[WWB]: Add ImageText-to-Image pipeline validation #1373
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is image to image sensitive to random |
the problem came from the difference in the resolutions of generated images by HF and GenAI libs. |
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I am getting good accuracy convergence for big models, e.g. SD-XL but cannot make tests working with GenAI for any dummy model (I tried several). Waiting for fixes from OV. |
…nvino.genai into ak/wwb_inpainting
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@ilya-lavrenov, CI is passed with non-dummy model. |
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WWB tests on master: WWB tests on current PR: WWB tests with dummy random model: Even if we switch to dummy model once the related issue is fixed by CPU team, execution time is still very huge, can it be optimized? why did im2im give 3x to execution time even with dummy models? |
| prompt, | ||
| image=image_data, | ||
| num_inference_steps=num_inference_steps, | ||
| strength=0.8, |
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do you run optimum / diffusers with the same strength value?
| @@ -65,6 +67,7 @@ def test_image_model_types(model_id, model_type, backend): | |||
| @pytest.mark.parametrize( | |||
| ("model_id", "model_type"), | |||
| [ | |||
| ("dreamlike-art/dreamlike-anime-1.0", "image-to-image"), | |||
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maybe echarlaix/tiny-random-latent-consistency can work here instead of non-working echarlaix/tiny-random-stable-diffusion-xl ?
CVS-159223