resume fixes, added tpe and cma params

- better tracking for optuna runs
- forge extras update to latest
- requirements hotfixes
- gamma and forensic scorer replaced by pca and hybridnoise, both recommended on solid background images to optimize towards less noise
- suppressing unnecessary debug mode prints

Author: Enferlain

conf/config.tmpl.yaml

@@ -134,9 +134,6 @@ optimizer:
 batch_size: 1 # Number of images to generate for EACH payload per iteration.
 save_imgs: True # Save all generated images to the run's 'imgs' folder.
 img_average_type: arithmetic # How to average scores within a batch: 'arithmetic', 'geometric', or 'quadratic'.
-background_check: # Settings for the background blackness scorer.
-  enabled: False # Set to true to enable the check. This scorer is useful for character-focused models.
-  payloads: [] # List of payload names (e.g., ["noob1", "noob2"]) to apply this specific check to.
 
 # --- Generator/aiohttp Settings ---
 generator_concurrency_limit: 10 # Max number of simultaneous API requests to the WebUI.
@@ -171,4 +168,19 @@ visualizations:
   convergence_plot: True # Generate a plot showing the score over iterations.
   # scatter_plot: False # (Not implemented)
   # unet_diagram: False # (Deprecated)
-  # heatmap: False # (Not implemented)
+  # heatmap: False # (Not implemented)
+
+# --- Scorer-Specific Settings ---
+# PCAScorer settings
+pcascorer_component: 1
+pcascorer_mode: 'projection'
+pcascorer_input_type: 'color'
+pcascorer_linearize: False
+pcascorer_invert: False
+pcascorer_enhancement: 'equalize'
+pcascorer_gamma: 1.0
+
+# HybridNoiseScorer settings
+hybridnoise_kernel_size: 3
+hybridnoise_noise_threshold: 20.0
+hybridnoise_color_tolerance: 30

requirements.txt

@@ -11,7 +11,7 @@ hydra-core               # Core Hydra library for configuration
 sd-mecha                 # Use the latest compatible version, or specify one explicitly like >=0.1.0 if known
 
 # --- Optimization Libraries ---
-bayesian-optimization    # Keep if you want to retain BayesOpt as an option
+bayesian-optimization==1.5.1  # Keep if you want to retain BayesOpt as an option
 optuna                   # ADDED: For Optuna optimizer support
 optuna-dashboard         # Realtime dashboard for optuna
 optuna-fast-fanova       # Recommended Optuna dependency
@@ -50,6 +50,10 @@ tensordict               # Appears related to PyTorch/distributed? Review if nee
 timm                     # Image models library, possibly used by a scorer? Review if needed.
 fairscale                # Distributed training/sharding library. Unlikely needed unless doing specific advanced things.
 # pynput                 # REMOVED: Was for old hotkey system, we'll use asyncio/other methods
+# needs descriptions
+geoopt
+rembg
+aesthetic-predictor-v2-5
 
 # --- Testing ---
 # pytest                   # Keep if you have tests or plan to add them

sd_optim.py

@@ -19,6 +19,12 @@
     format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
     datefmt='%Y-%m-%d %H:%M:%S'
 )
+
+# Suppress noisy third-party loggers - ADD THIS HERE
+logging.getLogger('choreographer').setLevel(logging.WARNING)
+logging.getLogger('kaleido').setLevel(logging.WARNING)
+logging.getLogger('plotly').setLevel(logging.WARNING)  # Just in case
+
 # Use a logger specific to this main script
 logger = logging.getLogger(__name__)  # Hydra often configures this further
 

sd_optim/generator.py

@@ -114,7 +114,8 @@ async def generate_swarm(
         try:
             # <<< USE provided session for getting Swarm session ID >>>
             session_id = await self.get_swarm_session(session)  # Pass session here
-            if not session_id: logger.error("Failed to get Swarm session ID."); return
+            if not session_id:
+                logger.error("Failed to get Swarm session ID."); return
 
             payload["session_id"] = session_id