Fix controlnet input arg name and group controlnet arguments
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@ -8,7 +8,8 @@ def main():
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# fmt: off
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parser = argparse.ArgumentParser(description="Generate an image based on a prompt.")
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parser.add_argument("--prompt", type=str, required=True, help="The textual description of the image to generate.")
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parser.add_argument("--control-image-path", type=str, required=True, help="Local path of the image to use as input for controlnet.")
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parser.add_argument("--controlnet-image-path", type=str, required=True, help="Local path of the image to use as input for controlnet.")
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parser.add_argument("--controlnet-strength", type=float, default=0.4, help="Controls how strongly the control image influences the output image. A value of 0.0 means no influence. (Default is 0.4)")
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parser.add_argument("--output", type=str, default="image.png", help="The filename for the output image. Default is \"image.png\".")
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parser.add_argument("--model", "-m", type=str, required=True, choices=["dev", "schnell"], help="The model to use (\"schnell\" or \"dev\").")
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parser.add_argument("--seed", type=int, default=None, help="Entropy Seed (Default is time-based random-seed)")
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@ -16,7 +17,6 @@ def main():
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parser.add_argument("--width", type=int, default=1024, help="Image width (Default is 1024)")
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parser.add_argument("--steps", type=int, default=None, help="Inference Steps")
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parser.add_argument("--guidance", type=float, default=3.5, help="Guidance Scale (Default is 3.5)")
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parser.add_argument("--controlnet-strength", type=float, default=0.7, help="Controls how strongly the control image influences the output image. A value of 0.0 means no influence. (Default is 0.7)")
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parser.add_argument("--quantize", "-q", type=int, choices=[4, 8], default=None, help="Quantize the model (4 or 8, Default is None)")
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parser.add_argument("--path", type=str, default=None, help="Local path for loading a model from disk")
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parser.add_argument("--lora-paths", type=str, nargs="*", default=None, help="Local safetensors for applying LORA from disk")
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@ -45,7 +45,7 @@ def main():
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image = flux.generate_image(
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seed=int(time.time()) if args.seed is None else args.seed,
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prompt=args.prompt,
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control_image=ImageUtil.load_image(args.control_image_path),
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control_image=ImageUtil.load_image(args.controlnet_image_path),
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config=ConfigControlnet(
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num_inference_steps=args.steps,
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height=args.height,
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