| from modules.shared import cmd_opts, opts |
| from modules.processing import get_fixed_seed |
| from modules.ui_components import FormRow |
| import modules.shared as sh |
| import modules.paths as ph |
| import os |
| from .frame_interpolation import set_interp_out_fps, gradio_f_interp_get_fps_and_fcount, process_interp_vid_upload_logic, process_interp_pics_upload_logic |
| from .upscaling import process_ncnn_upscale_vid_upload_logic |
| from .vid2depth import process_depth_vid_upload_logic |
| from .video_audio_utilities import find_ffmpeg_binary, ffmpeg_stitch_video, direct_stitch_vid_from_frames, get_quick_vid_info, extract_number, get_ffmpeg_params |
| from .gradio_funcs import * |
| from .general_utils import get_os, get_deforum_version, custom_placeholder_format, test_long_path_support, get_max_path_length, substitute_placeholders |
| from .deforum_controlnet import setup_controlnet_ui, controlnet_component_names, controlnet_infotext |
| import tempfile |
| |
| def Root(): |
| device = sh.device |
| models_path = ph.models_path + '/Deforum' |
| half_precision = not cmd_opts.no_half |
| mask_preset_names = ['everywhere','video_mask'] |
| p = None |
| frames_cache = [] |
| raw_batch_name = None |
| raw_seed = None |
| initial_seed = None |
| initial_info = None |
| first_frame = None |
| outpath_samples = "" |
| animation_prompts = None |
| color_corrections = None |
| initial_clipskip = None |
| current_user_os = get_os() |
| tmp_deforum_run_duplicated_folder = os.path.join(tempfile.gettempdir(), 'tmp_run_deforum') |
| return locals() |
|
|
| def DeforumAnimArgs(): |
| animation_mode = '2D' |
| max_frames = 120 |
| border = 'replicate' |
| angle = "0:(0)" |
| zoom = "0:(1.0025+0.002*sin(1.25*3.14*t/30))" |
| translation_x = "0:(0)" |
| translation_y = "0:(0)" |
| translation_z = "0:(1.75)" |
| transform_center_x = "0:(0.5)" |
| transform_center_y = "0:(0.5)" |
| rotation_3d_x = "0:(0)" |
| rotation_3d_y = "0:(0)" |
| rotation_3d_z = "0:(0)" |
| enable_perspective_flip = False |
| perspective_flip_theta = "0:(0)" |
| perspective_flip_phi = "0:(0)" |
| perspective_flip_gamma = "0:(0)" |
| perspective_flip_fv = "0:(53)" |
| noise_schedule = "0: (0.065)" |
| strength_schedule = "0: (0.65)" |
| contrast_schedule = "0: (1.0)" |
| cfg_scale_schedule = "0: (7)" |
| enable_steps_scheduling = False |
| steps_schedule = "0: (25)" |
| fov_schedule = "0: (70)" |
| aspect_ratio_schedule = "0: (1)" |
| aspect_ratio_use_old_formula = False |
| near_schedule = "0: (200)" |
| far_schedule = "0: (10000)" |
| seed_schedule = '0:(s), 1:(-1), "max_f-2":(-1), "max_f-1":(s)' |
| pix2pix_img_cfg_scale = "1.5" |
| pix2pix_img_cfg_scale_schedule = "0:(1.5)" |
| enable_subseed_scheduling = False |
| subseed_schedule = "0:(1)" |
| subseed_strength_schedule = "0:(0)" |
| |
| enable_sampler_scheduling = False |
| sampler_schedule = '0: ("Euler a")' |
| |
| use_noise_mask = False |
| mask_schedule = '0: ("{video_mask}")' |
| noise_mask_schedule = '0: ("{video_mask}")' |
| |
| enable_checkpoint_scheduling = False |
| checkpoint_schedule = '0: ("model1.ckpt"), 100: ("model2.safetensors")' |
| |
| enable_clipskip_scheduling = False |
| clipskip_schedule = '0: (2)' |
| |
| enable_noise_multiplier_scheduling = True |
| noise_multiplier_schedule = '0: (1.05)' |
| |
| amount_schedule = "0: (0.1)" |
| kernel_schedule = "0: (5)" |
| sigma_schedule = "0: (1.0)" |
| threshold_schedule = "0: (0.0)" |
| |
| hybrid_comp_alpha_schedule = "0:(0.5)" |
| hybrid_comp_mask_blend_alpha_schedule = "0:(0.5)" |
| hybrid_comp_mask_contrast_schedule = "0:(1)" |
| hybrid_comp_mask_auto_contrast_cutoff_high_schedule = "0:(100)" |
| hybrid_comp_mask_auto_contrast_cutoff_low_schedule = "0:(0)" |
| hybrid_flow_factor_schedule = "0:(1)" |
| |
| color_coherence = 'LAB' |
| color_coherence_image_path = "" |
| color_coherence_video_every_N_frames = 1 |
| color_force_grayscale = False |
| legacy_colormatch = False |
| diffusion_cadence = '2' |
| optical_flow_cadence = 'None' |
| cadence_flow_factor_schedule = "0: (1)" |
| optical_flow_redo_generation = 'None' |
| redo_flow_factor_schedule = "0: (1)" |
| diffusion_redo = '0' |
| |
| noise_type = 'perlin' |
| |
| perlin_w = 8 |
| perlin_h = 8 |
| perlin_octaves = 4 |
| perlin_persistence = 0.5 |
| |
| use_depth_warping = True |
| depth_algorithm = 'Midas-3-Hybrid' |
| midas_weight = 0.2 |
| padding_mode = 'border' |
| sampling_mode = 'bicubic' |
| save_depth_maps = False |
| |
| video_init_path ='https://deforum.github.io/a1/V1.mp4' |
| extract_nth_frame = 1 |
| extract_from_frame = 0 |
| extract_to_frame = -1 |
| overwrite_extracted_frames = True |
| use_mask_video = False |
| video_mask_path ='https://deforum.github.io/a1/VM1.mp4' |
| |
| hybrid_generate_inputframes = False |
| hybrid_generate_human_masks = "None" |
| hybrid_use_first_frame_as_init_image = True |
| hybrid_motion = "None" |
| hybrid_motion_use_prev_img = False |
| hybrid_flow_consistency = False |
| hybrid_consistency_blur = 2 |
| hybrid_flow_method = "RAFT" |
| hybrid_composite = 'None' |
| hybrid_use_init_image = False |
| hybrid_comp_mask_type = "None" |
| hybrid_comp_mask_inverse = False |
| hybrid_comp_mask_equalize = "None" |
| hybrid_comp_mask_auto_contrast = False |
| hybrid_comp_save_extra_frames = False |
| |
| resume_from_timestring = False |
| resume_timestring = "20230129210106" |
| enable_ddim_eta_scheduling = False |
| ddim_eta_schedule = "0:(0)" |
| enable_ancestral_eta_scheduling = False |
| ancestral_eta_schedule = "0:(1)" |
|
|
| return locals() |
| |
| def DeforumAnimPrompts(): |
| return r"""{ |
| "0": "tiny cute swamp bunny, highly detailed, intricate, ultra hd, sharp photo, crepuscular rays, in focus, by tomasz alen kopera", |
| "30": "anthropomorphic clean cat, surrounded by fractals, epic angle and pose, symmetrical, 3d, depth of field, ruan jia and fenghua zhong", |
| "60": "a beautiful coconut --neg photo, realistic", |
| "90": "a beautiful durian, trending on Artstation" |
| } |
| """ |
|
|
| def DeforumArgs(): |
| |
| W = 512 |
| H = 512 |
| W, H = map(lambda x: x - x % 64, (W, H)) |
| |
| show_info_on_ui = True |
|
|
| |
| tiling = False |
| restore_faces = False |
| seed_enable_extras = False |
| subseed = -1 |
| subseed_strength = 0 |
| seed_resize_from_w = 0 |
| seed_resize_from_h = 0 |
| |
| |
| seed = -1 |
| sampler = 'euler_ancestral' |
| steps = 25 |
| scale = 7 |
| |
| dynamic_threshold = None |
| static_threshold = None |
|
|
| |
| save_settings = True |
| save_sample_per_step = False |
|
|
| |
| prompt_weighting = False |
| normalize_prompt_weights = True |
| log_weighted_subprompts = False |
|
|
| |
| n_batch = 1 |
| batch_name = "Deforum_{timestring}" |
| seed_behavior = "iter" |
| seed_iter_N = 1 |
| outdir = "" |
|
|
| |
| use_init = False |
| strength = 0.8 |
| strength_0_no_init = True |
| init_image = "https://deforum.github.io/a1/I1.png" |
| |
| use_mask = False |
| use_alpha_as_mask = False |
| mask_file = "https://deforum.github.io/a1/M1.jpg" |
| invert_mask = False |
| |
| mask_contrast_adjust = 1.0 |
| mask_brightness_adjust = 1.0 |
| |
| overlay_mask = True |
| |
| mask_overlay_blur = 4 |
|
|
| fill = 1 |
| full_res_mask = True |
| full_res_mask_padding = 4 |
| reroll_blank_frames = 'reroll' |
| reroll_patience = 10 |
|
|
| n_samples = 1 |
| precision = 'autocast' |
|
|
| prompt = "" |
| timestring = "" |
| init_sample = None |
| mask_image = None |
| noise_mask = None |
| seed_internal = 0 |
|
|
| return locals() |
|
|
| def keyframeExamples(): |
| return '''{ |
| "0": "https://deforum.github.io/a1/Gi1.png", |
| "max_f/4-5": "https://deforum.github.io/a1/Gi2.png", |
| "max_f/2-10": "https://deforum.github.io/a1/Gi3.png", |
| "3*max_f/4-15": "https://deforum.github.io/a1/Gi4.jpg", |
| "max_f-20": "https://deforum.github.io/a1/Gi1.png" |
| }''' |
|
|
| def LoopArgs(): |
| use_looper = False |
| init_images = keyframeExamples() |
| image_strength_schedule = "0:(0.75)" |
| blendFactorMax = "0:(0.35)" |
| blendFactorSlope = "0:(0.25)" |
| tweening_frames_schedule = "0:(20)" |
| color_correction_factor = "0:(0.075)" |
| return locals() |
|
|
| def ParseqArgs(): |
| parseq_manifest = None |
| parseq_use_deltas = True |
| return locals() |
| |
| def DeforumOutputArgs(): |
| skip_video_creation = False |
| fps = 15 |
| make_gif = False |
| delete_imgs = False |
| image_path = "C:/SD/20230124234916_%09d.png" |
| mp4_path = "testvidmanualsettings.mp4" |
| add_soundtrack = 'None' |
| soundtrack_path = "https://deforum.github.io/a1/A1.mp3" |
| |
| r_upscale_video = False |
| r_upscale_factor = 'x2' |
| r_upscale_model = 'realesr-animevideov3' |
| r_upscale_keep_imgs = True |
| |
| store_frames_in_ram = False |
| |
| frame_interpolation_engine = "None" |
| frame_interpolation_x_amount = 2 |
| frame_interpolation_slow_mo_enabled = False |
| frame_interpolation_slow_mo_amount = 2 |
| frame_interpolation_keep_imgs = False |
| return locals() |
| |
| import gradio as gr |
| import time |
| from types import SimpleNamespace |
|
|
| i1_store_backup = f"<p style=\"text-align:center;font-weight:bold;margin-bottom:0em\">Deforum extension for auto1111 — version 2.4b | Git commit: {get_deforum_version()}</p>" |
| i1_store = i1_store_backup |
|
|
| mask_fill_choices=['fill', 'original', 'latent noise', 'latent nothing'] |
|
|
| def setup_deforum_setting_dictionary(self, is_img2img, is_extension = True): |
| d = SimpleNamespace(**DeforumArgs()) |
| da = SimpleNamespace(**DeforumAnimArgs()) |
| dp = SimpleNamespace(**ParseqArgs()) |
| dv = SimpleNamespace(**DeforumOutputArgs()) |
| dr = SimpleNamespace(**Root()) |
| dloopArgs = SimpleNamespace(**LoopArgs()) |
| if not is_extension: |
| with gr.Row(variant='compact'): |
| btn = gr.Button("Click here after the generation to show the video") |
| with gr.Row(variant='compact'): |
| i1 = gr.HTML(i1_store, elem_id='deforum_header') |
| else: |
| btn = i1 = gr.HTML("") |
| |
| with gr.Accordion("Info, Links and Help", open=False, elem_id='main_top_info_accord'): |
| gr.HTML("""<strong>Made by <a href="https://deforum.github.io">deforum.github.io</a>, port for AUTOMATIC1111's webui maintained by <a href="https://github.com/kabachuha">kabachuha</a></strong> & <a href="https://github.com/hithereai">hithereai</a></strong> """) |
| gr.HTML("""<a style="color:SteelBlue" href="https://github.com/deforum-art/deforum-for-automatic1111-webui/wiki/FAQ-&-Troubleshooting">FOR HELP CLICK HERE</a""", elem_id="for_help_click_here") |
| gr.HTML("""<ul style="list-style-type:circle; margin-left:1em"> |
| <li>The code for this extension: <a style="color:SteelBlue" href="https://github.com/deforum-art/deforum-for-automatic1111-webui">here</a>.</li> |
| <li>Join the <a style="color:SteelBlue" href="https://discord.gg/deforum">official Deforum Discord</a> to share your creations and suggestions.</li> |
| <li>Official Deforum Wiki: <a style="color:SteelBlue" href="https://github.com/deforum-art/deforum-for-automatic1111-webui/wiki">here</a>.</li> |
| <li>Anime-inclined great guide (by FizzleDorf) with lots of examples: <a style="color:SteelBlue" href="https://rentry.org/AnimAnon-Deforum">here</a>.</li> |
| <li>For advanced keyframing with Math functions, see <a style="color:SteelBlue" href="https://github.com/deforum-art/deforum-for-automatic1111-webui/wiki/Maths-in-Deforum">here</a>.</li> |
| <li>Alternatively, use <a style="color:SteelBlue" href="https://sd-parseq.web.app/deforum">sd-parseq</a> as a UI to define your animation schedules (see the Parseq section in the Init tab).</li> |
| <li><a style="color:SteelBlue" href="https://www.framesync.xyz/">framesync.xyz</a> is also a good option, it makes compact math formulae for Deforum keyframes by selecting various waveforms.</li> |
| <li>The other site allows for making keyframes using <a style="color:SteelBlue" href="https://www.chigozie.co.uk/keyframe-string-generator/">interactive splines and Bezier curves</a> (select Disco output format).</li> |
| <li>If you want to use Width/Height which are not multiples of 64, please change noise_type to 'Uniform', in Keyframes --> Noise.</li> |
| </ul> |
| <italic>If you liked this extension, please <a style="color:SteelBlue" href="https://github.com/deforum-art/deforum-for-automatic1111-webui">give it a star on GitHub</a>!</italic> 😊""") |
| with gr.Row(variant='compact'): |
| show_info_on_ui = gr.Checkbox(label="Show more info", value=d.show_info_on_ui, interactive=True) |
| if not is_extension: |
| def show_vid(): |
| return { |
| i1: gr.update(value=i1_store, visible=True) |
| } |
| |
| btn.click( |
| show_vid, |
| [], |
| [i1] |
| ) |
|
|
| with gr.Blocks(): |
| with gr.Tabs(): |
| |
| with gr.TabItem('Run'): |
| from modules.sd_samplers import samplers_for_img2img |
| with gr.Row(variant='compact'): |
| sampler = gr.Dropdown(label="Sampler", choices=[x.name for x in samplers_for_img2img], value=samplers_for_img2img[0].name, type="value", elem_id="sampler", interactive=True) |
| steps = gr.Slider(label="Steps", minimum=0, maximum=200, step=1, value=d.steps, interactive=True) |
| with gr.Row(variant='compact'): |
| W = gr.Slider(label="Width", minimum=64, maximum=2048, step=64, value=d.W, interactive=True) |
| H = gr.Slider(label="Height", minimum=64, maximum=2048, step=64, value=d.H, interactive=True) |
| with gr.Row(variant='compact'): |
| seed = gr.Number(label="Seed", value=d.seed, interactive=True, precision=0, info="Starting seed for the animation. -1 for random") |
| n_batch = gr.Slider(label="# of vids", minimum=1, maximum=100, step=1, value=d.n_batch, interactive=True, info="if seed is set to random (-1), generate a few vids in one run", visible=False) |
| batch_name = gr.Textbox(label="Batch name", lines=1, interactive=True, value = d.batch_name, info="output images will be placed in a folder with this name ({timestring} token will be replaced) inside the img2img output folder. Supports params placeholders. e.g {seed}, {w}, {h}, {prompts}") |
| with gr.Row(variant='compact'): |
| restore_faces = gr.Checkbox(label='Restore Faces', value=d.restore_faces) |
| tiling = gr.Checkbox(label='Tiling', value=d.tiling) |
| enable_ddim_eta_scheduling = gr.Checkbox(label='Enable DDIM ETA scheduling', value=da.enable_ddim_eta_scheduling, visible=False) |
| enable_ancestral_eta_scheduling = gr.Checkbox(label='Enable Ancestral ETA scheduling', value=da.enable_ancestral_eta_scheduling) |
| with gr.Row(variant='compact') as eta_sch_row: |
| ddim_eta_schedule = gr.Textbox(label="DDIM ETA Schedule", lines=1, value=da.ddim_eta_schedule, interactive=True, visible=False) |
| ancestral_eta_schedule = gr.Textbox(label="Ancestral ETA Schedule", lines=1, value=da.ancestral_eta_schedule, interactive=True, visible=False) |
| |
| with gr.Accordion('Batch Mode, Resume and more', open=False): |
| with gr.Tab('Batch Mode/ run from setting files'): |
| with gr.Row(variant='compact'): |
| override_settings_with_file = gr.Checkbox(label="Enable batch mode", value=False, interactive=True, elem_id='override_settings', info="run from a list of setting .txt files. Upload them to the box on the right (visible when enabled)") |
| custom_settings_file = gr.File(label="Setting files", interactive=True, file_count="multiple", file_types=[".txt"], elem_id="custom_setting_file", visible=False) |
| |
| with gr.Tab('Resume Animation'): |
| with gr.Row(variant='compact'): |
| resume_from_timestring = gr.Checkbox(label="Resume from timestring", value=da.resume_from_timestring, interactive=True) |
| resume_timestring = gr.Textbox(label="Resume timestring", lines=1, value = da.resume_timestring, interactive=True) |
| with gr.Row(variant='compact') as pix2pix_img_cfg_scale_row: |
| pix2pix_img_cfg_scale_schedule = gr.Textbox(label="Pix2Pix img CFG schedule", value=da.pix2pix_img_cfg_scale_schedule, interactive=True, info="ONLY in use when working with a P2P ckpt!") |
| |
| with gr.TabItem('Keyframes'): |
| with gr.Row(variant='compact'): |
| with gr.Column(scale=2): |
| animation_mode = gr.Radio(['2D', '3D', 'Interpolation', 'Video Input'], label="Animation mode", value=da.animation_mode, elem_id="animation_mode", info="control animation mode, will hide non relevant params upon change") |
| with gr.Column(scale=1, min_width=180): |
| border = gr.Radio(['replicate', 'wrap'], label="Border", value=da.border, elem_id="border", info="controls pixel generation method for images smaller than the frame. hover on the options to see more info") |
| with gr.Row(variant='compact'): |
| diffusion_cadence = gr.Slider(label="Cadence", minimum=1, maximum=50, step=1, value=da.diffusion_cadence, interactive=True, info="# of in-between frames that will not be directly diffused") |
| max_frames = gr.Number(label="Max frames", lines=1, value = da.max_frames, interactive=True, precision=0, info="end the animation at this frame number") |
| |
| with gr.Accordion('Guided Images', open=False, elem_id='guided_images_accord') as guided_images_accord: |
| |
| with gr.Accordion('*READ ME before you use this mode!*', open=False): |
| gr.HTML("""You can use this as a guided image tool or as a looper depending on your settings in the keyframe images field. |
| Set the keyframes and the images that you want to show up. |
| Note: the number of frames between each keyframe should be greater than the tweening frames.""") |
| |
| gr.HTML("""Prerequisites and Important Info: |
| <ul style="list-style-type:circle; margin-left:2em; margin-bottom:0em"> |
| <li>This mode works ONLY with 2D/3D animation modes. Interpolation and Video Input modes aren't supported.</ li> |
| <li>Init tab's strength slider should be greater than 0. Recommended value (.65 - .80).</ li> |
| <li>'seed_behavior' will be forcibly set to 'schedule'.</li> |
| </ul> |
| """) |
| gr.HTML("""Looping recommendations: |
| <ul style="list-style-type:circle; margin-left:2em; margin-bottom:0em"> |
| <li>seed_schedule should start and end on the same seed. <br /> |
| Example: seed_schedule could use 0:(5), 1:(-1), 219:(-1), 220:(5)</li> |
| <li>The 1st and last keyframe images should match.</li> |
| <li>Set your total number of keyframes to be 21 more than the last inserted keyframe image. <br /> |
| Example: Default args should use 221 as total keyframes.</li> |
| <li>Prompts are stored in JSON format. If you've got an error, check it in validator, <a style="color:SteelBlue" href="https://odu.github.io/slingjsonlint/">like here</a></li> |
| </ul> |
| """) |
| gr.HTML("""The Guided images mode exposes the following variables for the prompts and the schedules: |
| <ul style="list-style-type:circle; margin-left:2em; margin-bottom:0em"> |
| <li><b>s</b> is the <i>initial</i> seed for the whole video generation.</li> |
| <li><b>max_f</b> is the length of the video, in frames.<br /> |
| Example: seed_schedule could use 0:(s), 1:(-1), "max_f-2":(-1), "max_f-1":(s)</li> |
| <li><b>t</b> is the current frame number.<br /> |
| Example: strength_schedule could use 0:(0.25 * cos((72 / 60 * 3.141 * (t + 0) / 30))**13 + 0.7) to make alternating changes each 30 frames</li> |
| </ul> |
| """) |
| with gr.Row(variant='compact'): |
| use_looper = gr.Checkbox(label="Enable guided images mode", value=dloopArgs.use_looper, interactive=True) |
| with gr.Row(variant='compact'): |
| init_images = gr.Textbox(label="Images to use for keyframe guidance", lines=9, value = keyframeExamples(), interactive=True) |
| |
| with gr.Accordion('Guided images schedules', open=False): |
| with gr.Row(variant='compact'): |
| image_strength_schedule = gr.Textbox(label="Image strength schedule", lines=1, value = dloopArgs.image_strength_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| blendFactorMax = gr.Textbox(label="Blend factor max", lines=1, value = dloopArgs.blendFactorMax, interactive=True) |
| with gr.Row(variant='compact'): |
| blendFactorSlope = gr.Textbox(label="Blend factor slope", lines=1, value = dloopArgs.blendFactorSlope, interactive=True) |
| with gr.Row(variant='compact'): |
| tweening_frames_schedule = gr.Textbox(label="Tweening frames schedule", lines=1, value = dloopArgs.tweening_frames_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| color_correction_factor = gr.Textbox(label="Color correction factor", lines=1, value = dloopArgs.color_correction_factor, interactive=True) |
| |
| with gr.Tabs(elem_id='extra_schedules'): |
| with gr.TabItem('Strength'): |
| with gr.Row(variant='compact'): |
| strength_schedule = gr.Textbox(label="Strength schedule", lines=1, value = da.strength_schedule, interactive=True, info="amount of presence of previous frame to influence next frame, also controls steps in the following formula [steps - (strength_schedule * steps)]") |
| with gr.TabItem('CFG'): |
| with gr.Row(variant='compact'): |
| cfg_scale_schedule = gr.Textbox(label="CFG scale schedule", lines=1, value = da.cfg_scale_schedule, interactive=True, info="how closely the image should conform to the prompt. Lower values produce more creative results. (recommended range 5-15)") |
| with gr.Row(variant='compact'): |
| enable_clipskip_scheduling = gr.Checkbox(label="Enable CLIP skip scheduling", value=da.enable_clipskip_scheduling, interactive=True) |
| with gr.Row(variant='compact'): |
| clipskip_schedule = gr.Textbox(label="CLIP skip schedule", lines=1, value = da.clipskip_schedule, interactive=True) |
| with gr.TabItem('Seed') as a3: |
| with gr.Row(variant='compact'): |
| seed_behavior = gr.Radio(['iter', 'fixed', 'random', 'ladder', 'alternate', 'schedule'], label="Seed behavior", value=d.seed_behavior, elem_id="seed_behavior", info="controls the seed behavior that is used for animation. hover on the options to see more info") |
| with gr.Row(variant='compact') as seed_iter_N_row: |
| seed_iter_N = gr.Number(label="Seed iter N", value=d.seed_iter_N, interactive=True, precision=0, info="for how many frames the same seed should stick before iterating to the next one") |
| with gr.Row(visible=False) as seed_schedule_row: |
| seed_schedule = gr.Textbox(label="Seed schedule", lines=1, value = da.seed_schedule, interactive=True) |
| with gr.TabItem('SubSeed', open=False) as subseed_sch_tab: |
| with gr.Row(variant='compact'): |
| enable_subseed_scheduling = gr.Checkbox(label="Enable Subseed scheduling", value=da.enable_subseed_scheduling, interactive=True) |
| subseed_schedule = gr.Textbox(label="Subseed schedule", lines=1, value = da.subseed_schedule, interactive=True) |
| subseed_strength_schedule = gr.Textbox(label="Subseed strength schedule", lines=1, value = da.subseed_strength_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=64, label="Resize seed from width", value=0) |
| seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=64, label="Resize seed from height", value=0) |
| |
| with gr.TabItem('Step') as a13: |
| with gr.Row(variant='compact'): |
| enable_steps_scheduling = gr.Checkbox(label="Enable steps scheduling", value=da.enable_steps_scheduling, interactive=True) |
| with gr.Row(variant='compact'): |
| steps_schedule = gr.Textbox(label="Steps schedule", lines=1, value = da.steps_schedule, interactive=True, info="mainly allows using more than 200 steps. otherwise, it's a mirror-like param of 'strength schedule'") |
| |
| with gr.TabItem('Sampler') as a14: |
| with gr.Row(variant='compact'): |
| enable_sampler_scheduling = gr.Checkbox(label="Enable sampler scheduling", value=da.enable_sampler_scheduling, interactive=True) |
| with gr.Row(variant='compact'): |
| sampler_schedule = gr.Textbox(label="Sampler schedule", lines=1, value = da.sampler_schedule, interactive=True, info="allows keyframing different samplers. Use names as they appear in ui dropdown in 'run' tab") |
| |
| with gr.TabItem('Checkpoint') as a15: |
| with gr.Row(variant='compact'): |
| enable_checkpoint_scheduling = gr.Checkbox(label="Enable checkpoint scheduling", value=da.enable_checkpoint_scheduling, interactive=True) |
| with gr.Row(variant='compact'): |
| checkpoint_schedule = gr.Textbox(label="Checkpoint schedule", lines=1, value = da.checkpoint_schedule, interactive=True, info="allows keyframing different sd models. use *full* name as appears in ui dropdown") |
| |
| with gr.Tabs(elem_id='motion_noise_etc'): |
| with gr.TabItem('Motion') as motion_tab: |
| with gr.Column(visible=True) as only_2d_motion_column: |
| with gr.Row(variant='compact'): |
| zoom = gr.Textbox(label="Zoom", lines=1, value = da.zoom, interactive=True, info="scale the canvas size, multiplicatively. [static = 1.0]") |
| with gr.Row(variant='compact'): |
| angle = gr.Textbox(label="Angle", lines=1, value = da.angle, interactive=True, info="rotate canvas clockwise/anticlockwise in degrees per frame") |
| with gr.Row(variant='compact'): |
| transform_center_x = gr.Textbox(label="Transform Center X", lines=1, value = da.transform_center_x, interactive=True, info="x center axis for 2D angle/zoom") |
| with gr.Row(variant='compact'): |
| transform_center_y = gr.Textbox(label="Transform Center Y", lines=1, value = da.transform_center_y, interactive=True, info="y center axis for 2D angle/zoom") |
| with gr.Column(visible=True) as both_anim_mode_motion_params_column: |
| with gr.Row(variant='compact'): |
| translation_x = gr.Textbox(label="Translation X", lines=1, value = da.translation_x, interactive=True, info="move canvas left/right in pixels per frame") |
| with gr.Row(variant='compact'): |
| translation_y = gr.Textbox(label="Translation Y", lines=1, value = da.translation_y, interactive=True, info="move canvas up/down in pixels per frame") |
| with gr.Column(visible=False) as only_3d_motion_column: |
| with gr.Row(variant='compact'): |
| translation_z = gr.Textbox(label="Translation Z", lines=1, value = da.translation_z, interactive=True, info="move canvas towards/away from view [speed set by FOV]") |
| with gr.Row(variant='compact'): |
| rotation_3d_x = gr.Textbox(label="Rotation 3D X", lines=1, value = da.rotation_3d_x, interactive=True, info="tilt canvas up/down in degrees per frame") |
| with gr.Row(variant='compact'): |
| rotation_3d_y = gr.Textbox(label="Rotation 3D Y", lines=1, value = da.rotation_3d_y, interactive=True, info="pan canvas left/right in degrees per frame") |
| with gr.Row(variant='compact'): |
| rotation_3d_z = gr.Textbox(label="Rotation 3D Z", lines=1, value = da.rotation_3d_z, interactive=True, info="roll canvas clockwise/anticlockwise") |
| |
| with gr.Row(variant='compact') as enable_per_f_row: |
| enable_perspective_flip = gr.Checkbox(label="Enable perspective flip", value=da.enable_perspective_flip, interactive=True) |
| with gr.Row(variant='compact', visible=False) as per_f_th_row: |
| perspective_flip_theta = gr.Textbox(label="Perspective flip theta", lines=1, value = da.perspective_flip_theta, interactive=True) |
| with gr.Row(variant='compact', visible=False) as per_f_ph_row: |
| perspective_flip_phi = gr.Textbox(label="Perspective flip phi", lines=1, value = da.perspective_flip_phi, interactive=True) |
| with gr.Row(variant='compact', visible=False) as per_f_ga_row: |
| perspective_flip_gamma = gr.Textbox(label="Perspective flip gamma", lines=1, value = da.perspective_flip_gamma, interactive=True) |
| with gr.Row(variant='compact', visible=False) as per_f_f_row: |
| perspective_flip_fv = gr.Textbox(label="Perspective flip fv", lines=1, value = da.perspective_flip_fv, interactive=True, info="the 2D vanishing point of perspective (rec. range 30-160)") |
| |
| with gr.TabItem('Noise'): |
| with gr.Column() as noise_tab_column: |
| with gr.Row(variant='compact'): |
| noise_type = gr.Radio(['uniform', 'perlin'], label="Noise type", value=da.noise_type, elem_id="noise_type") |
| with gr.Row(variant='compact'): |
| noise_schedule = gr.Textbox(label="Noise schedule", lines=1, value = da.noise_schedule, interactive=True) |
| with gr.Row(variant='compact') as perlin_row: |
| with gr.Column(min_width=220): |
| perlin_octaves = gr.Slider(label="Perlin octaves", minimum=1, maximum=7, value=da.perlin_octaves, step=1, interactive=True) |
| with gr.Column(min_width=220): |
| perlin_persistence = gr.Slider(label="Perlin persistence", minimum=0, maximum=1, value=da.perlin_persistence, step=0.02, interactive=True) |
| with gr.Row(variant='compact'): |
| enable_noise_multiplier_scheduling = gr.Checkbox(label="Enable noise multiplier scheduling", value=da.enable_noise_multiplier_scheduling, interactive=True) |
| with gr.Row(variant='compact'): |
| noise_multiplier_schedule = gr.Textbox(label="Noise multiplier schedule", lines=1, value = da.noise_multiplier_schedule, interactive=True) |
| |
| with gr.TabItem('Coherence', open=False) as coherence_accord: |
| with gr.Row(variant='compact'): |
| color_coherence = gr.Dropdown(label="Color coherence", choices=['None', 'HSV', 'LAB', 'RGB', 'Video Input', 'Image'], value=da.color_coherence, type="value", elem_id="color_coherence", interactive=True, info="choose an algorithm/ method for keeping color coherence across the animation") |
| color_force_grayscale = gr.Checkbox(label="Color force Grayscale", value=da.color_force_grayscale, interactive=True, info="force all frames to be in grayscale") |
| with gr.Row(variant='compact'): |
| legacy_colormatch = gr.Checkbox(label="Legacy colormatch", value=da.legacy_colormatch, interactive=True) |
| with gr.Row(visible=False) as color_coherence_image_path_row: |
| color_coherence_image_path = gr.Textbox(label="Color coherence image path", lines=1, value=da.color_coherence_image_path, interactive=True) |
| with gr.Row(visible=False) as color_coherence_video_every_N_frames_row: |
| color_coherence_video_every_N_frames = gr.Number(label="Color coherence video every N frames", value=1, interactive=True) |
| with gr.Row(variant='compact') as optical_flow_cadence_row: |
| with gr.Column(min_width=220) as optical_flow_cadence_column: |
| optical_flow_cadence = gr.Dropdown(choices=['None', 'RAFT', 'DIS Medium', 'DIS Fine', 'Farneback'], label="Optical flow cadence", value=da.optical_flow_cadence, elem_id="optical_flow_cadence", interactive=True, info="use optical flow estimation for your in-between (cadence) frames") |
| with gr.Column(min_width=220, visible=False) as cadence_flow_factor_schedule_column: |
| cadence_flow_factor_schedule = gr.Textbox(label="Cadence flow factor schedule", lines=1, value = da.cadence_flow_factor_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| with gr.Column(min_width=220): |
| optical_flow_redo_generation = gr.Dropdown(choices=['None', 'RAFT', 'DIS Medium', 'DIS Fine', 'Farneback'], label="Optical flow generation", value=da.optical_flow_redo_generation, elem_id="optical_flow_redo_generation", visible=True, interactive=True, info="this option takes twice as long because it generates twice in order to capture the optical flow from the previous image to the first generation, then warps the previous image and redoes the generation") |
| with gr.Column(min_width=220, visible=False) as redo_flow_factor_schedule_column: |
| redo_flow_factor_schedule = gr.Textbox(label="Generation flow factor schedule", lines=1, value = da.redo_flow_factor_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| contrast_schedule = gr.Textbox(label="Contrast schedule", lines=1, value = da.contrast_schedule, interactive=True, info="adjusts the overall contrast per frame [neutral at 1.0, recommended to *not* play with this param]") |
| diffusion_redo = gr.Slider(label="Redo generation", minimum=0, maximum=50, step=1, value=da.diffusion_redo, interactive=True, info="this option renders N times before the final render. it is suggested to lower your steps if you up your redo. seed is randomized during redo generations and restored afterwards") |
| with gr.Row(variant='compact'): |
| |
| reroll_blank_frames = gr.Radio(['reroll', 'interrupt', 'ignore'], label="Reroll blank frames", value=d.reroll_blank_frames, elem_id="reroll_blank_frames") |
| reroll_patience = gr.Number(value=d.reroll_patience, label="Reroll patience", interactive=True) |
| |
| with gr.TabItem('Anti Blur', elem_id='anti_blur_accord') as anti_blur_tab: |
| with gr.Row(variant='compact'): |
| amount_schedule = gr.Textbox(label="Amount schedule", lines=1, value = da.amount_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| kernel_schedule = gr.Textbox(label="Kernel schedule", lines=1, value = da.kernel_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| sigma_schedule = gr.Textbox(label="Sigma schedule", lines=1, value = da.sigma_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| threshold_schedule = gr.Textbox(label="Threshold schedule", lines=1, value = da.threshold_schedule, interactive=True) |
| with gr.TabItem('Depth Warping & FOV', elem_id='depth_warp_fov_tab') as depth_warp_fov_tab: |
| |
| depth_warp_msg_html = gr.HTML(value='Please switch to 3D animation mode to view this section.', elem_id='depth_warp_msg_html') |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_1: |
| use_depth_warping = gr.Checkbox(label="Use depth warping", value=da.use_depth_warping, interactive=True) |
| |
| leres_license_msg = gr.HTML(value='Note that LeReS has a Non-Commercial <a href="https://github.com/aim-uofa/AdelaiDepth/blob/main/LeReS/LICENSE" target="_blank">license</a>. Use it only for fun/personal use.', visible=False, elem_id='leres_license_msg') |
| depth_algorithm = gr.Dropdown(label="Depth Algorithm", choices=['Midas+AdaBins (old)','Zoe+AdaBins (old)','Midas-3-Hybrid','AdaBins','Zoe', 'Leres'], value=da.depth_algorithm, type="value", elem_id="df_depth_algorithm", interactive=True) |
| midas_weight = gr.Number(label="MiDaS/Zoe weight", value=da.midas_weight, interactive=True, visible=False, info="sets a midpoint at which a depthmap is to be drawn: range [-1 to +1]") |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_2: |
| padding_mode = gr.Radio(['border', 'reflection', 'zeros'], label="Padding mode", value=da.padding_mode, elem_id="padding_mode", info="controls the handling of pixels outside the field of view as they come into the scene. hover on the options for more info") |
| sampling_mode = gr.Radio(['bicubic', 'bilinear', 'nearest'], label="Sampling mode", value=da.sampling_mode, elem_id="sampling_mode") |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_3: |
| aspect_ratio_use_old_formula = gr.Checkbox(label="Use old aspect ratio formula", value=da.aspect_ratio_use_old_formula, interactive=True, info="for backward compatibility. uses the formula width/height") |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_4: |
| aspect_ratio_schedule = gr.Textbox(label="Aspect Ratio schedule", lines=1, value = da.aspect_ratio_schedule, interactive=True, info="adjusts the aspect ratio for the depth calculation") |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_5: |
| fov_schedule = gr.Textbox(label="FOV schedule", lines=1, value = da.fov_schedule, interactive=True, info="adjusts the scale at which the canvas is moved in 3D by the translation_z value. [maximum range -180 to +180, with 0 being undefined. Values closer to 180 will make the image have less depth, while values closer to 0 will allow more depth]") |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_6: |
| near_schedule = gr.Textbox(label="Near schedule", lines=1, value = da.near_schedule, interactive=True) |
| with gr.Row(variant='compact', visible=False) as depth_warp_row_7: |
| far_schedule = gr.Textbox(label="Far schedule", lines=1, value = da.far_schedule, interactive=True) |
| |
| with gr.TabItem('Prompts'): |
| |
| with gr.Accordion(label='*Important* notes on Prompts', elem_id='prompts_info_accord', open=False, visible=True) as prompts_info_accord: |
| gr.HTML(""" |
| <ul style="list-style-type:circle; margin-left:0.75em; margin-bottom:0.2em"> |
| <li>Please always keep values in math functions above 0.</li> |
| <li>There is *no* Batch mode like in vanilla deforum. Please Use the txt2img tab for that.</li> |
| <li>For negative prompts, please write your positive prompt, then --neg ugly, text, assymetric, or any other negative tokens of your choice. OR:</li> |
| <li>Use the negative_prompts field to automatically append all words as a negative prompt. *Don't* add --neg in the negative_prompts field!</li> |
| <li>Prompts are stored in JSON format. If you've got an error, check it in a <a style="color:SteelBlue" href="https://odu.github.io/slingjsonlint/">JSON Validator</a></li> |
| </ul> |
| """) |
| with gr.Row(variant='compact'): |
| animation_prompts = gr.Textbox(label="Prompts", lines=8, interactive=True, value = DeforumAnimPrompts(), info="full prompts list in a JSON format. value on left side is the frame number") |
| with gr.Row(variant='compact'): |
| animation_prompts_positive = gr.Textbox(label="Prompts positive", lines=1, interactive=True, placeholder="words in here will be added to the start of all positive prompts") |
| with gr.Row(variant='compact'): |
| animation_prompts_negative = gr.Textbox(label="Prompts negative", value="nsfw, nude", lines=1, interactive=True, placeholder="words in here will be added to the end of all negative prompts") |
| |
| with gr.Accordion('Composable Mask scheduling', open=False): |
| gr.HTML(""" |
| <ul style="list-style-type:circle; margin-left:0.75em; margin-bottom:0.2em"> |
| <li>To enable, check use_mask in the Init tab</li> |
| <li>Supports boolean operations: (! - negation, & - and, | - or, ^ - xor, \ - difference, () - nested operations)</li> |
| <li>default variables: in \{\}, like \{init_mask\}, \{video_mask\}, \{everywhere\}</li> |
| <li>masks from files: in [], like [mask1.png]</li> |
| <li>description-based: <i>word masks</i> in <>, like <apple>, <hair></li> |
| </ul> |
| """) |
| with gr.Row(variant='compact'): |
| mask_schedule = gr.Textbox(label="Mask schedule", lines=1, value = da.mask_schedule, interactive=True) |
| with gr.Row(variant='compact'): |
| use_noise_mask = gr.Checkbox(label="Use noise mask", value=da.use_noise_mask, interactive=True) |
| with gr.Row(variant='compact'): |
| noise_mask_schedule = gr.Textbox(label="Noise mask schedule", lines=1, value = da.noise_mask_schedule, interactive=True) |
| |
| with gr.TabItem('Init'): |
| |
| with gr.Tab('Image Init'): |
| with gr.Row(variant='compact'): |
| with gr.Column(min_width=150): |
| use_init = gr.Checkbox(label="Use init", value=d.use_init, interactive=True, visible=True) |
| with gr.Column(min_width=150): |
| strength_0_no_init = gr.Checkbox(label="Strength 0 no init", value=d.strength_0_no_init, interactive=True) |
| with gr.Column(min_width=170): |
| strength = gr.Slider(label="Strength", minimum=0, maximum=1, step=0.01, value=d.strength, interactive=True) |
| with gr.Row(variant='compact'): |
| init_image = gr.Textbox(label="Init image", lines=1, interactive=True, value = d.init_image) |
| |
| with gr.Tab('Video Init'): |
| with gr.Row(variant='compact'): |
| video_init_path = gr.Textbox(label="Video init path", lines=1, value = da.video_init_path, interactive=True) |
| with gr.Row(variant='compact'): |
| extract_from_frame = gr.Number(label="Extract from frame", value=da.extract_from_frame, interactive=True, precision=0) |
| extract_to_frame = gr.Number(label="Extract to frame", value=da.extract_to_frame, interactive=True, precision=0) |
| extract_nth_frame = gr.Number(label="Extract nth frame", value=da.extract_nth_frame, interactive=True, precision=0) |
| overwrite_extracted_frames = gr.Checkbox(label="Overwrite extracted frames", value=False, interactive=True) |
| use_mask_video = gr.Checkbox(label="Use mask video", value=False, interactive=True) |
| with gr.Row(variant='compact'): |
| video_mask_path = gr.Textbox(label="Video mask path", lines=1, value = da.video_mask_path, interactive=True) |
| |
| with gr.Tab('Mask Init'): |
| with gr.Row(variant='compact'): |
| use_mask = gr.Checkbox(label="Use mask", value=d.use_mask, interactive=True) |
| use_alpha_as_mask = gr.Checkbox(label="Use alpha as mask", value=d.use_alpha_as_mask, interactive=True) |
| invert_mask = gr.Checkbox(label="Invert mask", value=d.invert_mask, interactive=True) |
| overlay_mask = gr.Checkbox(label="Overlay mask", value=d.overlay_mask, interactive=True) |
| with gr.Row(variant='compact'): |
| mask_file = gr.Textbox(label="Mask file", lines=1, interactive=True, value = d.mask_file) |
| with gr.Row(variant='compact'): |
| mask_overlay_blur = gr.Slider(label="Mask overlay blur", minimum=0, maximum=64, step=1, value=d.mask_overlay_blur, interactive=True) |
| with gr.Row(variant='compact'): |
| choice = mask_fill_choices[d.fill] |
| fill = gr.Radio(label='Mask fill', choices=mask_fill_choices, value=choice, type="index") |
| with gr.Row(variant='compact'): |
| full_res_mask = gr.Checkbox(label="Full res mask", value=d.full_res_mask, interactive=True) |
| full_res_mask_padding = gr.Slider(minimum=0, maximum=512, step=1, label="Full res mask padding", value=d.full_res_mask_padding, interactive=True) |
| with gr.Row(variant='compact'): |
| with gr.Column(min_width=240): |
| mask_contrast_adjust = gr.Number(label="Mask contrast adjust", value=d.mask_contrast_adjust, interactive=True) |
| with gr.Column(min_width=250): |
| mask_brightness_adjust = gr.Number(label="Mask brightness adjust", value=d.mask_brightness_adjust, interactive=True) |
| |
| with gr.Accordion('Parseq', open=False): |
| gr.HTML(""" |
| <p>Use a <a style='color:SteelBlue;' target='_blank' href='https://sd-parseq.web.app/deforum'>Parseq</a> manifest for your animation (leave blank to ignore).</p> |
| <p style="margin-top:1em; margin-bottom:1em;"> |
| Fields managed in your Parseq manifest override the values and schedules set in other parts of this UI. You can select which values to override by using the "Managed Fields" section in Parseq. |
| </p> |
| """) |
| with gr.Row(variant='compact'): |
| parseq_manifest = gr.Textbox(label="Parseq Manifest (JSON or URL)", lines=4, value = dp.parseq_manifest, interactive=True) |
| with gr.Row(variant='compact'): |
| parseq_use_deltas = gr.Checkbox(label="Use delta values for movement parameters", value=dp.parseq_use_deltas, interactive=True) |
| |
| with gr.TabItem('ControlNet'): |
| gr.HTML(controlnet_infotext()) |
| try: |
| controlnet_dict = setup_controlnet_ui() |
| except Exception as e: |
| raise Exception(e) |
| |
| with gr.TabItem('Hybrid Video'): |
| |
| hybrid_msg_html = gr.HTML(value='Please, change animation mode to 2D or 3D to enable Hybrid Mode',visible=False, elem_id='hybrid_msg_html') |
| |
| with gr.Accordion("Info & Help", open=False): |
| hybrid_html = "<p style=\"padding-bottom:0\"><b style=\"text-shadow: blue -1px -1px;\">Hybrid Video Compositing in 2D/3D Mode</b><span style=\"color:#DDD;font-size:0.7rem;text-shadow: black -1px -1px;margin-left:10px;\">by <a href=\"https://github.com/reallybigname\">reallybigname</a></span></p>" |
| hybrid_html += "<ul style=\"list-style-type:circle; margin-left:1em; margin-bottom:1em;\"><li>Composite video with previous frame init image in <b>2D or 3D animation_mode</b> <i>(not for Video Input mode)</i></li>" |
| hybrid_html += "<li>Uses your <b>Init</b> settings for <b>video_init_path, extract_nth_frame, overwrite_extracted_frames</b></li>" |
| hybrid_html += "<li>In Keyframes tab, you can also set <b>color_coherence</b> = '<b>Video Input</b>'</li>" |
| hybrid_html += "<li><b>color_coherence_video_every_N_frames</b> lets you only match every N frames</li>" |
| hybrid_html += "<li>Color coherence may be used with hybrid composite off, to just use video color.</li>" |
| hybrid_html += "<li>Hybrid motion may be used with hybrid composite off, to just use video motion.</li></ul>" |
| hybrid_html += "Hybrid Video Schedules" |
| hybrid_html += "<ul style=\"list-style-type:circle; margin-left:1em; margin-bottom:1em;\"><li>The alpha schedule controls overall alpha for video mix, whether using a composite mask or not.</li>" |
| hybrid_html += "<li>The <b>hybrid_comp_mask_blend_alpha_schedule</b> only affects the 'Blend' <b>hybrid_comp_mask_type</b>.</li>" |
| hybrid_html += "<li>Mask contrast schedule is from 0-255. Normal is 1. Affects all masks.</li>" |
| hybrid_html += "<li>Autocontrast low/high cutoff schedules 0-100. Low 0 High 100 is full range. <br>(<i><b>hybrid_comp_mask_auto_contrast</b> must be enabled</i>)</li></ul>" |
| hybrid_html += "<a style='color:SteelBlue;' target='_blank' href='https://github.com/deforum-art/deforum-for-automatic1111-webui/wiki/Animation-Settings#hybrid-video-mode-for-2d3d-animations'>Click Here</a> for more info/ a Guide." |
| gr.HTML(hybrid_html) |
| |
| with gr.Accordion("Hybrid Settings", open=True) as hybrid_settings_accord: |
| with gr.Row(variant='compact'): |
| hybrid_composite = gr.Radio(['None', 'Normal', 'Before Motion', 'After Generation'], label="Hybrid composite", value=da.hybrid_composite, elem_id="hybrid_composite") |
| with gr.Row(variant='compact'): |
| with gr.Column(min_width=340): |
| with gr.Row(variant='compact'): |
| hybrid_generate_inputframes = gr.Checkbox(label="Generate inputframes", value=da.hybrid_generate_inputframes, interactive=True) |
| hybrid_use_first_frame_as_init_image = gr.Checkbox(label="First frame as init image", value=da.hybrid_use_first_frame_as_init_image, interactive=True, visible=False) |
| hybrid_use_init_image = gr.Checkbox(label="Use init image as video", value=da.hybrid_use_init_image, interactive=True, visible=True) |
| with gr.Row(variant='compact'): |
| with gr.Column(variant='compact'): |
| with gr.Row(variant='compact'): |
| hybrid_motion = gr.Radio(['None', 'Optical Flow', 'Perspective', 'Affine'], label="Hybrid motion", value=da.hybrid_motion, elem_id="hybrid_motion") |
| with gr.Column(variant='compact'): |
| with gr.Row(variant='compact'): |
| with gr.Column(scale=1): |
| hybrid_flow_method = gr.Radio(['RAFT', 'DIS Medium', 'DIS Fine', 'Farneback'], label="Flow method", value=da.hybrid_flow_method, elem_id="hybrid_flow_method", visible=False) |
| with gr.Row(variant='compact'): |
| with gr.Column(variant='compact'): |
| hybrid_flow_consistency = gr.Checkbox(label="Flow consistency mask", value=da.hybrid_flow_consistency, interactive=True, visible=False) |
| hybrid_consistency_blur = gr.Slider(label="Consistency mask blur", minimum=0, maximum=16, step=1, value=da.hybrid_consistency_blur, interactive=True, visible=False) |
| with gr.Column(variant='compact'): |
| hybrid_motion_use_prev_img = gr.Checkbox(label="Motion use prev img", value=da.hybrid_motion_use_prev_img, interactive=True, visible=False) |
| with gr.Row(variant='compact'): |
| hybrid_comp_mask_type = gr.Radio(['None', 'Depth', 'Video Depth', 'Blend', 'Difference'], label="Comp mask type", value=da.hybrid_comp_mask_type, elem_id="hybrid_comp_mask_type", visible=False) |
| with gr.Row(visible=False, variant='compact') as hybrid_comp_mask_row: |
| hybrid_comp_mask_equalize = gr.Radio(['None', 'Before', 'After', 'Both'], label="Comp mask equalize", value=da.hybrid_comp_mask_equalize, elem_id="hybrid_comp_mask_equalize") |
| with gr.Column(variant='compact'): |
| hybrid_comp_mask_auto_contrast = gr.Checkbox(label="Comp mask auto contrast", value=False, interactive=True) |
| hybrid_comp_mask_inverse = gr.Checkbox(label="Comp mask inverse", value=da.hybrid_comp_mask_inverse, interactive=True) |
| with gr.Row(variant='compact'): |
| hybrid_comp_save_extra_frames = gr.Checkbox(label="Comp save extra frames", value=False, interactive=True) |
| |
| with gr.Accordion("Hybrid Schedules", open=False, visible=False) as hybrid_sch_accord: |
| with gr.Row(variant='compact') as hybrid_comp_alpha_schedule_row: |
| hybrid_comp_alpha_schedule = gr.Textbox(label="Comp alpha schedule", lines=1, value = da.hybrid_comp_alpha_schedule, interactive=True) |
| with gr.Row(variant='compact') as hybrid_flow_factor_schedule_row: |
| hybrid_flow_factor_schedule = gr.Textbox(label="Flow factor schedule", visible=False, lines=1, value = da.hybrid_flow_factor_schedule, interactive=True) |
| with gr.Row(variant='compact', visible=False) as hybrid_comp_mask_blend_alpha_schedule_row: |
| hybrid_comp_mask_blend_alpha_schedule = gr.Textbox(label="Comp mask blend alpha schedule", lines=1, value = da.hybrid_comp_mask_blend_alpha_schedule, interactive=True, elem_id="hybridelemtest") |
| with gr.Row(variant='compact', visible=False) as hybrid_comp_mask_contrast_schedule_row: |
| hybrid_comp_mask_contrast_schedule = gr.Textbox(label="Comp mask contrast schedule", lines=1, value = da.hybrid_comp_mask_contrast_schedule, interactive=True) |
| with gr.Row(variant='compact', visible=False) as hybrid_comp_mask_auto_contrast_cutoff_high_schedule_row : |
| hybrid_comp_mask_auto_contrast_cutoff_high_schedule = gr.Textbox(label="Comp mask auto contrast cutoff high schedule", lines=1, value = da.hybrid_comp_mask_auto_contrast_cutoff_high_schedule, interactive=True) |
| with gr.Row(variant='compact', visible=False) as hybrid_comp_mask_auto_contrast_cutoff_low_schedule_row: |
| hybrid_comp_mask_auto_contrast_cutoff_low_schedule = gr.Textbox(label="Comp mask auto contrast cutoff low schedule", lines=1, value = da.hybrid_comp_mask_auto_contrast_cutoff_low_schedule, interactive=True) |
| |
| with gr.Accordion("Humans Masking", open=False, visible=False) as humans_masking_accord: |
| with gr.Row(variant='compact'): |
| hybrid_generate_human_masks = gr.Radio(['None', 'PNGs', 'Video', 'Both'], label="Generate human masks", value=da.hybrid_generate_human_masks, elem_id="hybrid_generate_human_masks") |
| |
| with gr.TabItem('Output', elem_id='output_tab'): |
| |
| with gr.Accordion('Video Output Settings', open=True): |
| with gr.Row(variant='compact') as fps_out_format_row: |
| fps = gr.Slider(label="FPS", value=dv.fps, minimum=1, maximum=240, step=1) |
| with gr.Column(variant='compact'): |
| with gr.Row(variant='compact') as soundtrack_row: |
| add_soundtrack = gr.Radio(['None', 'File', 'Init Video'], label="Add soundtrack", value=dv.add_soundtrack, info="add audio to video from file/url or init video", elem_id="add_soundtrack") |
| soundtrack_path = gr.Textbox(label="Soundtrack path", lines=1, interactive=True, value = dv.soundtrack_path, info="abs. path or url to audio file") |
| |
| with gr.Row(variant='compact'): |
| skip_video_creation = gr.Checkbox(label="Skip video creation", value=dv.skip_video_creation, interactive=True, info="If enabled, only images will be saved") |
| delete_imgs = gr.Checkbox(label="Delete Imgs", value=dv.delete_imgs, interactive=True, info="auto-delete imgs when video is ready") |
| store_frames_in_ram = gr.Checkbox(label="Store frames in ram", value=dv.store_frames_in_ram, interactive=True, visible=False) |
| save_depth_maps = gr.Checkbox(label="Save depth maps", value=da.save_depth_maps, interactive=True, info="save animation's depth maps as extra files") |
| |
| make_gif = gr.Checkbox(label="Make GIF", value=dv.make_gif, interactive=True, info="make gif in addition to the video/s") |
| with gr.Row(equal_height=True, variant='compact', visible=True) as r_upscale_row: |
| r_upscale_video = gr.Checkbox(label="Upscale", value=dv.r_upscale_video, interactive=True, info="upscale output imgs when run is finished") |
| r_upscale_model = gr.Dropdown(label="Upscale model", choices=['realesr-animevideov3', 'realesrgan-x4plus', 'realesrgan-x4plus-anime'], interactive=True, value = dv.r_upscale_model, type="value") |
| r_upscale_factor = gr.Dropdown(choices=['x2', 'x3', 'x4'], label="Upscale factor", interactive=True, value=dv.r_upscale_factor, type="value") |
| r_upscale_keep_imgs = gr.Checkbox(label="Keep Imgs", value=dv.r_upscale_keep_imgs, interactive=True, info="don't delete upscaled imgs") |
| |
| with gr.Tab('Frame Interpolation') as frame_interp_tab: |
| with gr.Accordion('Important notes and Help', open=False, elem_id="f_interp_accord"): |
| gr.HTML(""" |
| Use <a href="https://github.com/megvii-research/ECCV2022-RIFE">RIFE</a> / <a href="https://film-net.github.io/">FILM</a> Frame Interpolation to smooth out, slow-mo (or both) any video.</p> |
| <p style="margin-top:1em"> |
| Supported engines: |
| <ul style="list-style-type:circle; margin-left:1em; margin-bottom:1em"> |
| <li>RIFE v4.6 and FILM.</li> |
| </ul> |
| </p> |
| <p style="margin-top:1em"> |
| Important notes: |
| <ul style="list-style-type:circle; margin-left:1em; margin-bottom:1em"> |
| <li>Frame Interpolation will *not* run if any of the following are enabled: 'Store frames in ram' / 'Skip video for run all'.</li> |
| <li>Audio (if provided) will *not* be transferred to the interpolated video if Slow-Mo is enabled.</li> |
| <li>'add_soundtrack' and 'soundtrack_path' aren't being honoured in "Interpolate an existing video" mode. Original vid audio will be used instead with the same slow-mo rules above.</li> |
| <li>In "Interpolate existing pics" mode, FPS is determined *only* by output FPS slider. Audio will be added if requested even with slow-mo "enabled", as it does *nothing* in this mode.</li> |
| </ul> |
| </p> |
| """) |
| with gr.Column(variant='compact'): |
| with gr.Row(variant='compact'): |
| |
| with gr.Column(min_width=110, scale = 3): |
| frame_interpolation_engine = gr.Radio(['None','RIFE v4.6','FILM'], label="Engine", value=dv.frame_interpolation_engine, info="select the frame interpolation engine. hover on the options for more info") |
| with gr.Column(min_width=30, scale = 1): |
| frame_interpolation_slow_mo_enabled = gr.Checkbox(label="Slow Mo", elem_id="frame_interpolation_slow_mo_enabled", value=dv.frame_interpolation_slow_mo_enabled, interactive=True, visible=False) |
| with gr.Column(min_width=30, scale = 1): |
| |
| frame_interpolation_keep_imgs = gr.Checkbox(label="Keep Imgs", elem_id="frame_interpolation_keep_imgs", value=dv.frame_interpolation_keep_imgs, interactive=True, visible=False) |
| with gr.Row(variant='compact', visible=False) as frame_interp_amounts_row: |
| with gr.Column(min_width=180) as frame_interp_x_amount_column: |
| |
| frame_interpolation_x_amount = gr.Slider(minimum=2, maximum=10, step=1, label="Interp X", value=dv.frame_interpolation_x_amount, interactive=True) |
| with gr.Column(min_width=180, visible=False) as frame_interp_slow_mo_amount_column: |
| |
| frame_interpolation_slow_mo_amount = gr.Slider(minimum=2, maximum=10, step=1, label="Slow-Mo X", value=dv.frame_interpolation_x_amount, interactive=True) |
| with gr.Row(visible=False) as interp_existing_video_row: |
| |
| with gr.Accordion('Interpolate existing Video/ Images', open=False) as interp_existing_video_accord: |
| with gr.Row(variant='compact') as interpolate_upload_files_row: |
| |
| vid_to_interpolate_chosen_file = gr.File(label="Video to Interpolate", interactive=True, file_count="single", file_types=["video"], elem_id="vid_to_interpolate_chosen_file") |
| |
| pics_to_interpolate_chosen_file = gr.File(label="Pics to Interpolate", interactive=True, file_count="multiple", file_types=["image"], elem_id="pics_to_interpolate_chosen_file") |
| with gr.Row(variant='compact', visible=False) as interp_live_stats_row: |
| |
| in_vid_frame_count_window = gr.Textbox(label="In Frame Count", lines=1, interactive=False, value='---') |
| |
| in_vid_fps_ui_window = gr.Textbox(label="In FPS", lines=1, interactive=False, value='---') |
| |
| out_interp_vid_estimated_fps = gr.Textbox(label="Interpolated Vid FPS", value='---') |
| with gr.Row(variant='compact') as interp_buttons_row: |
| |
| interpolate_button = gr.Button(value="*Interpolate Video*") |
| interpolate_pics_button = gr.Button(value="*Interpolate Pics*") |
| |
| gr.HTML("* check your CLI for outputs *", elem_id="below_interpolate_butts_msg") |
| |
| interpolate_button.click(upload_vid_to_interpolate,inputs=[vid_to_interpolate_chosen_file, frame_interpolation_engine, frame_interpolation_x_amount, frame_interpolation_slow_mo_enabled, frame_interpolation_slow_mo_amount, frame_interpolation_keep_imgs, in_vid_fps_ui_window]) |
| interpolate_pics_button.click(upload_pics_to_interpolate,inputs=[pics_to_interpolate_chosen_file, frame_interpolation_engine, frame_interpolation_x_amount, frame_interpolation_slow_mo_enabled, frame_interpolation_slow_mo_amount, frame_interpolation_keep_imgs, fps, add_soundtrack, soundtrack_path]) |
| |
| with gr.TabItem('Video Upscaling'): |
| vid_to_upscale_chosen_file = gr.File(label="Video to Upscale", interactive=True, file_count="single", file_types=["video"], elem_id="vid_to_upscale_chosen_file") |
| with gr.Column(): |
| |
| with gr.Row(variant='compact') as ncnn_upload_vid_stats_row: |
| ncnn_upscale_in_vid_frame_count_window = gr.Textbox(label="In Frame Count", lines=1, interactive=False, value='---') |
| ncnn_upscale_in_vid_fps_ui_window = gr.Textbox(label="In FPS", lines=1, interactive=False, value='---') |
| ncnn_upscale_in_vid_res = gr.Textbox(label="In Res", lines=1, interactive=False, value='---') |
| ncnn_upscale_out_vid_res = gr.Textbox(label="Out Res", value='---') |
| with gr.Column(): |
| with gr.Row(variant='compact', visible=True) as ncnn_actual_upscale_row: |
| ncnn_upscale_model = gr.Dropdown(label="Upscale model", choices=['realesr-animevideov3', 'realesrgan-x4plus', 'realesrgan-x4plus-anime'], interactive=True, value = "realesr-animevideov3", type="value") |
| ncnn_upscale_factor = gr.Dropdown(choices=['x2', 'x3', 'x4'], label="Upscale factor", interactive=True, value="x2", type="value") |
| ncnn_upscale_keep_imgs = gr.Checkbox(label="Keep Imgs", value=True, interactive=True) |
| ncnn_upscale_btn = gr.Button(value="*Upscale uploaded video*") |
| ncnn_upscale_btn.click(ncnn_upload_vid_to_upscale,inputs=[vid_to_upscale_chosen_file, ncnn_upscale_in_vid_fps_ui_window, ncnn_upscale_in_vid_res, ncnn_upscale_out_vid_res, ncnn_upscale_model, ncnn_upscale_factor, ncnn_upscale_keep_imgs]) |
| with gr.Column(visible=False): |
| selected_tab = gr.State(value=0) |
| with gr.Tabs(elem_id="extras_resize_mode"): |
| with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by: |
| upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=2, elem_id="extras_upscaling_resize") |
| with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to: |
| with FormRow(): |
| upscaling_resize_w = gr.Slider(label="Width", minimum=1, maximum=7680, step=1, value=512, elem_id="extras_upscaling_resize_w") |
| upscaling_resize_h = gr.Slider(label="Height", minimum=1, maximum=7680, step=1, value=512, elem_id="extras_upscaling_resize_h") |
| upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop") |
| with FormRow(): |
| extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in sh.sd_upscalers], value=sh.sd_upscalers[3].name) |
| extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in sh.sd_upscalers], value=sh.sd_upscalers[0].name) |
| with FormRow(): |
| with gr.Column(scale=3): |
| extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility") |
| with gr.Column(scale=1, min_width=80): |
| upscale_keep_imgs = gr.Checkbox(label="Keep Imgs", elem_id="upscale_keep_imgs", value=True, interactive=True) |
| tab_scale_by.select(fn=lambda: 0, inputs=[], outputs=[selected_tab]) |
| tab_scale_to.select(fn=lambda: 1, inputs=[], outputs=[selected_tab]) |
| |
| upscale_btn = gr.Button(value="*Upscale uploaded video*") |
| |
| gr.HTML("* check your CLI for outputs") |
| |
| |
| with gr.TabItem('Vid2depth'): |
| vid_to_depth_chosen_file = gr.File(label="Video to get Depth from", interactive=True, file_count="single", file_types=["video"], elem_id="vid_to_depth_chosen_file") |
| with gr.Row(variant='compact'): |
| mode = gr.Dropdown(label='Mode', elem_id="mode", choices=['Depth (Midas/Adabins)', 'Anime Remove Background', 'Mixed', 'None (just grayscale)'], value='Depth (Midas/Adabins)') |
| threshold_value = gr.Slider(label="Threshold Value Lower", value=127, minimum=0, maximum=255, step=1) |
| threshold_value_max = gr.Slider(label="Threshold Value Upper", value=255, minimum=0, maximum=255, step=1) |
| with gr.Row(variant='compact'): |
| thresholding = gr.Radio(['None', 'Simple', 'Simple (Auto-value)', 'Adaptive (Mean)', 'Adaptive (Gaussian)'], label="Thresholding Mode", value='None') |
| with gr.Row(variant='compact'): |
| adapt_block_size = gr.Number(label="Block size", value=11) |
| adapt_c = gr.Number(label="C", value=2) |
| invert = gr.Checkbox(label='Closer is brighter', value=True, elem_id="invert") |
| with gr.Row(variant='compact'): |
| end_blur = gr.Slider(label="End blur width", value=0, minimum=0, maximum=255, step=1) |
| midas_weight_vid2depth = gr.Slider(label="MiDaS weight (vid2depth)", value=da.midas_weight, minimum=0, maximum=1, step=0.05, interactive=True, info="sets a midpoint at which a depthmap is to be drawn: range [-1 to +1]") |
| depth_keep_imgs = gr.Checkbox(label='Keep Imgs', value=True, elem_id="depth_keep_imgs") |
| with gr.Row(variant='compact'): |
| |
| depth_btn = gr.Button(value="*Get depth from uploaded video*") |
| with gr.Row(variant='compact'): |
| |
| gr.HTML("* check your CLI for outputs") |
| |
| depth_btn.click(upload_vid_to_depth,inputs=[vid_to_depth_chosen_file, mode, thresholding, threshold_value, threshold_value_max, adapt_block_size, adapt_c, invert, end_blur, midas_weight_vid2depth, depth_keep_imgs]) |
| |
| with gr.TabItem('Frames to Video') as stitch_imgs_to_vid_row: |
| gr.HTML(""" |
| <p style="margin-top:0em"> |
| Important Notes: |
| <ul style="list-style-type:circle; margin-left:1em; margin-bottom:0.25em"> |
| <li>Enter relative to webui folder or Full-Absolute path, and make sure it ends with something like this: '20230124234916_%09d.png', just replace 20230124234916 with your batch ID. The %09d is important, don't forget it!</li> |
| <li>In the filename, '%09d' represents the 9 counting numbers, For '20230124234916_000000001.png', use '20230124234916_%09d.png'</li> |
| <li>If non-deforum frames, use the correct number of counting digits. For files like 'bunnies-0000.jpg', you'd use 'bunnies-%04d.jpg'</li> |
| </ul> |
| """) |
| with gr.Row(variant='compact'): |
| image_path = gr.Textbox(label="Image path", lines=1, interactive=True, value = dv.image_path) |
| ffmpeg_stitch_imgs_but = gr.Button(value="*Stitch frames to video*") |
| ffmpeg_stitch_imgs_but.click(direct_stitch_vid_from_frames,inputs=[image_path, fps, add_soundtrack, soundtrack_path]) |
| |
| with gr.Accordion(visible=False, label='INVISIBLE') as not_in_use_accordion: |
| perlin_w = gr.Slider(label="Perlin W", minimum=0.1, maximum=16, step=0.1, value=da.perlin_w, interactive=True) |
| perlin_h = gr.Slider(label="Perlin H", minimum=0.1, maximum=16, step=0.1, value=da.perlin_h, interactive=True) |
| save_settings = gr.Checkbox(label="save_settings", value=d.save_settings, interactive=True) |
| seed_enable_extras = gr.Checkbox(label="Enable subseed controls", value=False) |
| save_sample_per_step = gr.Checkbox(label="Save sample per step", value=d.save_sample_per_step, interactive=True) |
| |
| show_info_on_ui.change(fn=change_css, inputs=show_info_on_ui, outputs = gr.outputs.HTML()) |
| |
| fps.change(fn=change_gif_button_visibility, inputs=fps, outputs=make_gif) |
| r_upscale_model.change(fn=update_r_upscale_factor, inputs=r_upscale_model, outputs=r_upscale_factor) |
| ncnn_upscale_model.change(fn=update_r_upscale_factor, inputs=ncnn_upscale_model, outputs=ncnn_upscale_factor) |
| ncnn_upscale_model.change(update_upscale_out_res_by_model_name, inputs=[ncnn_upscale_in_vid_res, ncnn_upscale_model], outputs=ncnn_upscale_out_vid_res) |
| ncnn_upscale_factor.change(update_upscale_out_res, inputs=[ncnn_upscale_in_vid_res, ncnn_upscale_factor], outputs=ncnn_upscale_out_vid_res) |
| vid_to_upscale_chosen_file.change(vid_upscale_gradio_update_stats,inputs=[vid_to_upscale_chosen_file, ncnn_upscale_factor],outputs=[ncnn_upscale_in_vid_fps_ui_window, ncnn_upscale_in_vid_frame_count_window, ncnn_upscale_in_vid_res, ncnn_upscale_out_vid_res]) |
| animation_mode.change(fn=change_max_frames_visibility, inputs=animation_mode, outputs=max_frames) |
| diffusion_cadence_outputs = [diffusion_cadence,guided_images_accord,optical_flow_cadence_row,cadence_flow_factor_schedule, |
| optical_flow_redo_generation,redo_flow_factor_schedule,diffusion_redo] |
| for output in diffusion_cadence_outputs: |
| animation_mode.change(fn=change_diffusion_cadence_visibility, inputs=animation_mode, outputs=output) |
| three_d_related_outputs = [only_3d_motion_column, depth_warp_row_1, depth_warp_row_2, depth_warp_row_3, depth_warp_row_4, depth_warp_row_5, depth_warp_row_6, depth_warp_row_7] |
| for output in three_d_related_outputs: |
| animation_mode.change(fn=disble_3d_related_stuff, inputs=animation_mode, outputs=output) |
| pers_flip_outputs = [per_f_th_row, per_f_ph_row, per_f_ga_row, per_f_f_row] |
| for output in pers_flip_outputs: |
| enable_perspective_flip.change(fn=hide_if_false,inputs=enable_perspective_flip,outputs=output) |
| animation_mode.change(fn=only_show_in_non_3d_mode, inputs=animation_mode, outputs=depth_warp_msg_html) |
| animation_mode.change(fn=enable_2d_related_stuff, inputs=animation_mode, outputs=only_2d_motion_column) |
| animation_mode.change(fn=disable_by_interpolation, inputs=animation_mode, outputs=color_force_grayscale) |
| animation_mode.change(fn=disable_by_interpolation, inputs=animation_mode, outputs=noise_tab_column) |
| pers_flip_hide_all_param_names = [per_f_th_row, per_f_ph_row, per_f_ga_row, per_f_f_row] |
| for output in pers_flip_hide_all_param_names: |
| animation_mode.change(fn=per_flip_handle, inputs=[animation_mode, enable_perspective_flip], outputs=output) |
| |
| animation_mode.change(fn=disable_pers_flip_accord, inputs=animation_mode, outputs=enable_per_f_row) |
| animation_mode.change(fn=disable_pers_flip_accord, inputs=animation_mode, outputs=both_anim_mode_motion_params_column) |
| aspect_ratio_use_old_formula.change(fn=hide_if_true, inputs=aspect_ratio_use_old_formula, outputs=aspect_ratio_schedule) |
| |
| animation_mode.change(fn=show_hybrid_html_msg, inputs=animation_mode, outputs=hybrid_msg_html) |
| animation_mode.change(fn=change_hybrid_tab_status, inputs=animation_mode, outputs=hybrid_sch_accord) |
| animation_mode.change(fn=change_hybrid_tab_status, inputs=animation_mode, outputs=hybrid_settings_accord) |
| animation_mode.change(fn=change_hybrid_tab_status, inputs=animation_mode, outputs=humans_masking_accord) |
| optical_flow_redo_generation.change(fn=hide_if_none, inputs=optical_flow_redo_generation, outputs=redo_flow_factor_schedule_column) |
| override_settings_with_file.change(fn=hide_if_false, inputs=override_settings_with_file,outputs=custom_settings_file) |
| hybrid_comp_mask_type.change(fn=hide_if_none, inputs=hybrid_comp_mask_type, outputs=hybrid_comp_mask_row) |
| hybrid_motion_outputs = [hybrid_flow_method, hybrid_flow_factor_schedule, hybrid_flow_consistency, hybrid_consistency_blur, hybrid_motion_use_prev_img] |
| for output in hybrid_motion_outputs: |
| hybrid_motion.change(fn=disable_by_non_optical_flow, inputs=hybrid_motion, outputs=output) |
| hybrid_flow_consistency.change(fn=hide_if_false, inputs=hybrid_flow_consistency, outputs=hybrid_consistency_blur) |
| optical_flow_cadence.change(fn=hide_if_none, inputs=optical_flow_cadence, outputs=cadence_flow_factor_schedule_column) |
| hybrid_composite.change(fn=disable_by_hybrid_composite_dynamic, inputs=[hybrid_composite, hybrid_comp_mask_type], outputs=hybrid_comp_mask_row) |
| hybrid_composite_outputs = [humans_masking_accord, hybrid_sch_accord, hybrid_comp_mask_type, hybrid_use_first_frame_as_init_image, hybrid_use_init_image] |
| for output in hybrid_composite_outputs: |
| hybrid_composite.change(fn=hide_if_false, inputs=hybrid_composite, outputs=output) |
| hybrid_comp_mask_type_outputs = [hybrid_comp_mask_blend_alpha_schedule_row, hybrid_comp_mask_contrast_schedule_row, hybrid_comp_mask_auto_contrast_cutoff_high_schedule_row, hybrid_comp_mask_auto_contrast_cutoff_low_schedule_row] |
| for output in hybrid_comp_mask_type_outputs: |
| hybrid_comp_mask_type.change(fn=hide_if_none, inputs=hybrid_comp_mask_type, outputs=output) |
| |
| seed_behavior.change(fn=change_seed_iter_visibility, inputs=seed_behavior, outputs=seed_iter_N_row) |
| seed_behavior.change(fn=change_seed_schedule_visibility, inputs=seed_behavior, outputs=seed_schedule_row) |
| color_coherence.change(fn=change_color_coherence_video_every_N_frames_visibility, inputs=color_coherence, outputs=color_coherence_video_every_N_frames_row) |
| color_coherence.change(fn=change_color_coherence_image_path_visibility, inputs=color_coherence, outputs=color_coherence_image_path_row) |
| noise_type.change(fn=change_perlin_visibility, inputs=noise_type, outputs=perlin_row) |
| skip_video_creation_outputs = [fps_out_format_row, soundtrack_row, store_frames_in_ram, make_gif, r_upscale_row, delete_imgs] |
| for output in skip_video_creation_outputs: |
| skip_video_creation.change(fn=change_visibility_from_skip_video, inputs=skip_video_creation, outputs=output) |
| frame_interpolation_slow_mo_enabled.change(fn=hide_if_false,inputs=frame_interpolation_slow_mo_enabled,outputs=frame_interp_slow_mo_amount_column) |
| frame_interpolation_engine.change(fn=change_interp_x_max_limit,inputs=[frame_interpolation_engine,frame_interpolation_x_amount],outputs=frame_interpolation_x_amount) |
| [change_fn.change(set_interp_out_fps, inputs=[frame_interpolation_x_amount, frame_interpolation_slow_mo_enabled, frame_interpolation_slow_mo_amount, in_vid_fps_ui_window], outputs=out_interp_vid_estimated_fps) for change_fn in [frame_interpolation_x_amount, frame_interpolation_slow_mo_amount, frame_interpolation_slow_mo_enabled]] |
| |
| vid_to_interpolate_chosen_file.change(gradio_f_interp_get_fps_and_fcount,inputs=[vid_to_interpolate_chosen_file, frame_interpolation_x_amount, frame_interpolation_slow_mo_enabled, frame_interpolation_slow_mo_amount],outputs=[in_vid_fps_ui_window,in_vid_frame_count_window, out_interp_vid_estimated_fps]) |
| vid_to_interpolate_chosen_file.change(fn=hide_interp_stats,inputs=[vid_to_interpolate_chosen_file],outputs=[interp_live_stats_row]) |
| interp_hide_list = [frame_interpolation_slow_mo_enabled,frame_interpolation_keep_imgs,frame_interp_amounts_row,interp_existing_video_row] |
| for output in interp_hide_list: |
| frame_interpolation_engine.change(fn=hide_interp_by_interp_status,inputs=frame_interpolation_engine,outputs=output) |
| diffusion_cadence.change(fn=hide_optical_flow_cadence, inputs=diffusion_cadence,outputs=optical_flow_cadence_row) |
| depth_algorithm.change(fn=legacy_3d_mode, inputs=depth_algorithm, outputs=midas_weight) |
| depth_algorithm.change(fn=show_leres_html_msg, inputs=depth_algorithm, outputs=leres_license_msg) |
| ddim_outputs = [enable_ddim_eta_scheduling] |
| for output in ddim_outputs: |
| sampler.change(fn=show_when_ddim,inputs=sampler,outputs=output) |
| ancestral_outputs = [enable_ancestral_eta_scheduling] |
| for output in ancestral_outputs: |
| sampler.change(fn=show_when_ancestral_samplers,inputs=sampler,outputs=output) |
| enable_ancestral_eta_scheduling.change(fn=hide_if_false,inputs=enable_ancestral_eta_scheduling,outputs=ancestral_eta_schedule) |
| enable_ddim_eta_scheduling.change(fn=hide_if_false,inputs=enable_ddim_eta_scheduling,outputs=ddim_eta_schedule) |
| |
| stuff = locals() |
| stuff = {**stuff, **controlnet_dict} |
| stuff.pop('controlnet_dict') |
| return stuff |
|
|
| |
| |
| |
| |
| |
| |
| |
| |
| |
|
|
| anim_args_names = str(r'''animation_mode, max_frames, border, |
| angle, zoom, translation_x, translation_y, translation_z, transform_center_x, transform_center_y, |
| rotation_3d_x, rotation_3d_y, rotation_3d_z, |
| enable_perspective_flip, enable_ddim_eta_scheduling, ddim_eta_schedule, enable_ancestral_eta_scheduling, ancestral_eta_schedule, |
| perspective_flip_theta, perspective_flip_phi, perspective_flip_gamma, perspective_flip_fv, |
| noise_schedule, strength_schedule, contrast_schedule, cfg_scale_schedule, pix2pix_img_cfg_scale_schedule, |
| enable_subseed_scheduling, subseed_schedule, subseed_strength_schedule, |
| enable_steps_scheduling, steps_schedule, |
| fov_schedule, aspect_ratio_schedule, aspect_ratio_use_old_formula, near_schedule, far_schedule, |
| seed_schedule, |
| enable_sampler_scheduling, sampler_schedule, |
| mask_schedule, use_noise_mask, noise_mask_schedule, |
| enable_checkpoint_scheduling, checkpoint_schedule, |
| enable_clipskip_scheduling, clipskip_schedule, enable_noise_multiplier_scheduling, noise_multiplier_schedule, |
| kernel_schedule, sigma_schedule, amount_schedule, threshold_schedule, |
| color_coherence, color_coherence_image_path, color_coherence_video_every_N_frames, color_force_grayscale, legacy_colormatch, |
| diffusion_cadence, optical_flow_cadence, cadence_flow_factor_schedule, |
| optical_flow_redo_generation, redo_flow_factor_schedule, diffusion_redo, |
| noise_type, perlin_w, perlin_h, perlin_octaves, perlin_persistence, |
| use_depth_warping, depth_algorithm ,midas_weight, |
| padding_mode, sampling_mode, save_depth_maps, |
| video_init_path, extract_nth_frame, extract_from_frame, extract_to_frame, overwrite_extracted_frames, |
| use_mask_video, video_mask_path, |
| resume_from_timestring, resume_timestring''' |
| ).replace("\n", "").replace("\r", "").replace(" ", "").split(',') |
| hybrid_args_names = str(r'''hybrid_generate_inputframes, hybrid_generate_human_masks, hybrid_use_first_frame_as_init_image, |
| hybrid_motion, hybrid_motion_use_prev_img, hybrid_flow_consistency, hybrid_consistency_blur, hybrid_flow_method, hybrid_composite, |
| hybrid_use_init_image, hybrid_comp_mask_type, hybrid_comp_mask_inverse, |
| hybrid_comp_mask_equalize, hybrid_comp_mask_auto_contrast, hybrid_comp_save_extra_frames, |
| hybrid_comp_alpha_schedule, hybrid_flow_factor_schedule, |
| hybrid_comp_mask_blend_alpha_schedule, hybrid_comp_mask_contrast_schedule, |
| hybrid_comp_mask_auto_contrast_cutoff_high_schedule, hybrid_comp_mask_auto_contrast_cutoff_low_schedule''' |
| ).replace("\n", "").replace("\r", "").replace(" ", "").split(',') |
| args_names = str(r'''W, H, tiling, restore_faces, seed, sampler, seed_enable_extras, |
| seed_resize_from_w, seed_resize_from_h, steps, n_batch, save_settings, |
| save_sample_per_step, batch_name, seed_behavior, seed_iter_N, use_init, strength_0_no_init, strength, init_image, |
| use_mask, use_alpha_as_mask, invert_mask, overlay_mask, |
| mask_file, mask_contrast_adjust, mask_brightness_adjust, mask_overlay_blur, |
| fill, full_res_mask, full_res_mask_padding, reroll_blank_frames,reroll_patience''' |
| ).replace("\n", "").replace("\r", "").replace(" ", "").split(',') |
| video_args_names = str(r'''skip_video_creation, |
| fps, make_gif, delete_imgs, add_soundtrack, soundtrack_path, r_upscale_video, r_upscale_model, r_upscale_factor, r_upscale_keep_imgs, |
| store_frames_in_ram, frame_interpolation_engine, frame_interpolation_x_amount, frame_interpolation_slow_mo_enabled, frame_interpolation_slow_mo_amount, frame_interpolation_keep_imgs''' |
| ).replace("\n", "").replace("\r", "").replace(" ", "").split(',') |
| parseq_args_names = str(r'''parseq_manifest, parseq_use_deltas''' |
| ).replace("\n", "").replace("\r", "").replace(" ", "").split(',') |
| loop_args_names = str(r'''use_looper, init_images, image_strength_schedule, blendFactorMax, blendFactorSlope, |
| tweening_frames_schedule, color_correction_factor''' |
| ).replace("\n", "").replace("\r", "").replace(" ", "").split(',') |
|
|
| def get_component_names(): |
| return ['override_settings_with_file', 'custom_settings_file'] + anim_args_names +['animation_prompts', 'animation_prompts_positive', 'animation_prompts_negative'] + args_names + video_args_names + parseq_args_names + hybrid_args_names + loop_args_names + controlnet_component_names() |
|
|
| def get_settings_component_names(): |
| return [name for name in get_component_names()] |
|
|
| def setup_deforum_setting_ui(self, is_img2img, is_extension = True): |
| ds = setup_deforum_setting_dictionary(self, is_img2img, is_extension) |
| return [ds[name] for name in (['btn'] + get_component_names())] |
|
|
| def pack_anim_args(args_dict): |
| return {name: args_dict[name] for name in (anim_args_names + hybrid_args_names)} |
|
|
| def pack_args(args_dict): |
| args_dict = {name: args_dict[name] for name in args_names} |
| args_dict['precision'] = 'autocast' |
| args_dict['scale'] = 7 |
| args_dict['subseed'] = -1 |
| args_dict['subseed_strength'] = 0 |
| args_dict['C'] = 4 |
| args_dict['f'] = 8 |
| args_dict['timestring'] = "" |
| args_dict['init_sample'] = None |
| args_dict['noise_mask'] = None |
| args_dict['seed_internal'] = 0 |
| return args_dict |
| |
| def pack_video_args(args_dict): |
| return {name: args_dict[name] for name in video_args_names} |
|
|
| def pack_parseq_args(args_dict): |
| return {name: args_dict[name] for name in parseq_args_names} |
| |
| def pack_loop_args(args_dict): |
| return {name: args_dict[name] for name in loop_args_names} |
|
|
| def pack_controlnet_args(args_dict): |
| return {name: args_dict[name] for name in controlnet_component_names()} |
|
|
| def process_args(args_dict_main, run_id): |
| from deforum_helpers.settings import load_args |
| override_settings_with_file = args_dict_main['override_settings_with_file'] |
| custom_settings_file = args_dict_main['custom_settings_file'] |
| args_dict = pack_args(args_dict_main) |
| anim_args_dict = pack_anim_args(args_dict_main) |
| video_args_dict = pack_video_args(args_dict_main) |
| parseq_args_dict = pack_parseq_args(args_dict_main) |
| loop_args_dict = pack_loop_args(args_dict_main) |
| controlnet_args_dict = pack_controlnet_args(args_dict_main) |
|
|
| import json |
| |
| root = SimpleNamespace(**Root()) |
| root.p = args_dict_main['p'] |
| p = root.p |
| root.animation_prompts = json.loads(args_dict_main['animation_prompts']) |
| |
| args_loaded_ok = True |
| if override_settings_with_file: |
| args_loaded_ok = load_args(args_dict_main, args_dict, anim_args_dict, parseq_args_dict, loop_args_dict, controlnet_args_dict, video_args_dict, custom_settings_file, root, run_id) |
| |
| positive_prompts = args_dict_main['animation_prompts_positive'] |
| negative_prompts = args_dict_main['animation_prompts_negative'] |
| negative_prompts = negative_prompts.replace('--neg', '') |
| for key in root.animation_prompts: |
| animationPromptCurr = root.animation_prompts[key] |
| root.animation_prompts[key] = f"{positive_prompts} {animationPromptCurr} {'' if '--neg' in animationPromptCurr else '--neg'} {negative_prompts}" |
| root.positive_prompts = positive_prompts |
| root.negative_prompts = negative_prompts |
| |
| if not os.path.exists(root.models_path): |
| os.mkdir(root.models_path) |
|
|
| args = SimpleNamespace(**args_dict) |
| anim_args = SimpleNamespace(**anim_args_dict) |
| video_args = SimpleNamespace(**video_args_dict) |
| parseq_args = SimpleNamespace(**parseq_args_dict) |
| loop_args = SimpleNamespace(**loop_args_dict) |
| controlnet_args = SimpleNamespace(**controlnet_args_dict) |
|
|
| p.width, p.height = map(lambda x: x - x % 8, (args.W, args.H)) |
| p.steps = args.steps |
| p.seed = args.seed |
| p.sampler_name = args.sampler |
| p.batch_size = args.n_batch |
| p.tiling = args.tiling |
| p.restore_faces = args.restore_faces |
| p.seed_enable_extras = args.seed_enable_extras |
| p.subseed = args.subseed |
| p.subseed_strength = args.subseed_strength |
| p.seed_resize_from_w = args.seed_resize_from_w |
| p.seed_resize_from_h = args.seed_resize_from_h |
| p.fill = args.fill |
| if args.seed == -1: |
| root.raw_seed = -1 |
| args.seed = get_fixed_seed(args.seed) |
| if root.raw_seed != -1: |
| root.raw_seed = args.seed |
| args.timestring = time.strftime('%Y%m%d%H%M%S') |
| args.strength = max(0.0, min(1.0, args.strength)) |
| args.prompts = json.loads(args_dict_main['animation_prompts']) |
| args.positive_prompts = args_dict_main['animation_prompts_positive'] |
| args.negative_prompts = args_dict_main['animation_prompts_negative'] |
|
|
| if not args.use_init and not anim_args.hybrid_use_init_image: |
| args.init_image = None |
| |
| if anim_args.animation_mode == 'None': |
| anim_args.max_frames = 1 |
| elif anim_args.animation_mode == 'Video Input': |
| args.use_init = True |
| |
| current_arg_list = [args, anim_args, video_args, parseq_args] |
| full_base_folder_path = os.path.join(os.getcwd(), p.outpath_samples) |
| root.raw_batch_name = args.batch_name |
| args.batch_name = substitute_placeholders(args.batch_name, current_arg_list, full_base_folder_path) |
| args.outdir = os.path.join(p.outpath_samples, str(args.batch_name)) |
| root.outpath_samples = args.outdir |
| args.outdir = os.path.join(os.getcwd(), args.outdir) |
| if not os.path.exists(args.outdir): |
| os.makedirs(args.outdir) |
| |
| return args_loaded_ok, root, args, anim_args, video_args, parseq_args, loop_args, controlnet_args |
| |
| |
| def upload_vid_to_interpolate(file, engine, x_am, sl_enabled, sl_am, keep_imgs, in_vid_fps): |
| |
| if not file or engine == 'None': |
| return print("Please upload a video and set a proper value for 'Interp X'. Can't interpolate x0 times :)") |
| f_location, f_crf, f_preset = get_ffmpeg_params() |
|
|
| root_params = Root() |
| f_models_path = root_params['models_path'] |
|
|
| process_interp_vid_upload_logic(file, engine, x_am, sl_enabled, sl_am, keep_imgs, f_location, f_crf, f_preset, in_vid_fps, f_models_path, file.orig_name) |
|
|
| def upload_pics_to_interpolate(pic_list, engine, x_am, sl_enabled, sl_am, keep_imgs, fps, add_audio, audio_track): |
| from PIL import Image |
| |
| if pic_list is None or len(pic_list) < 2: |
| return print("Please upload at least 2 pics for interpolation.") |
| f_location, f_crf, f_preset = get_ffmpeg_params() |
| |
| pic_sizes = [Image.open(picture_path.name).size for picture_path in pic_list] |
| if len(set(pic_sizes)) != 1: |
| return print("All uploaded pics need to be of the same Width and Height / resolution.") |
| |
| resolution = pic_sizes[0] |
| |
| root_params = Root() |
| f_models_path = root_params['models_path'] |
| |
| process_interp_pics_upload_logic(pic_list, engine, x_am, sl_enabled, sl_am, keep_imgs, f_location, f_crf, f_preset, fps, f_models_path, resolution, add_audio, audio_track) |
|
|
| def upload_vid_to_depth(vid_to_depth_chosen_file, mode, thresholding, threshold_value, threshold_value_max, adapt_block_size, adapt_c, invert, end_blur, midas_weight_vid2depth, depth_keep_imgs): |
| |
| if not vid_to_depth_chosen_file: |
| return print("Please upload a video :()") |
| f_location, f_crf, f_preset = get_ffmpeg_params() |
| root_params = Root() |
| f_models_path = root_params['models_path'] |
| |
| process_depth_vid_upload_logic(vid_to_depth_chosen_file, mode, thresholding, threshold_value, threshold_value_max, adapt_block_size, adapt_c, invert, end_blur, midas_weight_vid2depth, vid_to_depth_chosen_file.orig_name, depth_keep_imgs, f_location, f_crf, f_preset, f_models_path) |
|
|
| def ncnn_upload_vid_to_upscale(vid_path, in_vid_fps, in_vid_res, out_vid_res, upscale_model, upscale_factor, keep_imgs): |
| if vid_path is None: |
| print("Please upload a video :)") |
| return |
| f_location, f_crf, f_preset = get_ffmpeg_params() |
| root_params = Root() |
| f_models_path = root_params['models_path'] |
| current_user = root_params['current_user_os'] |
| process_ncnn_upscale_vid_upload_logic(vid_path, in_vid_fps, in_vid_res, out_vid_res, f_models_path, upscale_model, upscale_factor, keep_imgs, f_location, f_crf, f_preset, current_user) |
|
|
