scripts/deforum_helpers/args.py

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"<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()) #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("""<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():
            # 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: 
                                   <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)
                    # 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 <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-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("""
                        <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")
                # COMPOSABLE MASK SCHEDULING ACCORD
                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 &lt;&gt;, like &lt;apple&gt;, &lt;hair&gt</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)
            # 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("""
                    <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)            
            # 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 = "<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)
                # 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 <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'):
                            # 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("""
                     <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])
                # **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)