How can I use only the images in the video without any prompts? TypeError: 'numpy.float64' object is not iterable

[ismakegame]

{ "batch_name":"Example_DGSpitzer", "n_batch": 1, "prompts":[], "width":576, "height":832, "bit_depth_output":8, "seed":3521683325, "seed_behavior":"iter", "sampler":"dpmpp_2s_a", "steps":50, "scale":7, "ddim_eta":0.0, "filename_format":"{timestring}{index}{prompt}.png", "use_init":true, "init_image":"https://cdn.pixabay.com/photo/2022/07/30/13/10/green-longhorn-beetle-7353749_1280.jpg", "strength":0.0, "use_mask":true, "use_alpha_as_mask":false, "invert_mask":false, "mask_file":"https://www.filterforge.com/wiki/images/archive/b/b7/20080927223728%21Polygonal_gradient_thumb.jpg", "mask_brightness_adjust":1.0, "mask_contrast_adjust":1.0, "overlay_mask":true, "mask_overlay_blur":5, "mean_scale":0, "var_scale":0, "exposure_scale":1, "exposure_target":0.5, "colormatch_scale":1, "colormatch_image":"https://www.saasdesign.io/wp-content/uploads/2021/02/palette-3-min-980x588.png", "colormatch_n_colors":4, "ignore_sat_weight":0, "clip_name":"ViT-L/14", "clip_scale":1, "aesthetics_scale":0, "cutn":1, "cut_pow":0.0001, "init_mse_scale":0, "init_mse_image":"https://cdn.pixabay.com/photo/2022/07/30/13/10/green-longhorn-beetle-7353749_1280.jpg", "blue_scale":1, "gradient_wrt":"x0_pred", "gradient_add_to":"both", "decode_method":"linear", "grad_threshold_type":"dynamic", "clamp_grad_threshold":0.2, "clamp_start":0.2, "clamp_stop":0.01, "cond_uncond_sync":true, "animation_prompts":{ }, "animation_mode":"Video Input", "max_frames":100, "diffusion_cadence":"2", "border":"warp", "angle":"0:(0)", "zoom":"0:(1.04)", "translation_x":"0:(5sin(23.14*t/10))", "translation_y":"0:(0.5)", "translation_z":"0:(0.5)", "rotation_3d_x":"0:(0)", "rotation_3d_y":"0:(0)", "rotation_3d_z":"0:(0)", "flip_2d_perspective":false, "perspective_flip_theta":"0:(0)", "perspective_flip_phi":"0:(t%15)", "perspective_flip_gamma":"0:(0)", "perspective_flip_fv":"0:(53)", "noise_schedule":"0:(0.02)", "strength_schedule":"0:(0.55),49:(0.1),51:(0.65)", "contrast_schedule":"0:(1.0)", "color_coherence":"Match Frame 0 LAB", "use_depth_warping":true, "midas_weight":0.3, "near_plane":200, "far_plane":10000, "fov":40, "padding_mode":"border", "sampling_mode":"bicubic", "save_depth_maps":false, "video_init_path":"./input/2.mp4", "extract_nth_frame":1, "overwrite_extracted_frames":true, "use_mask_video":false, "video_mask_path":"", "interpolate_key_frames":false, "interpolate_x_frames":4, "resume_from_timestring":false, "resume_timestring":"20220829210106", "fps":24 }

(dsd) E:\tools\DeforumStableDiffusionLocal-main>python run.py --enable_animation_mode --settings "./examples/runSettings_AnimationExtra.txt" models_path: E:\tools\DeforumStableDiffusionLocal-main\models output_path: E:\tools\DeforumStableDiffusionLocal-main\output configs\v1-inference.yaml exists config_path: E:\tools\DeforumStableDiffusionLocal-main\configs\v1-inference.yaml ckpt_path: E:\tools\DeforumStableDiffusionLocal-main\models\v1-5-pruned-emaonly.ckpt ..loading model LatentDiffusion: Running in eps-prediction mode Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 768 and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 8 heads. Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 768 and using 8 heads. DiffusionWrapper has 859.52 M params. making attention of type 'vanilla-xformers' with 512 in_channels building MemoryEfficientAttnBlock with 512 in_channels... Working with z of shape (1, 4, 32, 32) = 4096 dimensions. making attention of type 'vanilla-xformers' with 512 in_channels building MemoryEfficientAttnBlock with 512 in_channels... Exporting Video Frames (1 every 1) frames to E:\tools\DeforumStableDiffusionLocal-main\output\2023-02\Example_DGSpitzer\inputframes... Converted 25 frames Loading 25 input frames from E:\tools\DeforumStableDiffusionLocal-main\output\2023-02\Example_DGSpitzer\inputframes and saving video frames to E:\tools\DeforumStableDiffusionLocal-main\output\2023-02\Example_DGSpitzer Saving animation frames to E:\tools\DeforumStableDiffusionLocal-main\output\2023-02\Example_DGSpitzer Rendering animation frame 0 of 25 nan 3521683325 Using video init frame E:\tools\DeforumStableDiffusionLocal-main\output\2023-02\Example_DGSpitzer\inputframes\00001.jpg Global seed set to 3521683325 d:\Users\zoyi\anaconda3\envs\dsd\lib\site-packages\sklearn\cluster_kmeans.py:870: FutureWarning: The default value of n_init will change from 10 to 'auto' in 1.4. Set the value of n_init explicitly to suppress the warning warnings.warn( <PIL.Image.Image image mode=RGB size=266x68 at 0x24D0125A020> d:\Users\zoyi\anaconda3\envs\dsd\lib\site-packages\sklearn\cluster_kmeans.py:870: FutureWarning: The default value of n_init will change from 10 to 'auto' in 1.4. Set the value of n_init explicitly to suppress the warning warnings.warn( Traceback (most recent call last): File "E:\tools\DeforumStableDiffusionLocal-main\run.py", line 488, in main() File "E:\tools\DeforumStableDiffusionLocal-main\run.py", line 406, in main render_input_video(args, anim_args, animation_prompts, root) File "E:\tools\DeforumStableDiffusionLocal-main\deforum-stable-diffusion\helpers\render.py", line 485, in render_input_video render_animation(args, anim_args, animation_prompts, root) File "E:\tools\DeforumStableDiffusionLocal-main\deforum-stable-diffusion\helpers\render.py", line 430, in render_animation sample, image = generate(args, root, frame_idx, return_latent=False, return_sample=True) File "E:\tools\DeforumStableDiffusionLocal-main\deforum-stable-diffusion\helpers\generate.py", line 144, in generate clip_loss_fn = make_clip_loss_fn(root, args) File "E:\tools\DeforumStableDiffusionLocal-main\deforum-stable-diffusion\helpers\conditioning.py", line 74, in make_clip_loss_fn target_embeds, weights = parse_clip_prompts(args.clip_prompt) File "E:\tools\DeforumStableDiffusionLocal-main\deforum-stable-diffusion\helpers\conditioning.py", line 59, in parse_clip_prompts for prompt in clip_prompt: TypeError: 'numpy.float64' object is not iterable

[HelixNGC7293]

You can use this format below to keep your prompt empty (normally recommended at least type in some words to describe the image though) "animation_prompts":{ "0":"" },