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https://github.com/marcogll/anchor23.git
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Remove scripts from repository for now
Remove tools/ directory containing generate_swatches.py and downscale_colors.py as they are not needed at this time.
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@@ -1,25 +0,0 @@
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from PIL import Image
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import os
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# =========================
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# CONFIGURACIÓN
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# =========================
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INPUT_DIR = "assets/colors"
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OUTPUT_SIZE = (32, 32) # cambia a (24, 24) si lo prefieres
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SUPPORTED_EXTENSIONS = (".png", ".jpg", ".jpeg", ".webp")
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# =========================
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# DOWNSCALE
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# =========================
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for filename in os.listdir(INPUT_DIR):
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if filename.lower().endswith(SUPPORTED_EXTENSIONS):
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path = os.path.join(INPUT_DIR, filename)
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with Image.open(path) as img:
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img = img.convert("RGB")
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img = img.resize(OUTPUT_SIZE, Image.Resampling.LANCZOS)
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img.save(path, optimize=True)
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print(f"Downscaled {filename} to {OUTPUT_SIZE[0]}x{OUTPUT_SIZE[1]}")
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@@ -1,48 +0,0 @@
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from openai import OpenAI
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import base64
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import os
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# =========================
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# CONFIGURACIÓN API
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# =========================
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# Set OPENAI_API_KEY as environment variable or replace below
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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if not OPENAI_API_KEY:
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raise ValueError("OPENAI_API_KEY environment variable not set")
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client = OpenAI(api_key=OPENAI_API_KEY)
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# =========================
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# CONFIGURACIÓN
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# =========================
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SIZE = "1024x1024" # Tamaño válido
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OUTPUT_DIR = "assets/colors"
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COLORS = {
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"bone-white": "#F6F1EC",
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"soft-cream": "#EFE7DE",
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"mocha-taupe": "#B8A89A",
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"deep-earth": "#6F5E4F",
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"charcoal-brown": "#3F362E",
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}
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PROMPT_TEMPLATE = (
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"A flat square color swatch, solid fill, hex color {hex}. "
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"No gradients, no texture, no shadow, no border. "
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"Minimal, neutral, technical style."
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)
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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for name, hex_color in COLORS.items():
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prompt = PROMPT_TEMPLATE.format(hex=hex_color)
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result = client.images.generate(model="gpt-image-1", prompt=prompt, size=SIZE)
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image_base64 = result.data[0].b64_json
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image_bytes = base64.b64decode(image_base64)
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output_path = os.path.join(OUTPUT_DIR, f"{name}.png")
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with open(output_path, "wb") as f:
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f.write(image_bytes)
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print(f"Generated {output_path}")
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