jeep_posche_local_latent_blend.yaml

# CUDA_VISIBLE_DEVICES=5 python test_fatezero.py --config config/teaser/jeep_posche_local_latent_blend.yaml

pretrained_model_path: "./ckpt/jeep_tuned_200"

dataset_config:
    path: "data/teaser_car-turn"
    prompt: "a silver jeep driving down a curvy road in the countryside,"
    n_sample_frame: 8
    sampling_rate: 1
    stride: 80
    offset: 
        left: 0
        right: 0
        top: 0
        bottom: 0


editing_config:
    use_invertion_latents: true
    use_inversion_attention: true
    annotate: False
    editing_prompts: [
        # a silver jeep driving down a curvy road in the countryside,
        a Porsche car driving down a curvy road in the countryside,
    ]
    p2p_config:

        0:
            cross_replace_steps: 
                default_: 0.5
            self_replace_steps: 0.5
            
            use_inversion_attention: True
            is_replace_controller: True

            blend_words: [['silver', 'jeep'], ["Porsche", 'car']] # for local edit. If it is not local yet - use only the source object: blend_word = ((('cat',), ("cat",))).
            blend_self_attention: True
            blend_latents: True
            blend_th: [0.3, 0.3]
            
    clip_length: "${..dataset_config.n_sample_frame}"
    sample_seeds: [0]

    num_inference_steps: 50
    prompt2prompt_edit: True

    
model_config:
    lora: 160


test_pipeline_config:
    target: video_diffusion.pipelines.p2p_ddim_spatial_temporal.P2pDDIMSpatioTemporalPipeline
    num_inference_steps: "${..validation_sample_logger.num_inference_steps}"



seed: 0