Sure, let’s sketch a quick script idea that’s easy to tweak. Start by loading a dream‑description text prompt, then use an image‑generation API like DALL‑E or Stable Diffusion to create a base image. Next, apply a few Photoshop‑style filters—blur the edges, boost saturation, overlay a subtle grain—to give it that surreal feel. Finally, wrap it all in a short Python loop that reads a CSV of prompts and saves each result. If you need the exact code snippets, just let me know and I’ll walk you through it step by step.

That’s a great plan! We can use pandas to read the CSV, the OpenAI API to generate the image, and OpenCV for the post‑processing. For saturation tweaks, OpenCV’s `convertScaleAbs` or `cv2.cvtColor` with HSV conversion works well. If you want me to write a small starter script, just say so and I’ll share the code step by step.

Here’s a quick starter in Python – no fancy formatting, just plain code you can copy: ```python import pandas as pd import requests import cv2 import numpy as np from io import BytesIO from PIL import Image # 1. Read prompts df = pd.read_csv('prompts.csv') # file should have a column named 'prompt' # 2. Function to call OpenAI's image generation def generate_image(prompt): url = "https://api.openai.com/v1/images/generations" headers = { "Authorization": f"Bearer YOUR_OPENAI_KEY", "Content-Type": "application/json" } data = { "model": "dall-e-3", "prompt": prompt, "size": "1024x1024", "response_format": "url" } r = requests.post(url, headers=headers, json=data) r.raise_for_status() image_url = r.json()["data"][0]["url"] img_bytes = requests.get(image_url).content img = Image.open(BytesIO(img_bytes)) return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR) # 3. Simple OpenCV tweak: contrast + grain def post_process(img, contrast=1.2, grain_strength=0.05): # Adjust contrast img = cv2.convertScaleAbs(img, alpha=contrast, beta=0) # Add grain noise = np.random.normal(0, 255*grain_strength, img.shape).astype(np.uint8) img = cv2.add(img, noise) return img # 4. Loop over prompts, generate, tweak, and save for idx, row in df.iterrows(): prompt = row['prompt'] try: img = generate_image(prompt) img = post_process(img) cv2.imwrite(f"output_{idx}.png", img) print(f"Saved output_{idx}.png") except Exception as e: print(f"Error processing prompt {idx}: {e}") ``` Replace `YOUR_OPENAI_KEY` with your actual key and make sure the CSV has a `prompt` column. Once you run it, you’ll get a folder full of generated images you can tweak further. Let me know how it goes, and we can fine‑tune the contrast, grain, or even add a saturation slider next!