter produces an edge-preserving smooth base layer - # eps controls smoothing strength (higher = more smoothing) - base = cv2.ximgproc.guidedFilter(u8, u8, radius=8, eps=int(0.01 * 255 ** 2)) + # Prefer guided filter (opencv-contrib); fall back to bilateral + try: + base = cv2.ximgproc.guidedFilter(u8, u8, radius=8, eps=int(0.01 * 255 ** 2)) + except AttributeError: + # opencv-contrib not installed — bilateral filter gives a similar + # edge-preserving smooth base at slightly lower quality + sigma = max(15, int(denoise * 75)) + base = cv2.bilateralFilter(u8, d=9, sigmaColor=sigma, sigmaSpace=sigma) + detail = u8.astype(np.float32) - base.astype(np.float32) # Optionally soften the base to reduce noise before adding detail back @@ -724,6 +735,41 @@ class WritePhotoMetadata: # --------------------------------------------------------------------------- +# CodeFormerRestore (stub) +# --------------------------------------------------------------------------- +class CodeFormerRestore: + """ + Passthrough stub for CodeFormer face restoration. + + The real implementation requires the comfyui-reactor-node or similar + custom node package. This stub passes the image through unchanged so + the rest of the pipeline (CLIP, grading, sky, depth) can be tested + without CodeFormer installed. + + TODO: replace with the real CodeFormer node once the package is + installed (e.g. via ComfyUI Manager or manual install of + github.com/Gourieff/comfyui-reactor-node). + """ + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "image": ("IMAGE",), + "fidelity": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.05}), + } + } + + RETURN_TYPES = ("IMAGE",) + FUNCTION = "restore" + CATEGORY = "image/smart" + + def restore(self, image, fidelity: float = 0.7): + print(f"[CodeFormerRestore] STUB — passing image through (fidelity={fidelity} ignored)") + return (image,) + + +# --------------------------------------------------------------------------- # ComfyUI node registration # --------------------------------------------------------------------------- NODE_CLASS_MAPPINGS = { @@ -733,6 +779,9 @@ NODE_CLASS_MAPPINGS = { "SkyEnhance": SkyEnhance, "DepthSelectiveSharpen": DepthSelectiveSharpen, "WritePhotoMetadata": WritePhotoMetadata, + # Stub registered last so the real node from another package takes priority + # if comfyui-reactor-node or similar is installed alongside this file. + "CodeFormerRestore": CodeFormerRestore, } NODE_DISPLAY_NAME_MAPPINGS = { @@ -742,4 +791,5 @@ NODE_DISPLAY_NAME_MAPPINGS = { "SkyEnhance": "Sky Enhance", "DepthSelectiveSharpen": "Depth Selective Sharpen", "WritePhotoMetadata": "Write Photo Metadata", + "CodeFormerRestore": "CodeFormer Restore (stub — install reactor-node for real impl)", } |