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AgPixelGen.py

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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)