diff --git "a/scripts/deforum_helpers/args.py" "b/scripts/deforum_helpers/args.py" new file mode 100644--- /dev/null +++ "b/scripts/deforum_helpers/args.py" @@ -0,0 +1,1267 @@ +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' # ['None', '2D', '3D', 'Video Input', 'Interpolation'] + max_frames = 120 + border = 'replicate' # ['wrap', '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)" + # Sampler Scheduling + enable_sampler_scheduling = False + sampler_schedule = '0: ("Euler a")' + # Composable mask scheduling + use_noise_mask = False + mask_schedule = '0: ("{video_mask}")' + noise_mask_schedule = '0: ("{video_mask}")' + # Checkpoint Scheduling + enable_checkpoint_scheduling = False + checkpoint_schedule = '0: ("model1.ckpt"), 100: ("model2.safetensors")' + # CLIP skip Scheduling + enable_clipskip_scheduling = False + clipskip_schedule = '0: (2)' + # Noise Multiplier Scheduling + enable_noise_multiplier_scheduling = True + noise_multiplier_schedule = '0: (1.05)' + # Anti-blur + amount_schedule = "0: (0.1)" + kernel_schedule = "0: (5)" + sigma_schedule = "0: (1.0)" + threshold_schedule = "0: (0.0)" + # Hybrid video + 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)" + #Coherence + color_coherence = 'LAB' # ['None', 'HSV', 'LAB', 'RGB', 'Video Input', 'Image'] + color_coherence_image_path = "" + color_coherence_video_every_N_frames = 1 + color_force_grayscale = False + legacy_colormatch = False + diffusion_cadence = '2' #['1','2','3','4','5','6','7','8'] + optical_flow_cadence = 'None' #['None', 'RAFT','DIS Medium', 'DIS Fine', 'Farneback'] + cadence_flow_factor_schedule = "0: (1)" + optical_flow_redo_generation = 'None' #['None', 'RAFT', 'DIS Medium', 'DIS Fine', 'Farneback'] + redo_flow_factor_schedule = "0: (1)" + diffusion_redo = '0' + #**Noise settings:** + noise_type = 'perlin' # ['uniform', 'perlin'] + # Perlin params + perlin_w = 8 + perlin_h = 8 + perlin_octaves = 4 + perlin_persistence = 0.5 + #**3D Depth Warping:** + use_depth_warping = True + depth_algorithm = 'Midas-3-Hybrid' # ['Midas+AdaBins (old)','Zoe+AdaBins (old)', 'Midas-3-Hybrid','Midas-3.1-BeitLarge', 'AdaBins', 'Zoe', 'Leres'] Midas-3.1-BeitLarge is temporarily removed 04-05-23 until fixed + midas_weight = 0.2 # midas/ zoe weight - only relevant in old/ legacy depth_algorithm modes. see above ^ + padding_mode = 'border' # ['border', 'reflection', 'zeros'] + sampling_mode = 'bicubic' # ['bicubic', 'bilinear', 'nearest'] + save_depth_maps = False + #**Video Input:** + video_init_path ='https://deforum.github.io/a1/V1.mp4' + extract_nth_frame = 1 + extract_from_frame = 0 + extract_to_frame = -1 # minus 1 for unlimited frames + overwrite_extracted_frames = True + use_mask_video = False + video_mask_path ='https://deforum.github.io/a1/VM1.mp4' + #**Hybrid Video for 2D/3D Animation Mode:** + hybrid_generate_inputframes = False + hybrid_generate_human_masks = "None" #['None','PNGs','Video', 'Both'] + hybrid_use_first_frame_as_init_image = True + hybrid_motion = "None" #['None','Optical Flow','Perspective','Affine'] + hybrid_motion_use_prev_img = False + hybrid_flow_consistency = False + hybrid_consistency_blur = 2 + hybrid_flow_method = "RAFT" #['RAFT', 'DIS Medium', 'DIS Fine', 'Farneback'] + hybrid_composite = 'None' #['None', 'Normal', 'Before Motion', 'After Generation'] + hybrid_use_init_image = False + hybrid_comp_mask_type = "None" #['None', 'Depth', 'Video Depth', 'Blend', 'Difference'] + hybrid_comp_mask_inverse = False + hybrid_comp_mask_equalize = "None" # ['None','Before','After','Both'] + hybrid_comp_mask_auto_contrast = False + hybrid_comp_save_extra_frames = False + #**Resume Animation:** + 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(): + #**Image Settings** + W = 512 # + H = 512 # + W, H = map(lambda x: x - x % 64, (W, H)) # resize to integer multiple of 64 + + show_info_on_ui = True + + #**Webui stuff** + tiling = False + restore_faces = False + seed_enable_extras = False + subseed = -1 + subseed_strength = 0 + seed_resize_from_w = 0 + seed_resize_from_h = 0 + + #**Sampling Settings** + seed = -1 # + sampler = 'euler_ancestral' # ["klms","dpm2","dpm2_ancestral","heun","euler","euler_ancestral","plms", "ddim"] + steps = 25 # + scale = 7 # + + dynamic_threshold = None + static_threshold = None + + #**Save & Display Settings** + save_settings = True + save_sample_per_step = False + + #**Prompt Settings** + prompt_weighting = False + normalize_prompt_weights = True + log_weighted_subprompts = False + + #**Batch Settings** + n_batch = 1 # + batch_name = "Deforum_{timestring}" + seed_behavior = "iter" # ["iter","fixed","random","ladder","alternate","schedule"] + seed_iter_N = 1 + outdir = "" + + #**Init Settings** + use_init = False + strength = 0.8 + strength_0_no_init = True # Set the strength to 0 automatically when no init image is used + init_image = "https://deforum.github.io/a1/I1.png" + # Whiter areas of the mask are areas that change more + use_mask = False + use_alpha_as_mask = False # use the alpha channel of the init image as the mask + mask_file = "https://deforum.github.io/a1/M1.jpg" + invert_mask = False + # Adjust mask image, 1.0 is no adjustment. Should be positive numbers. + mask_contrast_adjust = 1.0 + mask_brightness_adjust = 1.0 + # Overlay the masked image at the end of the generation so it does not get degraded by encoding and decoding + overlay_mask = True + # Blur edges of final overlay mask, if used. Minimum = 0 (no blur) + mask_overlay_blur = 4 + + fill = 1 #MASKARGSEXPANSION Todo : Rename and convert to same formatting as used in img2img masked content + full_res_mask = True + full_res_mask_padding = 4 + reroll_blank_frames = 'reroll' # reroll, interrupt, or ignore + reroll_patience = 10 + + n_samples = 1 # doesnt do anything + 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 # True will delete all imgs after a successful mp4 creation + image_path = "C:/SD/20230124234916_%09d.png" + mp4_path = "testvidmanualsettings.mp4" + add_soundtrack = 'None' # ["File","Init Video"] + soundtrack_path = "https://deforum.github.io/a1/A1.mp3" + # End-Run upscaling + r_upscale_video = False + r_upscale_factor = 'x2' # ['2x', 'x3', 'x4'] + r_upscale_model = 'realesr-animevideov3' # 'realesr-animevideov3' (default of realesrgan engine, does 2-4x), the rest do only 4x: 'realesrgan-x4plus', 'realesrgan-x4plus-anime' + r_upscale_keep_imgs = True + + store_frames_in_ram = False + #**Interpolate Video Settings** + frame_interpolation_engine = "None" # ["None", "RIFE v4.6", "FILM"] + frame_interpolation_x_amount = 2 # [2 to 1000 depends on the engine] + frame_interpolation_slow_mo_enabled = False + frame_interpolation_slow_mo_amount = 2 #[2 to 10] + frame_interpolation_keep_imgs = False + return locals() + +import gradio as gr +import time +from types import SimpleNamespace + +i1_store_backup = f"

Deforum extension for auto1111 — version 2.4b | Git commit: {get_deforum_version()}

" +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()) #default args + da = SimpleNamespace(**DeforumAnimArgs()) #default anim args + dp = SimpleNamespace(**ParseqArgs()) #default parseq ars + dv = SimpleNamespace(**DeforumOutputArgs()) #default video args + dr = SimpleNamespace(**Root()) # ROOT args + 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("") + # MAIN (TOP) EXTENSION INFO ACCORD + with gr.Accordion("Info, Links and Help", open=False, elem_id='main_top_info_accord'): + gr.HTML("""Made by deforum.github.io, port for AUTOMATIC1111's webui maintained by kabachuha & hithereai """) + gr.HTML("""FOR HELP CLICK HERE +
  • The code for this extension: here.
    • +
  • Join the official Deforum Discord to share your creations and suggestions.
    • +
  • Official Deforum Wiki: here.
    • +
  • Anime-inclined great guide (by FizzleDorf) with lots of examples: here.
    • +
  • For advanced keyframing with Math functions, see here.
    • +
  • Alternatively, use sd-parseq as a UI to define your animation schedules (see the Parseq section in the Init tab).
    • +
  • framesync.xyz is also a good option, it makes compact math formulae for Deforum keyframes by selecting various waveforms.
    • +
  • The other site allows for making keyframes using interactive splines and Bezier curves (select Disco output format).
    • +
  • If you want to use Width/Height which are not multiples of 64, please change noise_type to 'Uniform', in Keyframes --> Noise.
    • + + If you liked this extension, please give it a star on GitHub! 😊""") + 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(): + # RUN TAB + 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) + # RUN FROM SETTING FILE ACCORD + 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) + # RESUME ANIMATION ACCORD + 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!") + # KEYFRAMES TAB + with gr.TabItem('Keyframes'): #TODO make a some sort of the original dictionary parsing + 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") + # GUIDED IMAGES ACCORD + with gr.Accordion('Guided Images', open=False, elem_id='guided_images_accord') as guided_images_accord: + # GUIDED IMAGES INFO 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.""") + # In later versions this should be also in the strength schedule, but for now you need to set it. + gr.HTML("""Prerequisites and Important Info: + + """) + gr.HTML("""Looping recommendations: + + """) + gr.HTML("""The Guided images mode exposes the following variables for the prompts and the schedules: + + """) + 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) + # GUIDED IMAGES SCHEDULES ACCORD + 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) + # EXTA SCHEDULES TABS + 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) + # Steps Scheduling + 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'") + # Sampler Scheduling + 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") + # Checkpoint Scheduling + 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") + # MOTION INNER TAB + 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") + # PERSPECTIVE FLIP - params are hidden if not enabled + 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)") + # NOISE INNER TAB + 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) + # COHERENCE INNER TAB + 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'): + # what to do with blank frames (they may result from glitches or the NSFW filter being turned on): reroll with +1 seed, interrupt the animation generation, or do nothing + 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) + # ANTI BLUR INNER TAB + 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: + # this html only shows when not in 2d/3d mode + 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) + # this following html only shows when using LeReS depth + leres_license_msg = gr.HTML(value='Note that LeReS has a Non-Commercial license. 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-3.1-BeitLarge' is temporarily removed until fixed 04-05-23 + 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) + # PROMPTS TAB + with gr.TabItem('Prompts'): + # PROMPTS INFO ACCORD + with gr.Accordion(label='*Important* notes on Prompts', elem_id='prompts_info_accord', open=False, visible=True) as prompts_info_accord: + gr.HTML(""" + + """) + 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") + # COMPOSABLE MASK SCHEDULING ACCORD + with gr.Accordion('Composable Mask scheduling', open=False): + gr.HTML(""" + + """) + 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) + # INIT MAIN TAB + with gr.TabItem('Init'): + # IMAGE INIT INNER-TAB + 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) + # VIDEO INIT INNER-TAB + 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) + # MASK INIT INNER-TAB + 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) + # PARSEQ ACCORD + with gr.Accordion('Parseq', open=False): + gr.HTML(""" +

    Use a Parseq manifest for your animation (leave blank to ignore).

    +

    + 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. +

    + """) + 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) + # CONTROLNET TAB + with gr.TabItem('ControlNet'): + gr.HTML(controlnet_infotext()) + try: + controlnet_dict = setup_controlnet_ui() + except Exception as e: + raise Exception(e) + # HYBRID VIDEO TAB + with gr.TabItem('Hybrid Video'): + # this html only shows when not in 2d/3d mode + 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') + # HYBRID INFO ACCORD + with gr.Accordion("Info & Help", open=False): + hybrid_html = "

    Hybrid Video Compositing in 2D/3D Modeby reallybigname

    " + hybrid_html += "" + hybrid_html += "Hybrid Video Schedules" + hybrid_html += "" + hybrid_html += "Click Here for more info/ a Guide." + gr.HTML(hybrid_html) + # HYBRID SETTINGS ACCORD + 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) + # HYBRID SCHEDULES ACCORD + 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) + # HUMANS MASKING ACCORD + 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") + # OUTPUT TAB + with gr.TabItem('Output', elem_id='output_tab'): + # VID OUTPUT ACCORD + 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") + # TODO: auto-hide if video input is selected?! + 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") + # the following param only shows for windows and linux users! + 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") + # FRAME INTERPOLATION TAB + 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 RIFE / FILM Frame Interpolation to smooth out, slow-mo (or both) any video.

    +

    + Supported engines: +

    +

    +

    + Important notes: +

    +

    + """) + with gr.Column(variant='compact'): + with gr.Row(variant='compact'): + # Interpolation Engine + 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): + # If this is set to True, we keep all of the interpolated frames in a folder. Default is False - means we delete them at the end of the run + 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: + # How many times to interpolate (interp X) + 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: + # Interp Slow-Mo (setting final output fps, not really doing anything direclty with RIFE/FILM) + 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: + # Intrpolate any existing video from the connected PC + with gr.Accordion('Interpolate existing Video/ Images', open=False) as interp_existing_video_accord: + with gr.Row(variant='compact') as interpolate_upload_files_row: + # A drag-n-drop UI box to which the user uploads a *single* (at this stage) video + 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") + # A drag-n-drop UI box to which the user uploads a pictures to interpolate + 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: + # Non interactive textbox showing uploaded input vid total Frame Count + in_vid_frame_count_window = gr.Textbox(label="In Frame Count", lines=1, interactive=False, value='---') + # Non interactive textbox showing uploaded input vid FPS + in_vid_fps_ui_window = gr.Textbox(label="In FPS", lines=1, interactive=False, value='---') + # Non interactive textbox showing expected output interpolated video FPS + out_interp_vid_estimated_fps = gr.Textbox(label="Interpolated Vid FPS", value='---') + with gr.Row(variant='compact') as interp_buttons_row: + # This is the actual button that's pressed to initiate the interpolation: + interpolate_button = gr.Button(value="*Interpolate Video*") + interpolate_pics_button = gr.Button(value="*Interpolate Pics*") + # Show a text about CLI outputs: + gr.HTML("* check your CLI for outputs *", elem_id="below_interpolate_butts_msg") # TODO: CSS THIS TO CENTER OF ROW! + # make the functin call when the interpolation button is clicked + 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]) + # VIDEO UPSCALE TAB + 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(): + # NCNN UPSCALE TAB + 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='---') # Non interactive textbox showing uploaded input vid Frame Count + ncnn_upscale_in_vid_fps_ui_window = gr.Textbox(label="In FPS", lines=1, interactive=False, value='---') # Non interactive textbox showing uploaded input vid FPS + ncnn_upscale_in_vid_res = gr.Textbox(label="In Res", lines=1, interactive=False, value='---') # Non interactive textbox showing uploaded input resolution + ncnn_upscale_out_vid_res = gr.Textbox(label="Out Res", value='---') # Non interactive textbox showing expected output resolution + 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) # fix value + 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): # Upscale V1. Disabled 06-03-23 + 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]) + # This is the actual button that's pressed to initiate the Upscaling: + upscale_btn = gr.Button(value="*Upscale uploaded video*") + # Show a text about CLI outputs: + gr.HTML("* check your CLI for outputs") + # make the function call when the UPSCALE button is clicked + # Vid2Depth TAB + 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'): + # This is the actual button that's pressed to initiate the Upscaling: + depth_btn = gr.Button(value="*Get depth from uploaded video*") + with gr.Row(variant='compact'): + # Show a text about CLI outputs: + gr.HTML("* check your CLI for outputs") + # make the function call when the UPSCALE button is clicked + 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]) + # STITCH FRAMES TO VID TAB + with gr.TabItem('Frames to Video') as stitch_imgs_to_vid_row: + gr.HTML(""" +

    + Important Notes: +

    + """) + 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]) + # **OLD + NON ACTIVES AREA** + 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) + # Gradio's Change functions - hiding and renaming elements based on other elements + show_info_on_ui.change(fn=change_css, inputs=show_info_on_ui, outputs = gr.outputs.HTML()) + # seed.change(fn=auto_hide_n_batch, inputs=seed, outputs=n_batch) + 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] # depth_3d_warping_accord, fov_accord + 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) + # show/hide enable persp flip mode button. Shown only in 2d/3d anim modes + 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) + #Hybrid related: + 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) + # End of hybrid related + 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]] + # Populate the FPS and FCount values as soon as a video is uploaded to the FileUploadBox (vid_to_interpolate_chosen_file) + 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) + # END OF UI TABS + stuff = locals() + stuff = {**stuff, **controlnet_dict} + stuff.pop('controlnet_dict') + return stuff + +### SETTINGS STORAGE UPDATE! 2023-01-27 +### To Reduce The Number Of Settings Overrides, +### They Are Being Passed As Dictionaries +### It Would Have Been Also Nice To Retrieve Them +### From Functions Like Deforumoutputargs(), +### But Over Time There Was Some Cross-Polination, +### So They Are Now Hardcoded As 'List'-Strings Below +### If you're adding a new setting, add it to one of the lists +### besides writing it in the setup functions above + +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()] #if name not in video_args_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 # can use this later to error cleanly upon wrong gen param in ui + 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', '') # remove --neg from negative_prompts if recieved by mistake + 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 + +# Local gradio-to-frame-interoplation function. *Needs* to stay here since we do Root() and use gradio elements directly, to be changed in the future +def upload_vid_to_interpolate(file, engine, x_am, sl_enabled, sl_am, keep_imgs, in_vid_fps): + # print msg and do nothing if vid not uploaded or interp_x not provided + 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() + # make sure all uploaded pics have the same resolution + 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): + # print msg and do nothing if vid not uploaded + 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)