feat: promote cond_noise_scale to UI for controlling conditioning noise level helping mitigate noise artifacts in high-res upscaling

inference_cli.py

@@ -335,7 +335,8 @@ def _worker_process(proc_idx, device_id, frames_np, shared_args, return_queue):
         debug=worker_debug,
         progress_callback=None,
         cfg_scale=shared_args["cfg_scale"],
-        seed=shared_args["seed"]
+        seed=shared_args["seed"],
+        cond_noise_scale=shared_args["cond_noise_scale"]
     )
 
     # Phase 3: Decode all batches
@@ -388,6 +389,7 @@ def _gpu_processing(frames_tensor, device_list, args):
         "model_dir": args.model_dir if args.model_dir is not None else "./models/SEEDVR2",
         "preserve_vram": args.preserve_vram,
         "color_correction": args.color_correction,
+        "cond_noise_scale": args.cond_noise_scale,
         "debug": args.debug,
         "cfg_scale": 1.0,
         "seed": args.seed,
@@ -512,6 +514,8 @@ def parse_arguments():
     parser.add_argument("--color_correction", type=str, default="wavelet", 
                         choices=["wavelet", "adain", "none"],
                         help="Color correction method: 'wavelet' (natural, recommended), 'adain' (stylistic), 'none' (no correction)")
+    parser.add_argument("--cond_noise_scale", type=float, default=0.0,
+                        help="Conditional noise scale (0.0-1.0). Higher values add more noise, affecting sharpness (default: 0.0)")
     parser.add_argument("--preserve_vram", action="store_true",
                         help="Enable VRAM preservation mode")
     parser.add_argument("--debug", action="store_true",

src/core/generation.py

@@ -528,7 +528,7 @@ def encode_all_batches(runner, ctx=None, images=None, batch_size=90, preserve_vr
 
 
 def upscale_all_batches(runner, ctx=None, preserve_vram=False, debug=None, 
-                       progress_callback=None, cfg_scale=1.0, seed=100):
+                       progress_callback=None, cfg_scale=1.0, seed=100, cond_noise_scale=0.0):
     """
     Phase 2: DiT Upscaling for all encoded batches.
     
@@ -543,6 +543,8 @@ def upscale_all_batches(runner, ctx=None, preserve_vram=False, debug=None,
         progress_callback: Optional callback(current, total, frames, phase_name)
         cfg_scale: Classifier-free guidance scale (default: 1.0)
         seed: Random seed for noise generation
+        cond_noise_scale: Conditional noise scale for latent augmentation (0.0-1.0).
+            Controls the amount of noise added to the conditioning latent.
         
     Returns:
         dict: Updated context containing:
@@ -584,8 +586,6 @@ def upscale_all_batches(runner, ctx=None, preserve_vram=False, debug=None,
     # Set seed for generation
     set_seed(seed)
     
-    cond_noise_scale = 0.0
-    
     # Count valid latents
     num_valid_latents = len([l for l in ctx['all_latents'] if l is not None])
 

src/interfaces/comfyui_node.py

@@ -94,6 +94,13 @@ class SeedVR2:
                     "default": "wavelet",
                     "tooltip": "Color correction method. Wavelet: Frequency-based for natural results (recommended). AdaIN: Statistical matching for stylized effects. None: No color correction."
                 }),
+                "cond_noise_scale": ("FLOAT", {
+                    "default": 0.0,
+                    "min": 0.0,
+                    "max": 1.0,
+                    "step": 0.05,
+                    "tooltip": "Conditional noise scale for latent augmentation. Higher values add more noise to the conditioning, affecting sharpness and detail. 0.0 = no noise (crisp), 1.0 = maximum noise (softer)."
+                }),
             },
             "optional": {
                 "block_swap_config": ("block_swap_config", {
@@ -112,7 +119,8 @@ class SeedVR2:
     CATEGORY = "SEEDVR2"
 
     def execute(self, images: torch.Tensor, model: str, seed: int, new_resolution: int, 
-        batch_size: int, color_correction=str, block_swap_config=None, extra_args=None) -> Tuple[torch.Tensor]:
+        batch_size: int, color_correction: str, cond_noise_scale: float, 
+        block_swap_config=None, extra_args=None) -> Tuple[torch.Tensor]:
         """Execute SeedVR2 video upscaling with progress reporting"""
         
         temporal_overlap = 0 
@@ -155,7 +163,8 @@ class SeedVR2:
         cfg_scale = 1.0
         try:
             return self._internal_execute(images, model, seed, new_resolution, cfg_scale, 
-                                        batch_size, color_correction, tiled_vae, vae_tile_size, vae_tile_overlap, 
+                                        batch_size, color_correction, cond_noise_scale, 
+                                        tiled_vae, vae_tile_size, vae_tile_overlap, 
                                         preserve_vram, temporal_overlap, 
                                         cache_model, device, block_swap_config)
         except Exception as e:
@@ -198,7 +207,7 @@ class SeedVR2:
 
 
     def _internal_execute(self, images, model, seed, new_resolution, cfg_scale, batch_size, 
-                 color_correction, tiled_vae, vae_tile_size, vae_tile_overlap,
+                 color_correction, cond_noise_scale, tiled_vae, vae_tile_size, vae_tile_overlap,
                  preserve_vram, temporal_overlap, cache_model, device, block_swap_config):
         """Internal execution logic with progress tracking"""
         
@@ -278,7 +287,8 @@ class SeedVR2:
             debug=debug, 
             progress_callback=self._progress_callback, 
             cfg_scale=cfg_scale, 
-            seed=seed
+            seed=seed,
+            cond_noise_scale=cond_noise_scale
         )
 
         # Phase 3: Decode all batches