Qwen-Image-Layered-MRP-MLX/tests/image_generation/helpers/image_generation_controlnet_test_helper.py
2025-03-01 21:37:03 +01:00

64 lines
2.1 KiB
Python

import os
import numpy as np
from PIL import Image
from mflux import Config, Flux1Controlnet, ModelConfig
from tests.image_generation.helpers.image_generation_test_helper import ImageGeneratorTestHelper
class ImageGeneratorControlnetTestHelper:
@staticmethod
def assert_matches_reference_image(
reference_image_path: str,
output_image_path: str,
controlnet_image_path: str,
model_config: ModelConfig,
prompt: str,
steps: int,
seed: int,
controlnet_strength: float,
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)
controlnet_image_path = str(ImageGeneratorTestHelper.resolve_path(controlnet_image_path))
lora_paths = [str(ImageGeneratorTestHelper.resolve_path(p)) for p in lora_paths] if lora_paths else None
try:
# given
flux = Flux1Controlnet(
model_config=model_config,
quantize=8,
lora_paths=lora_paths,
lora_scales=lora_scales,
)
# when
image = flux.generate_image(
seed=seed,
prompt=prompt,
controlnet_image_path=controlnet_image_path,
config=Config(
num_inference_steps=steps,
height=768,
width=493,
controlnet_strength=controlnet_strength,
),
)
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="Generated image doesn't match reference image",
)
finally:
# cleanup
if os.path.exists(output_image_path):
os.remove(output_image_path)