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comrender
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from .imagen_gemini import ImagenGemini
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NODE_CLASS_MAPPINGS = {
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"ImagenGemini": ImagenGemini
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"ImagenGemini": "Imagen Gemini"
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}
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__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']
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import os
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import torch
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import requests
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import base64
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import numpy as np
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import json
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from io import BytesIO
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from PIL import Image
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# --- Helper Functions ---
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def pil2tensor(pil_image):
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"""Convert PIL Image (RGB) back to ComfyUI tensor (B=1, H, W, C)"""
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if pil_image is None:
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return None
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arr = np.array(pil_image).astype(np.float32) / 255.0
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arr = arr[np.newaxis, ...]
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return torch.from_numpy(arr)
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class ImagenGemini:
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"""
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ComfyUI Node for Google Imagen 4 & 3 (Ultra, Standard, Fast).
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Supports specific resolution (1K/2K) and aspect ratios.
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"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"prompt": ("STRING", {"default": "A futuristic city with flying cars, cinematic lighting", "multiline": True}),
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"model": ([
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# Imagen 4 (Preview/Latest)
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"imagen-4.0-ultra-generate-001",
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"imagen-4.0-generate-001",
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"imagen-4.0-fast-generate-001",
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# Imagen 3 (Stable/Current)
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"imagen-3.0-generate-002",
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"imagen-3.0-fast-generate-001",
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"imagen-3.0-generate-001",
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], {"default": "imagen-4.0-generate-001"}),
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"gemini_api_key": ("STRING", {"default": "", "multiline": False}),
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"aspect_ratio": ([
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"1:1", "3:4", "4:3", "9:16", "16:9"
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], {"default": "1:1"}),
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"resolution": (["1K", "2K"], {"default": "1K"}),
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"num_images": ("INT", {"default": 1, "min": 1, "max": 4, "step": 1}),
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"person_generation": (["allow_adult", "dont_allow", "allow_all"], {"default": "allow_adult"}),
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}
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}
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RETURN_TYPES = ("IMAGE", "STRING")
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RETURN_NAMES = ("images", "guidance")
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FUNCTION = "process"
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CATEGORY = "ImagenGemini"
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OUTPUT_NODE = True
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def process(self, prompt, model, gemini_api_key, person_generation="allow_adult", aspect_ratio="1:1", resolution="1K", num_images=1):
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# 1. Credential Check
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if not gemini_api_key or gemini_api_key.strip() == "":
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gemini_api_key = os.environ.get("GEMINI_API_KEY")
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if not gemini_api_key or gemini_api_key.strip() == "":
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raise ValueError("Please provide a valid Google Gemini API Key via the UI or the GEMINI_API_KEY environment variable.")
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# 2. Configure API Payload
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parameters = {
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"sampleCount": num_images,
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"aspectRatio": aspect_ratio,
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"sampleImageSize": resolution,
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"personGeneration": person_generation
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}
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payload = {
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"instances": [
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{ "prompt": prompt }
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],
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"parameters": parameters
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}
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# 3. Request
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url = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:predict?key={gemini_api_key}"
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headers = {"Content-Type": "application/json"}
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try:
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response = requests.post(url, headers=headers, json=payload, timeout=120)
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response.raise_for_status()
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result = response.json()
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except Exception as e:
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print(f"Imagen API Request Failed: {e}")
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if hasattr(e, 'response') and e.response is not None:
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raise ValueError(f"API Error: {e.response.text}")
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raise ValueError(f"API Request failed: {str(e)}")
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# 4. Parse Response
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predictions = result.get("predictions", [])
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if not predictions:
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raise ValueError(f"No images returned. API Response: {json.dumps(result, indent=2)}")
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output_tensors = []
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for pred in predictions:
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b64_data = pred.get("bytesBase64Encoded")
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if b64_data:
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try:
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img_data = base64.b64decode(b64_data)
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pil_img = Image.open(BytesIO(img_data)).convert("RGB")
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tensor_out = pil2tensor(pil_img)
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output_tensors.append(tensor_out)
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except Exception as e:
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print(f"Error decoding image: {e}")
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if not output_tensors:
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raise ValueError("Failed to decode any images from the response.")
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# 5. Stack Batch
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result_batch = torch.cat(output_tensors, dim=0)
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# 6. Guidance Output
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guidance_text = """# Imagen 4 Prompting Guidance
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## Imagen 4 Prompt Writing Basics
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A good prompt is descriptive, clear, and uses meaningful keywords. Limit prompts to **480 tokens**.
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* **Subject**: Define the core object, person, animal, or scenery.
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* **Context and background**: Place the subject in a specific environment (e.g., "a studio with a white background," "outdoors").
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* **Style**: Specify the artistic style (e.g., "oil painting," "sketch," "isometric 3D," "photorealistic").
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**Iterative prompting** is key: start with a core idea and refine by adding details until the image matches your vision.
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## Key Prompt Elements
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* **Use descriptive language**: Employ detailed adjectives and adverbs.
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* **Provide context**: Include background info to aid understanding.
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* **Reference specific artists or styles**: Mention specific aesthetics or movements (e.g., "Impressionism").
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* **Enhancing facial details**: Explicitly focus on faces (e.g., use "portrait").
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## Generating Text in Images
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Imagen 4 can render text within images.
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* **Iterate with confidence**: You may need multiple attempts for the best text integration.
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* **Keep it short**: Limit text strings to **25 characters or less** for optimal results.
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* **Multiple phrases**: Use 2–3 distinct phrases max; do not exceed this for cleaner compositions.
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* **Guide Placement**: The model attempts to follow positioning directions, though variations occur.
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* **Inspire font style**: Specify general styles (e.g., "bold font," "handwritten") rather than exact typefaces.
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* **Font size**: Use general size indicators like "small," "medium," or "large."
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## Advanced Techniques: Photography Modifiers
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To generate photorealistic images, start your prompt with **"A photo of..."** and use specific terminology from the categories below to control the look and feel.
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### 1. Shot Types & Framing
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Control how much of the subject is visible.
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* **Extreme Close-Up**: Focuses on a specific detail (e.g., "an eye," "texture of a leaf").
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* **Close-Up**: Frames the head and shoulders; captures facial expressions.
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* **Medium Shot**: Waist-up; good for interactions or dialogue scenes.
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* **Cowboy Shot (American Shot)**: Framed from mid-thigh up; classic for confident stances.
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* **Full Shot**: Captures the subject's entire body from head to toe.
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* **Wide Shot / Long Shot**: Shows the subject within their environment.
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* **Establishing Shot**: Very wide view designed to show the setting or location.
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### 2. Camera Angles
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Control the viewer's perspective relative to the subject.
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* **Eye-Level**: Neutral, natural perspective; connects directly with the subject.
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* **Low Angle**: Camera looks up at the subject; makes them look powerful, dominant, or large.
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* **High Angle**: Camera looks down; makes the subject look vulnerable or small.
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* **Bird’s-Eye View / Overhead**: Directly from above (90 degrees); creates a geometric or map-like layout.
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* **Worm’s-Eye View**: From the ground looking straight up; emphasizes height and scale.
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* **Dutch Angle / Canted Angle**: Tilted camera horizon; creates tension, disorientation, or dynamism.
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* **Over-the-Shoulder**: View from behind a subject, looking at what they are seeing or facing.
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### 3. Lighting Styles & Atmosphere
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Lighting defines the mood and depth of the image.
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* **Golden Hour**: Warm, soft, orange glow just after sunrise or before sunset.
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* **Blue Hour**: Cool, deep blue tones just before sunrise or after sunset.
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* **Rembrandt Lighting**: Dramatic portrait lighting characterized by a triangular highlight on the shadowed cheek.
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* **Butterfly Lighting**: Glamour lighting with a butterfly-shaped shadow under the nose; high placement.
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* **Rim Lighting / Backlighting**: Light source behind the subject; creates a glowing outline or silhouette.
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* **Chiaroscuro**: Strong contrast between light and dark; moody and dramatic.
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* **High-Key**: Bright, evenly lit, minimal shadows; optimistic and clean.
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* **Low-Key**: Dark, predominant shadows, selective lighting; mysterious and intense.
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* **Volumetric Lighting / God Rays**: Visible beams of light cutting through atmosphere (fog, dust, smoke).
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### 4. Photographic Styles & Genres
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Define the "intent" of the photograph.
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* **Candid Shot**: Unposed, natural, capturing a genuine moment unaware of the camera.
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* **Street Photography**: Gritty, urban, capturing everyday life and society.
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* **Editorial / Fashion**: Stylish, high-end, posed, focused on clothing or beauty (often "studio lighting").
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* **Macro Photography**: Extreme magnification of small subjects (insects, droplets).
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* **Tilt-Shift**: Miniature effect; blurs top and bottom to make real scenes look like toys.
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* **Double Exposure**: Superimposing two images (e.g., "silhouette of a person combined with a forest").
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* **Long Exposure**: Blurs moving elements (e.g., "silky water," "light trails" from cars).
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### 5. Camera Settings & Optics
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Simulate specific lens and camera behaviors.
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* **Bokeh / Shallow Depth of Field**: Sharp subject, blurry background; isolates the subject.
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* **Deep Depth of Field**: Everything in focus from foreground to background (common in landscapes).
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* **Motion Blur**: Background or subject streaking to convey speed.
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* **Fisheye Lens**: Ultra-wide, distorted spherical view (180 degrees).
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* **Telephoto Lens**: Compresses distance; makes background elements look closer and larger.
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* **Wide Angle**: Expands the view; exaggerates perspective (objects near lens look huge).
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### 6. Film Stocks & Vintage Aesthetics
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Mimic specific analog looks.
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* **Kodachrome**: Vivid, rich colors, high contrast (classic mid-century look).
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* **Polaroid / Instant Film**: Soft focus, specific color casts, white borders.
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* **Sepia**: Brownish tone; implies history or "Old West."
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* **Monochrome / Black and White**: Focuses on texture and contrast; timeless.
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* **Cyanotype**: Blueprint-like, deep monochromatic blue.
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* **Daguerreotype**: Metallic, antique, high-detail, eerie vintage portraiture.
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## Art & Material Modifiers
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* **Shapes and materials**: Define unique compositions (e.g., "an armchair made of paper," "neon tubes in the shape of a bird").
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* **Historical art references**: Use **"in the style of [Movement]"** (e.g., "Renaissance," "Pop Art," "Surrealism").
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* **Image quality modifiers**: Use keywords like **"high-quality," "4K," "HDR," "studio photo,"** or **"by a professional"** to boost aesthetic quality.
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## Prompt Parameterization
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For dynamic applications, use placeholders in your prompt structure (e.g., `A {logo_style} logo for a {company_name}`)."""
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return (result_batch, guidance_text)
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