64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
import os
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import numpy as np
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from PIL import Image
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from mflux import ModelConfig, Flux1Controlnet, ConfigControlnet
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from tests.helpers.image_generation_test_helper import ImageGeneratorTestHelper
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class ImageGeneratorControlnetTestHelper:
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@staticmethod
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def assert_matches_reference_image(
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reference_image_path: str,
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output_image_path: str,
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controlnet_image_path: str,
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model_config: ModelConfig,
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prompt: str,
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steps: int,
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seed: int,
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controlnet_strength: float,
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lora_paths: list[str] | None = None,
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lora_scales: list[float] | None = None,
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):
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# resolve paths
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reference_image_path = ImageGeneratorTestHelper.resolve_path(reference_image_path)
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output_image_path = ImageGeneratorTestHelper.resolve_path(output_image_path)
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controlnet_image_path = str(ImageGeneratorTestHelper.resolve_path(controlnet_image_path))
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lora_paths = [str(ImageGeneratorTestHelper.resolve_path(p)) for p in lora_paths] if lora_paths else None
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# given
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flux = Flux1Controlnet(
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model_config=model_config,
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quantize=8,
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lora_paths=lora_paths,
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lora_scales=lora_scales,
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)
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# when
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image = flux.generate_image(
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seed=seed,
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prompt=prompt,
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output=str(output_image_path),
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controlnet_image_path=controlnet_image_path,
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controlnet_save_canny=False,
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config=ConfigControlnet(
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num_inference_steps=steps,
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height=768,
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width=493,
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controlnet_strength=controlnet_strength,
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),
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)
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image.save(path=output_image_path)
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# then
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np.testing.assert_array_equal(
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np.array(Image.open(output_image_path)),
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np.array(Image.open(reference_image_path)),
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err_msg="Generated image doesn't match reference image",
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)
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# cleanup
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if os.path.exists(output_image_path):
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os.remove(output_image_path)
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