Frank Schwenk
75 lines
2.5 KiB
Python
75 lines
2.5 KiB
Python
#!/usr/bin/env python3
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"""Example pipeline: OpenRouter photo enhancement (Darktable export → cloud edit)."""
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import os
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from pathlib import Path
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from imagepipeline import Pipeline
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REPO_ROOT = Path(__file__).resolve().parents[1]
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ENV_FILE = REPO_ROOT / ".env"
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# Change this to your Darktable export folder.
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INPUT = Path("/home/frank/tmp/aiedittest")
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# Optional: where run folders are created (defaults to current working directory).
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OUTPUT_BASE = Path.home() / "pipeline_output"
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OPENROUTER_PROMPT = (
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"Subtle photo enhancement only. Improve exposure, color, and skin tones. "
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"Sharpen where the blur seems to be unintended."
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"Keep the same people, poses, background, and composition. "
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"Natural, realistic look — no oversaturation or plastic skin."
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"Do not change image ratio, do not crop or enlarge the image, just improve the photo."
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"In group photos, improve the photo of the group, not the individual photos."
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"Also in group photos make faces same brightness and remove any glare or reflections."
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"Think of it like an amateur developed the RAW file in Lightroom and you are the senior who makes final touches to make it look professional."
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)
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# Test cheap with Klein; switch to flux.2-pro or flux.2-max for final exports.
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OPENROUTER_MODEL = "x-ai/grok-imagine-image-quality"
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def _load_env_file(path: Path) -> None:
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if not path.is_file():
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return
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for raw_line in path.read_text(encoding="utf-8").splitlines():
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line = raw_line.strip()
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if not line or line.startswith("#"):
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continue
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key, sep, value = line.partition("=")
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if not sep:
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continue
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key = key.strip()
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value = value.strip()
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if len(value) >= 2 and value[0] == value[-1] and value[0] in "\"'":
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value = value[1:-1]
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os.environ.setdefault(key, value)
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def main() -> None:
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_load_env_file(ENV_FILE)
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with Pipeline(
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name="example_ai",
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input_dir=INPUT,
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output_base=OUTPUT_BASE,
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) as p:
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p.step(
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"openrouter_edit",
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inputs="input",
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prompt=OPENROUTER_PROMPT,
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model=OPENROUTER_MODEL,
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max_edge=2048,
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)
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# Local CPU fallback (usually worse on already-graded Darktable exports):
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# exp = p.step("ai_exposure", inputs="input", max_edge=2048, strength=0.5)
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# p.step("ai_tone_map", inputs=exp, strength=0.5)
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output_root = p.run()
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print(f"Pipeline finished. Output: {output_root}")
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if __name__ == "__main__":
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main()
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