import os from pathlib import Path import numpy as np from PIL import Image from mflux import Config, Flux1, ModelConfig class ImageGeneratorTestHelper: @staticmethod def assert_matches_reference_image( reference_image_path: str, output_image_path: str, model_config: ModelConfig, prompt: str, steps: int, seed: int, height: int = None, width: int = None, image_path: str | None = None, image_strength: float | None = None, lora_paths: list[str] | None = None, lora_scales: list[float] | None = None, ): # resolve paths reference_image_path = ImageGeneratorTestHelper.resolve_path(reference_image_path) output_image_path = ImageGeneratorTestHelper.resolve_path(output_image_path) lora_paths = [str(ImageGeneratorTestHelper.resolve_path(p)) for p in lora_paths] if lora_paths else None try: # given flux = Flux1( model_config=model_config, quantize=8, lora_paths=lora_paths, lora_scales=lora_scales ) # fmt: off # when image = flux.generate_image( seed=seed, prompt=prompt, config=Config( num_inference_steps=steps, image_path=ImageGeneratorTestHelper.resolve_path(image_path), image_strength=image_strength, height=height, width=width, ), ) image.save(path=output_image_path, overwrite=True) # then np.testing.assert_array_equal( np.array(Image.open(output_image_path)), np.array(Image.open(reference_image_path)), err_msg=f"Generated image doesn't match reference image. Check {output_image_path} vs {reference_image_path}", ) finally: # cleanup if os.path.exists(output_image_path): os.remove(output_image_path) @staticmethod def resolve_path(path) -> Path | None: if path is None: return None return Path(__file__).parent.parent.parent / "resources" / path