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import json
import io
import random
from PIL import Image
from generate import *
from typing import Dict, Any
def display_image(image_bytes):
image = Image.open(io.BytesIO(image_bytes))
return image
def process_optional_params(**kwargs) -> Dict[str, Any]:
return {k: v for k, v in kwargs.items() if v is not None}
def process_images(primary=None, secondary=None, validate=True) -> Dict[str, str]:
if validate and primary is None:
raise ValueError("Primary image is required.")
result = {}
if primary:
result["image"] = process_and_encode_image(primary)
if secondary:
result["maskImage"] = process_and_encode_image(secondary)
return result
def create_image_generation_config(height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
return {
"numberOfImages": 1,
"height": height,
"width": width,
"quality": quality,
"cfgScale": cfg_scale,
"seed": seed
}
def build_request(task_type, params, height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
param_dict = {"TEXT_IMAGE": "textToImageParams", "INPAINTING": "inPaintingParams",
"OUTPAINTING":"outPaintingParams","IMAGE_VARIATION":"imageVariationParams",
"COLOR_GUIDED_GENERATION":"colorGuidedGenerationParams","BACKGROUND_REMOVAL":"backgroundRemovalParams"}
return json.dumps({
"taskType": task_type,
param_dict[task_type]: params,
"imageGenerationConfig": create_image_generation_config(
height=height,
width=width,
quality=quality,
cfg_scale=cfg_scale,
seed=seed
)
})
def text_to_image(prompt, negative_text=None, height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
text_to_image_params = {"text": prompt,
**({"negativeText": negative_text} if negative_text not in [None, ""] else {})
}
body = build_request("TEXT_IMAGE", text_to_image_params, height, width, quality, cfg_scale, seed)
image_bytes = generate_image(body)
return display_image(image_bytes)
def inpainting(image, mask_prompt=None, mask_image=None, text=None, negative_text=None, height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
images = process_images(primary=image, secondary=None)
# Prepare the inPaintingParams dictionary
if mask_prompt and mask_image:
raise ValueError("You must specify either maskPrompt or maskImage, but not both.")
if not mask_prompt and not mask_image:
raise ValueError("You must specify either maskPrompt or maskImage.")
# Prepare the inPaintingParams dictionary with the appropriate mask parameter
in_painting_params = {
**images, # Unpacks image and maskImage if present
**({"maskPrompt": mask_prompt} if mask_prompt not in [None, ""] else {}),
**({"text": text} if text not in [None, ""] else {}),
**({"negativeText": negative_text} if negative_text not in [None, ""] else {})
}
body = build_request("INPAINTING", in_painting_params, height, width, quality, cfg_scale, seed)
return display_image(generate_image(body))
def outpainting(image, mask_prompt=None, mask_image=None, text=None, negative_text=None, outpainting_mode="DEFAULT", height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
images = process_images(primary=image, secondary=None)
if mask_prompt and mask_image:
raise ValueError("You must specify either maskPrompt or maskImage, but not both.")
if not mask_prompt and not mask_image:
raise ValueError("You must specify either maskPrompt or maskImage.")
# Prepare the outPaintingParams dictionary
out_painting_params = {
**images, # Unpacks image and maskImage if present
**process_optional_params(
**({"maskPrompt": mask_prompt} if mask_prompt not in [None, ""] else {}),
**({"text": text} if text not in [None, ""] else {}),
**({"negativeText": negative_text} if negative_text not in [None, ""] else {})
)
}
body = build_request("OUTPAINTING", out_painting_params, height, width, quality, cfg_scale, seed)
return display_image(generate_image(body))
def image_variation(images, text=None, negative_text=None, similarity_strength=0.5, height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
encoded_images = []
for image_path in images:
with open(image_path, "rb") as image_file:
encoded_images.append(process_and_encode_image(image_file))
# Prepare the imageVariationParams dictionary
image_variation_params = {
"images": encoded_images,
**({"text": text} if text not in [None, ""] else {}),
**({"negativeText": negative_text} if negative_text not in [None, ""] else {})
}
body = build_request("IMAGE_VARIATION", image_variation_params, height, width, quality, cfg_scale, seed)
return display_image(generate_image(body))
def image_conditioning(condition_image, text, negative_text=None, control_mode="CANNY_EDGE", control_strength=0.7, height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
condition_image_encoded = process_images(primary=condition_image)
# Prepare the textToImageParams dictionary
text_to_image_params = {
"text": text,
"controlMode": control_mode,
"controlStrength": control_strength,
**condition_image_encoded,
**({"negativeText": negative_text} if negative_text not in [None, ""] else {})
}
body = build_request("TEXT_IMAGE", text_to_image_params, height, width, quality, cfg_scale, seed)
return display_image(generate_image(body))
def color_guided_content(text=None, reference_image=None, negative_text=None, colors=None, height=1024, width=1024, quality="standard", cfg_scale=8.0, seed=0):
# Encode the reference image if provided
reference_image_encoded = process_images(primary=reference_image)
if not colors:
colors = "#FF5733,#33FF57,#3357FF,#FF33A1,#33FFF5,#FF8C33,#8C33FF,#33FF8C,#FF3333,#33A1FF"
color_guided_generation_params = {
"text": text,
"colors": colors.split(','),
**reference_image_encoded,
**({"negativeText": negative_text} if negative_text not in [None, ""] else {})
}
body = build_request("COLOR_GUIDED_GENERATION", color_guided_generation_params, height, width, quality, cfg_scale, seed)
return display_image(generate_image(body))
def background_removal(image):
input_image = process_and_encode_image(image)
body = json.dumps({
"taskType": "BACKGROUND_REMOVAL",
"backgroundRemovalParams": {"image": input_image}
})
return display_image(generate_image(body))
def generate_nova_prompt():
with open('seeds.json', 'r') as file:
data = json.load(file)
if 'seeds' not in data or not isinstance(data['seeds'], list):
raise ValueError("The JSON file must contain a 'seeds' key with a list of strings.")
random_string = random.choice(data['seeds'])
prompt = f"""
Generate a creative image prompt that builds upon this concept: "{random_string}"
Requirements:
- Create a new, expanded prompt without mentioning or repeating the original concept
- Focus on vivid visual details and artistic elements
- Keep the prompt under 1000 characters
- Do not include any meta-instructions or seed references
- Return only the new prompt text
Response Format:
[Just the new prompt text, nothing else]
"""
messages = [
{"role": "user", "content": [{"text": prompt}]}
]
return generate_prompt(messages)
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