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import json
import base64
import random
from PIL import Image, ImageEnhance
from io import BytesIO
import numpy as np
import time
def load_image_data(json_path='AgPixelGen.json'):
with open(json_path, 'r') as f:
return json.load(f)
def decode_image_from_base64(base64_string):
image_bytes = base64.b64decode(base64_string)
image = Image.open(BytesIO(image_bytes))
return image
def random_transform(image):
random.seed(time.time())
transforms = ['color_change', 'noise']
random.shuffle(transforms)
for transform_type in transforms:
if transform_type == 'color_change':
image = color_change(image)
elif transform_type == 'noise':
image = add_noise(image)
return image
def color_change(image):
enhancer = ImageEnhance.Color(image)
image = enhancer.enhance(random.uniform(0.2, 3.0))
enhancer = ImageEnhance.Brightness(image)
image = enhancer.enhance(random.uniform(0.5, 2.0))
enhancer = ImageEnhance.Contrast(image)
image = enhancer.enhance(random.uniform(0.5, 2.0))
return image
def add_noise(image):
width, height = image.size
pixels = np.array(image)
noise_factor = random.uniform(0.02, 0.1)
noise = np.random.normal(scale=noise_factor, size=(height, width, 3))
noisy_pixels = pixels + noise * 255
noisy_pixels = np.clip(noisy_pixels, 0, 255).astype(np.uint8)
return Image.fromarray(noisy_pixels)
def decode_and_transform_image(image_data, key):
image = decode_image_from_base64(image_data[key])
transformed_image = random_transform(image)
return transformed_image
def save_image(image, output_path='output.jpg'):
image.save(output_path)
def generate_image(user_prompt=""):
image_data = load_image_data()
if user_prompt:
key = user_prompt.replace(' ', '+')
else:
matched_keys = [k for k in image_data.keys() if all(word.lower() in k.lower() for word in user_prompt.split())]
if matched_keys:
key = random.choice(matched_keys)
else:
key = None
if not key or key not in image_data:
matched_keys = [k for k in image_data.keys() if all(word.lower() in k.lower() for word in user_prompt.split())]
if matched_keys:
key = random.choice(matched_keys)
else:
return "<error>"
transformed_image = decode_and_transform_image(image_data, key)
save_image(transformed_image)
return "Image generated and saved."
if __name__ == "__main__":
user_prompt = input("Enter your prompt: ")
result = generate_image(user_prompt)
print(result) |