added upscaler

app/upscaler/realesrgan.py

@@ -1 +1,55 @@
-"""Auto-generated placeholder module for Stable Diffusion Image Generator."""
+"""NCNN RealESRGAN upscaler wrapper.
+
+This module exposes:
+- NCNNUpscaler: provides lightweight 2x/4x super-resolution via realesrgan-ncnn-py.
+"""
+
+from __future__ import annotations
+
+from PIL import Image
+from realesrgan_ncnn_py import Realesrgan
+
+from app.utils.logger import get_logger
+
+logger = get_logger(__name__)
+
+# Supported scales mapped to internal model indices
+SCALE_TO_MODEL = {
+    2.0: 3,  # realesrgan-x2plus
+    4.0: 0,  # realesrgan-x4plus
+}
+
+
+class NCNNUpscaler:
+    """Lightweight NCNN RealESRGAN engine using realesrgan-ncnn-py.
+
+    Args:
+        scale (float): Supported values = 2.0 or 4.0.
+    """
+
+    def __init__(self, scale: float = 2.0):
+        """Initialize the NCNN upscaler."""
+        if scale not in SCALE_TO_MODEL:
+            raise ValueError("Only 2.0x and 4.0x supported for your NCNN build")
+
+        self.scale = scale
+        self.model_index = SCALE_TO_MODEL[scale]
+
+        logger.info(
+            f"[NCNN] Loading RealESRGAN model index={self.model_index} \
+            for scale={scale}x"
+        )
+
+        self.model = Realesrgan(model=self.model_index)
+
+    def upscale(self, image: Image.Image) -> Image.Image:
+        """Upscale a PIL image using NCNN RealESRGAN."""
+        if not isinstance(image, Image.Image):
+            raise TypeError("Input must be a PIL.Image")
+
+        logger.info(
+            f"[NCNN] Upscaling ({image.width}x{image.height}) "
+            f"by {self.scale}x using model={self.model_index}"
+        )
+
+        return self.model.process_pil(image)

app/upscaler/upscaler.py

@@ -0,0 +1,39 @@
+"""Unified upscaler interface.
+
+Chooses between:
+- NCNN RealESRGAN (fastest, works on NVIDIA/AMD/Intel)
+- Future SD-upscaler backend
+"""
+
+from __future__ import annotations
+
+from PIL import Image
+
+from app.upscaler.realesrgan import NCNNUpscaler
+from app.utils.logger import get_logger
+
+logger = get_logger(__name__)
+
+
+class Upscaler:
+    """Unified high-level upscaling wrapper."""
+
+    def __init__(self, scale: float = 2.0, prefer: str = "ncnn"):
+        """Initialize the upscaler with given backend preference."""
+        logger.info(f"Upscaler initializing (prefer={prefer}, scale={scale})")
+
+        self.engine = None
+
+        if prefer in ("ncnn", "auto"):
+            try:
+                self.engine = NCNNUpscaler(scale=scale)
+                logger.info("Using NCNN RealESRGAN engine.")
+                return
+            except Exception as err:
+                logger.warning(f"NCNN RealESRGAN init failed: {err}")
+
+        raise RuntimeError("No valid upscaler engine available.")
+
+    def upscale(self, image: Image.Image) -> Image.Image:
+        """Upscale the given image."""
+        return self.engine.upscale(image)

init_structure.py

@@ -1,94 +0,0 @@
-"""
-Project Structure Generator for Stable Diffusion Image Generator.
-
-Creates all required directories and placeholder files with compliant
-docstrings. Safe for repeated runs — will not overwrite existing files.
-"""
-
-import os
-
-# Placeholder docstrings
-MODULE_PLACEHOLDER = '"""Auto-generated placeholder module for Stable Diffusion Image Generator."""\n'
-INIT_PLACEHOLDER = '"""Package initialization file for Stable Diffusion Image Generator."""\n'
-
-
-# Utility functions
-def create_dir(path: str):
-    """Create directory if it doesn't already exist."""
-    os.makedirs(path, exist_ok=True)
-
-
-def create_file(path: str, content: str = MODULE_PLACEHOLDER):
-    """Create a file only if it does not already exist."""
-    if not os.path.exists(path):
-        with open(path, "w") as f:
-            f.write(content)
-
-
-def init_file(path: str):
-    """Create an __init__.py with a placeholder docstring."""
-    if not os.path.exists(path):
-        with open(path, "w") as f:
-            f.write(INIT_PLACEHOLDER)
-
-
-# Project Directory Structure
-
-directories = [
-    "app",
-    "app/core",
-    "app/models",
-    "app/utils",
-    "app/presets",
-    "app/upscaler",
-    "assets",
-    "assets/samples",
-    "assets/lora",
-]
-
-
-# File Definitions
-
-files = {
-    # Entry
-    "main.py": MODULE_PLACEHOLDER,
-
-    # Core pipeline + generation modules
-    "app/pipeline.py": MODULE_PLACEHOLDER,
-    "app/generator.py": MODULE_PLACEHOLDER,
-    "app/img2img.py": MODULE_PLACEHOLDER,
-
-    # UI
-    "app/ui.py": MODULE_PLACEHOLDER,
-
-    # Presets
-    "app/presets/styles.py": MODULE_PLACEHOLDER,
-
-    # Upscaler
-    "app/upscaler/realesrgan.py": MODULE_PLACEHOLDER,
-
-    # Utils
-    "app/utils/history.py": MODULE_PLACEHOLDER,
-    "app/utils/seed.py": MODULE_PLACEHOLDER,
-    "app/utils/logger.py": MODULE_PLACEHOLDER,
-
-    # Models or reference files
-    "app/models/metadata.py": MODULE_PLACEHOLDER,
-
-    # Root files
-    "requirements.txt": MODULE_PLACEHOLDER,
-    "README.md": MODULE_PLACEHOLDER,
-    "LICENSE": MODULE_PLACEHOLDER,
-}
-
-
-# Build the structure
-
-for d in directories:
-    create_dir(d)
-    init_file(os.path.join(d, "__init__.py"))
-
-for path, content in files.items():
-    create_file(path, content)
-
-print("Stable Diffusion Image Generator project structure created successfully!")

requirements.txt

@@ -8,9 +8,9 @@ torchaudio==2.5.1
 
 
 # HUGGINGFACE DIFFUSION ECOSYSTEM
-huggingface_hub==0.20.3
-diffusers==0.26.3
-transformers==4.39.3
+diffusers==0.29.2
+transformers==4.39.3    
+huggingface_hub==0.29.1 
 accelerate==0.28.0
 safetensors==0.4.2
 
@@ -29,13 +29,10 @@ python-dotenv==1.0.1
 
 
 # UPSCALING / SUPER-RESOLUTION
-realesrgan==0.3.0
-basicsr==1.4.2
-facexlib==0.3.0
-gfpgan==1.3.8
+realesrgan-ncnn-py==2.0.0
 
 
-# DEV TOOLS
+# DEVELOPMENT TOOLS
 black==24.3.0
 ruff==0.3.5
 pre-commit==3.7.0