from mflux.config.model_config import ModelConfig from mflux.models.qwen.variants.txt2img.qwen_image import QwenImage from tests.image_generation.helpers.image_generation_test_helper import ImageGeneratorTestHelper class TestImageGeneratorQwenImage: def test_qwen_image_generation_text_to_image(self): ImageGeneratorTestHelper.assert_matches_reference_image( reference_image_path="reference_qwen_txt2img.png", output_image_path="output_qwen_txt2img.png", model_class=QwenImage, model_config=ModelConfig.qwen_image(), quantize=6, # We should probably use at least 8-bit, but it doesn't run on 32GB machines steps=20, seed=42, height=341, width=768, prompt="Luxury food photograph", negative_prompt="ugly, blurry, low quality", mismatch_threshold=0.35, # Qwen models produce visually similar images with minor pixel differences ) def test_qwen_image_generation_image_to_image(self): ImageGeneratorTestHelper.assert_matches_reference_image( reference_image_path="reference_qwen_img2img.png", output_image_path="output_qwen_img2img.png", model_class=QwenImage, model_config=ModelConfig.qwen_image(), quantize=6, # We should probably use at least 8-bit, but it doesn't run on 32GB machines steps=20, seed=44, height=341, width=768, image_path="reference_dev_image_to_image.png", image_strength=0.4, prompt="Luxury food photograph of a burger", negative_prompt="ugly, blurry, low quality", mismatch_threshold=0.35, # Qwen models produce visually similar images with minor pixel differences ) def test_qwen_image_generation_lora(self): ImageGeneratorTestHelper.assert_matches_reference_image( reference_image_path="reference_qwen_lora.png", output_image_path="output_qwen_lora.png", model_class=QwenImage, model_config=ModelConfig.qwen_image(), guidance=1.0, quantize=6, # We should probably use at least 8-bit, but it doesn't run on 32GB machines steps=4, seed=42, height=341, width=768, prompt="Luxury food photograph", negative_prompt="ugly, blurry, low quality", lora_repo_id="lightx2v/Qwen-Image-Lightning", lora_names=["Qwen-Image-Lightning-4steps-V2.0.safetensors"], mismatch_threshold=0.65, # LoRA tests have higher variance due to model updates )