from modules.shared import cmd_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
from .upscaling import process_upscale_vid_upload_logic, process_ncnn_upscale_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
from .gradio_funcs import *
from .general_utils import get_os
from .deforum_controlnet import controlnet_component_names, setup_controlnet_ui
import tempfile
def Root():
device = sh.device
models_path = ph.models_path + '/Deforum'
half_precision = not cmd_opts.no_half
mask_preset_names = ['everywhere','init_mask','video_mask']
p = None
frames_cache = []
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():
#@markdown ####**Animation:**
animation_mode = '2D' #@param ['None', '2D', '3D', 'Video Input', 'Interpolation'] {type:'string'}
max_frames = 120 #@param {type:"number"}
border = 'replicate' #@param ['wrap', 'replicate'] {type:'string'}
#@markdown ####**Motion Parameters:**
angle = "0:(0)"#@param {type:"string"}
zoom = "0:(1.0025+0.002*sin(1.25*3.14*t/30))"#@param {type:"string"}
translation_x = "0:(0)"#@param {type:"string"}
translation_y = "0:(0)"#@param {type:"string"}
translation_z = "0:(1.75)"#@param {type:"string"}
rotation_3d_x = "0:(0)"#@param {type:"string"}
rotation_3d_y = "0:(0)"#@param {type:"string"}
rotation_3d_z = "0:(0)"#@param {type:"string"}
enable_perspective_flip = False #@param {type:"boolean"}
perspective_flip_theta = "0:(0)"#@param {type:"string"}
perspective_flip_phi = "0:(0)"#@param {type:"string"}
perspective_flip_gamma = "0:(0)"#@param {type:"string"}
perspective_flip_fv = "0:(53)"#@param {type:"string"}
noise_schedule = "0: (0.065)"#@param {type:"string"}
strength_schedule = "0: (0.65)"#@param {type:"string"}
contrast_schedule = "0: (1.0)"#@param {type:"string"}
cfg_scale_schedule = "0: (7)"
enable_steps_scheduling = False#@param {type:"boolean"}
steps_schedule = "0: (25)"#@param {type:"string"}
fov_schedule = "0: (70)"
near_schedule = "0: (200)"
far_schedule = "0: (10000)"
seed_schedule = "0:(5), 1:(-1), 219:(-1), 220:(5)"
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 #@param {type:"boolean"}
sampler_schedule = '0: ("Euler a")'
# Composable mask scheduling
use_noise_mask = False
mask_schedule = '0: ("!({everywhere}^({init_mask}|{video_mask}) ) ")'
noise_mask_schedule = '0: ("!({everywhere}^({init_mask}|{video_mask}) ) ")'
# Checkpoint Scheduling
enable_checkpoint_scheduling = False#@param {type:"boolean"}
checkpoint_schedule = '0: ("model1.ckpt"), 100: ("model2.ckpt")'
# CLIP skip Scheduling
enable_clipskip_scheduling = False #@param {type:"boolean"}
clipskip_schedule = '0: (2)'
# Anti-blur
kernel_schedule = "0: (5)"
sigma_schedule = "0: (1.0)"
amount_schedule = "0: (0.35)"
threshold_schedule = "0: (0.0)"
# Hybrid video
hybrid_comp_alpha_schedule = "0:(1)" #@param {type:"string"}
hybrid_comp_mask_blend_alpha_schedule = "0:(0.5)" #@param {type:"string"}
hybrid_comp_mask_contrast_schedule = "0:(1)" #@param {type:"string"}
hybrid_comp_mask_auto_contrast_cutoff_high_schedule = "0:(100)" #@param {type:"string"}
hybrid_comp_mask_auto_contrast_cutoff_low_schedule = "0:(0)" #@param {type:"string"}
#@markdown ####**Coherence:**
color_coherence = 'Match Frame 0 LAB' #@param ['None', 'Match Frame 0 HSV', 'Match Frame 0 LAB', 'Match Frame 0 RGB', 'Video Input'] {type:'string'}
color_coherence_video_every_N_frames = 1 #@param {type:"integer"}
color_force_grayscale = False #@param {type:"boolean"}
diffusion_cadence = '2' #@param ['1','2','3','4','5','6','7','8'] {type:'string'}
#@markdown ####**Noise settings:**
noise_type = 'perlin' #@param ['uniform', 'perlin'] {type:'string'}
# Perlin params
perlin_w = 8 #@param {type:"number"}
perlin_h = 8 #@param {type:"number"}
perlin_octaves = 4 #@param {type:"number"}
perlin_persistence = 0.5 #@param {type:"number"}
#@markdown ####**3D Depth Warping:**
use_depth_warping = True #@param {type:"boolean"}
midas_weight = 0.2 #@param {type:"number"}
padding_mode = 'border'#@param ['border', 'reflection', 'zeros'] {type:'string'}
sampling_mode = 'bicubic'#@param ['bicubic', 'bilinear', 'nearest'] {type:'string'}
save_depth_maps = False #@param {type:"boolean"}
#@markdown ####**Video Input:**
video_init_path ='https://github.com/hithereai/d/releases/download/m/vid.mp4' #@param {type:"string"}
extract_nth_frame = 1#@param {type:"number"}
extract_from_frame = 0 #@param {type:"number"}
extract_to_frame = -1 #@param {type:"number"} minus 1 for unlimited frames
overwrite_extracted_frames = True #@param {type:"boolean"}
use_mask_video = False #@param {type:"boolean"}
video_mask_path ='/content/video_in.mp4'#@param {type:"string"}
#@markdown ####**Hybrid Video for 2D/3D Animation Mode:**
hybrid_generate_inputframes = False #@param {type:"boolean"}
hybrid_generate_human_masks = "None" #@param ['None','PNGs','Video', 'Both']
hybrid_use_first_frame_as_init_image = True #@param {type:"boolean"}
hybrid_motion = "None" #@param ['None','Optical Flow','Perspective','Affine']
hybrid_motion_use_prev_img = False #@param {type:"boolean"}
hybrid_flow_method = "Farneback" #@param ['DIS Medium','Farneback']
hybrid_composite = False #@param {type:"boolean"}
hybrid_comp_mask_type = "None" #@param ['None', 'Depth', 'Video Depth', 'Blend', 'Difference']
hybrid_comp_mask_inverse = False #@param {type:"boolean"}
hybrid_comp_mask_equalize = "None" #@param ['None','Before','After','Both']
hybrid_comp_mask_auto_contrast = False #@param {type:"boolean"}
hybrid_comp_save_extra_frames = False #@param {type:"boolean"}
#@markdown ####**Resume Animation:**
resume_from_timestring = False #@param {type:"boolean"}
resume_timestring = "20220829210106" #@param {type:"string"}
return locals()
# def DeforumPrompts():
# return
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():
#@markdown **Image Settings**
W = 512 #@param
H = 512 #@param
W, H = map(lambda x: x - x % 64, (W, H)) # resize to integer multiple of 64
#@markdonw **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
#@markdown **Sampling Settings**
seed = -1 #@param
sampler = 'euler_ancestral' #@param ["klms","dpm2","dpm2_ancestral","heun","euler","euler_ancestral","plms", "ddim"]
steps = 25 #@param
scale = 7 #@param
ddim_eta = 0.0 #@param
dynamic_threshold = None
static_threshold = None
#@markdown **Save & Display Settings**
save_samples = True #@param {type:"boolean"}
save_settings = True #@param {type:"boolean"}
display_samples = True #@param {type:"boolean"}
save_sample_per_step = False #@param {type:"boolean"}
show_sample_per_step = False #@param {type:"boolean"}
#@markdown **Prompt Settings**
prompt_weighting = False #@param {type:"boolean"}
normalize_prompt_weights = True #@param {type:"boolean"}
log_weighted_subprompts = False #@param {type:"boolean"}
#@markdown **Batch Settings**
n_batch = 1 #@param
batch_name = "Deforum" #@param {type:"string"}
filename_format = "{timestring}_{index}_{prompt}.png" #@param ["{timestring}_{index}_{seed}.png","{timestring}_{index}_{prompt}.png"]
seed_behavior = "iter" #@param ["iter","fixed","random","ladder","alternate","schedule"]
seed_iter_N = 1 #@param {type:'integer'}
# make_grid = False #@param {type:"boolean"}
# grid_rows = 2 #@param
outdir = ""#get_output_folder(output_path, batch_name)
#@markdown **Init Settings**
use_init = False #@param {type:"boolean"}
strength = 0.0 #@param {type:"number"}
strength_0_no_init = True # Set the strength to 0 automatically when no init image is used
init_image = "https://github.com/hithereai/d/releases/download/m/kaba.png" #@param {type:"string"}
# Whiter areas of the mask are areas that change more
use_mask = False #@param {type:"boolean"}
use_alpha_as_mask = False # use the alpha channel of the init image as the mask
mask_file = "https://github.com/hithereai/d/releases/download/m/mask.jpg" #@param {type:"string"}
invert_mask = False #@param {type:"boolean"}
# Adjust mask image, 1.0 is no adjustment. Should be positive numbers.
mask_contrast_adjust = 1.0 #@param {type:"number"}
mask_brightness_adjust = 1.0 #@param {type:"number"}
# Overlay the masked image at the end of the generation so it does not get degraded by encoding and decoding
overlay_mask = True # {type:"boolean"}
# Blur edges of final overlay mask, if used. Minimum = 0 (no blur)
mask_overlay_blur = 4 # {type:"number"}
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
n_samples = 1 # doesnt do anything
precision = 'autocast'
C = 4
f = 8
prompt = ""
timestring = ""
init_latent = None
init_sample = None
init_c = None
mask_image = None
noise_mask = None
seed_internal = 0
return locals()
def keyframeExamples():
return '''{
"0": "https://user-images.githubusercontent.com/121192995/215279228-1673df8a-f919-4380-b04c-19379b2041ff.png",
"50": "https://user-images.githubusercontent.com/121192995/215279281-7989fd6f-4b9b-4d90-9887-b7960edd59f8.png",
"100": "https://user-images.githubusercontent.com/121192995/215279284-afc14543-d220-4142-bbf4-503776ca2b8b.png",
"150": "https://user-images.githubusercontent.com/121192995/215279286-23378635-85b3-4457-b248-23e62c048049.jpg",
"200": "https://user-images.githubusercontent.com/121192995/215279228-1673df8a-f919-4380-b04c-19379b2041ff.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_for_run_all = False #@param {type: 'boolean'}
fps = 15 #@param {type:"number"}
make_gif = False
image_path = "C:/SD/20230124234916_%05d.png" #@param {type:"string"}
mp4_path = "testvidmanualsettings.mp4" #@param {type:"string"}
ffmpeg_location = find_ffmpeg_binary()
ffmpeg_crf = '17'
ffmpeg_preset = 'slow'
add_soundtrack = 'None' #@param ["File","Init Video"]
soundtrack_path = "https://freetestdata.com/wp-content/uploads/2021/09/Free_Test_Data_1MB_MP3.mp3"
# End-Run upscaling
r_upscale_video = False
r_upscale_factor = 'x2' # ['2x', 'x3', 'x4']
# **model below** - 'realesr-animevideov3' (default of realesrgan engine, does 2-4x), the rest do only 4x: 'realesrgan-x4plus', 'realesrgan-x4plus-anime'
r_upscale_model = 'realesr-animevideov3'
r_upscale_keep_imgs = True
render_steps = False #@param {type: 'boolean'}
path_name_modifier = "x0_pred" #@param ["x0_pred","x"]
# max_video_frames = 200 #@param {type:"string"}
store_frames_in_ram = False #@param {type: 'boolean'}
#@markdown **Interpolate Video Settings**
# todo: change them to support FILM interpolation as well
frame_interpolation_engine = "None" #@param ["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 #@param [2 to 10]
frame_interpolation_keep_imgs = False #@param {type: 'boolean'}
return locals()
import gradio as gr
import os
import time
from types import SimpleNamespace
i1_store_backup = "
Deforum extension for auto1111 — version 2.2b
"
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():
btn = gr.Button("Click here after the generation to show the video")
with gr.Row():
i1 = gr.HTML(i1_store, elem_id='deforum_header')
else:
btn = i1 = gr.HTML("")
# MAIN (TOP) EXTENSION INFO ACCORD
with gr.Accordion("Info, Links and Help", open=False, elem_id='main_top_info_accord'):
gr.HTML("""Made by deforum.github.io, port for AUTOMATIC1111's webui maintained by kabachuha""")
gr.HTML("""FOR HELP CLICK HERE
The code for this extension: here.
Join the official Deforum Discord to share your creations and suggestions.
Official Deforum Wiki: here.
Anime-inclined great guide (by FizzleDorf) with lots of examples: here.
For advanced keyframing with Math functions, see here.
Alternatively, use sd-parseq as a UI to define your animation schedules (see the Parseq section in the Keyframes tab).
framesync.xyz is also a good option, it makes compact math formulae for Deforum keyframes by selecting various waveforms.
The other site allows for making keyframes using interactive splines and Bezier curves (select Disco output format).
If you want to use Width/Height which are not multiples of 64, please change noise_type to 'Uniform', in Keyframes --> Noise.
If you liked this extension, please give it a star on GitHub! 😊""")
if not is_extension:
def show_vid():
return {
i1: gr.update(value=i1_store, visible=True)
}
btn.click(
show_vid,
[],
[i1]
)
with gr.Blocks():
# RUN TAB
with gr.Tab('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(variables='compact'):
seed = gr.Number(label="Seed", value=d.seed, interactive=True, precision=0)
batch_name = gr.Textbox(label="Batch name", lines=1, interactive=True, value = d.batch_name)
with gr.Accordion('Restore Faces, Tiling & more', open=False) as run_more_settings_accord:
with gr.Row(variant='compact'):
restore_faces = gr.Checkbox(label='Restore Faces', value=d.restore_faces)
tiling = gr.Checkbox(label='Tiling', value=False)
ddim_eta = gr.Number(label="DDIM Eta", value=d.ddim_eta, interactive=True)
with gr.Row() 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)
# RUN FROM SETTING FILE ACCORD
with gr.Accordion('Resume & Run from file', open=False):
with gr.Tab('Run from Settings file'):
with gr.Row(variant='compact'):
override_settings_with_file = gr.Checkbox(label="Override settings", value=False, interactive=True, elem_id='override_settings')
custom_settings_file = gr.Textbox(label="Custom settings file", lines=1, interactive=True, elem_id='custom_settings_file')
# 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)
# KEYFRAMES TAB
with gr.Tab('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")
with gr.Column(scale=1, min_width=180):
border = gr.Radio(['replicate', 'wrap'], label="Border", value=da.border, elem_id="border")
with gr.Row(variant='compact'):
diffusion_cadence = gr.Slider(label="Cadence", minimum=1, maximum=50, step=1, value=da.diffusion_cadence, interactive=True)
max_frames = gr.Number(label="Max frames", lines=1, value = da.max_frames, interactive=True, precision=0)
# 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:
- This mode works ONLY with 2D/3D animation modes. Interpolation and Video Input modes aren't supported. li>
- Set Init tab's strength slider greater than 0. Recommended value (.65 - .80). li>
- Set 'seed_behavior' to 'schedule' under the Seed Scheduling section below.
""")
gr.HTML("""Looping recommendations:
- seed_schedule should start and end on the same seed.
Example: seed_schedule could use 0:(5), 1:(-1), 219:(-1), 220:(5)
- The 1st and last keyframe images should match.
- Set your total number of keyframes to be 21 more than the last inserted keyframe image.
Example: Default args should use 221 as total keyframes.
- Prompts are stored in JSON format. If you've got an error, check it in validator, like here
""")
with gr.Row():
use_looper = gr.Checkbox(label="Enable guided images mode", value=dloopArgs.use_looper, interactive=True)
with gr.Row():
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():
image_strength_schedule = gr.Textbox(label="Image strength schedule", lines=1, value = dloopArgs.image_strength_schedule, interactive=True)
with gr.Row():
blendFactorMax = gr.Textbox(label="Blend factor max", lines=1, value = dloopArgs.blendFactorMax, interactive=True)
with gr.Row():
blendFactorSlope = gr.Textbox(label="Blend factor slope", lines=1, value = dloopArgs.blendFactorSlope, interactive=True)
with gr.Row():
tweening_frames_schedule = gr.Textbox(label="Tweening frames schedule", lines=1, value = dloopArgs.tweening_frames_schedule, interactive=True)
with gr.Row():
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'):
strength_schedule = gr.Textbox(label="Strength schedule", lines=1, value = da.strength_schedule, interactive=True)
with gr.TabItem('CFG'):
cfg_scale_schedule = gr.Textbox(label="CFG scale schedule", lines=1, value = da.cfg_scale_schedule, interactive=True)
with gr.TabItem('Seed') as a3:
with gr.Row():
seed_behavior = gr.Radio(['iter', 'fixed', 'random', 'ladder', 'alternate', 'schedule'], label="Seed behavior", value=d.seed_behavior, elem_id="seed_behavior")
with gr.Row() as seed_iter_N_row:
seed_iter_N = gr.Number(label="Seed iter N", value=d.seed_iter_N, interactive=True, precision=0)
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:
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():
enable_steps_scheduling = gr.Checkbox(label="Enable steps scheduling", value=da.enable_steps_scheduling, interactive=True)
with gr.Row():
steps_schedule = gr.Textbox(label="Steps schedule", lines=1, value = da.steps_schedule, interactive=True)
# Sampler Scheduling
with gr.TabItem('Sampler') as a14:
with gr.Row():
enable_sampler_scheduling = gr.Checkbox(label="Enable sampler scheduling", value=da.enable_sampler_scheduling, interactive=True)
with gr.Row():
sampler_schedule = gr.Textbox(label="Sampler schedule", lines=1, value = da.sampler_schedule, interactive=True)
# Checkpoint Scheduling
with gr.TabItem('Checkpoint') as a15:
with gr.Row():
enable_checkpoint_scheduling = gr.Checkbox(label="Enable checkpoint scheduling", value=da.enable_checkpoint_scheduling, interactive=True)
with gr.Row():
checkpoint_schedule = gr.Textbox(label="Checkpoint schedule", lines=1, value = da.checkpoint_schedule, interactive=True)
with gr.TabItem('CLIP Skip', open=False) as a16:
with gr.Row():
enable_clipskip_scheduling = gr.Checkbox(label="Enable CLIP skip scheduling", value=da.enable_clipskip_scheduling, interactive=True)
with gr.Row():
clipskip_schedule = gr.Textbox(label="CLIP skip schedule", lines=1, value = da.clipskip_schedule, interactive=True)
# MOTION INNER TAB
with gr.Tab('Motion') as motion_tab:
with gr.Column(visible=True) as only_2d_motion_column:
with gr.Row(variant='compact'):
angle = gr.Textbox(label="Angle", lines=1, value = da.angle, interactive=True)
with gr.Row(variant='compact'):
zoom = gr.Textbox(label="Zoom", lines=1, value = da.zoom, interactive=True)
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)
with gr.Row(variant='compact'):
translation_y = gr.Textbox(label="Translation Y", lines=1, value = da.translation_y, interactive=True)
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)
with gr.Row(variant='compact'):
rotation_3d_x = gr.Textbox(label="Rotation 3D X", lines=1, value = da.rotation_3d_x, interactive=True)
with gr.Row(variant='compact'):
rotation_3d_y = gr.Textbox(label="Rotation 3D Y", lines=1, value = da.rotation_3d_y, interactive=True)
with gr.Row(variant='compact'):
rotation_3d_z = gr.Textbox(label="Rotation 3D Z", lines=1, value = da.rotation_3d_z, interactive=True)
# 3D DEPTH & FOV ACCORD
with gr.Accordion('Depth Warping & FOV', visible=False, open=False) as depth_3d_warping_accord:
with gr.Tab('Depth Warping'):
with gr.Row(variant='compact'):
use_depth_warping = gr.Checkbox(label="Use depth warping", value=da.use_depth_warping, interactive=True)
midas_weight = gr.Number(label="MiDaS weight", value=da.midas_weight, interactive=True)
with gr.Row(variant='compact'):
padding_mode = gr.Radio(['border', 'reflection', 'zeros'], label="Padding mode", value=da.padding_mode, elem_id="padding_mode")
sampling_mode = gr.Radio(['bicubic', 'bilinear', 'nearest'], label="Sampling mode", value=da.sampling_mode, elem_id="sampling_mode")
with gr.Tab('Field Of View', visible=False, open=False) as fov_accord:
with gr.Row(variant='compact'):
fov_schedule = gr.Textbox(label="FOV schedule", lines=1, value = da.fov_schedule, interactive=True)
with gr.Row():
near_schedule = gr.Textbox(label="Near schedule", lines=1, value = da.near_schedule, interactive=True)
with gr.Row():
far_schedule = gr.Textbox(label="Far schedule", lines=1, value = da.far_schedule, interactive=True)
# PERSPECTIVE FLIP ACCORD
with gr.Accordion('Perspective Flip', open=False) as perspective_flip_accord:
with gr.Row():
enable_perspective_flip = gr.Checkbox(label="Enable perspective flip", value=da.enable_perspective_flip, interactive=True)
with gr.Row():
perspective_flip_theta = gr.Textbox(label="Perspective flip theta", lines=1, value = da.perspective_flip_theta, interactive=True)
with gr.Row():
perspective_flip_phi = gr.Textbox(label="Perspective flip phi", lines=1, value = da.perspective_flip_phi, interactive=True)
with gr.Row():
perspective_flip_gamma = gr.Textbox(label="Perspective flip gamma", lines=1, value = da.perspective_flip_gamma, interactive=True)
with gr.Row():
perspective_flip_fv = gr.Textbox(label="Perspective flip fv", lines=1, value = da.perspective_flip_fv, interactive=True)
# NOISE INNER TAB
with gr.Tab('Noise', open=True) as a8:
with gr.Row():
noise_type = gr.Radio(['uniform', 'perlin'], label="Noise type", value=da.noise_type, elem_id="noise_type")
with gr.Row():
noise_schedule = gr.Textbox(label="Noise schedule", lines=1, value = da.noise_schedule, interactive=True)
with gr.Row() 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)
# COHERENCE INNER TAB
with gr.Tab('Coherence', open=False) as coherence_accord:
with gr.Row(equal_height=True):
# Future TODO: remove 'match frame 0' prefix (after we manage the deprecated-names settings import), then convert from Dropdown to Radio!
color_coherence = gr.Dropdown(label="Color coherence", choices=['None', 'Match Frame 0 HSV', 'Match Frame 0 LAB', 'Match Frame 0 RGB', 'Video Input'], value=da.color_coherence, type="value", elem_id="color_coherence", interactive=True)
with gr.Column() as force_grayscale_column:
color_force_grayscale = gr.Checkbox(label="Color force Grayscale", value=da.color_force_grayscale, 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():
contrast_schedule = gr.Textbox(label="Contrast schedule", lines=1, value = da.contrast_schedule, interactive=True)
with gr.Row():
# 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")
# ANTI BLUR INNER TAB
with gr.Tab('Anti Blur', open=False, elem_id='anti_blur_accord') as anti_blur_tab:
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'):
amount_schedule = gr.Textbox(label="Amount schedule", lines=1, value = da.amount_schedule, interactive=True)
with gr.Row(variant='compact'):
threshold_schedule = gr.Textbox(label="Threshold schedule", lines=1, value = da.threshold_schedule, interactive=True)
# PROMPTS TAB
with gr.Tab('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("""
- Please always keep values in math functions above 0.
- There is *no* Batch mode like in vanilla deforum. Please Use the txt2img tab for that.
- For negative prompts, please write your positive prompt, then --neg ugly, text, assymetric, or any other negative tokens of your choice. OR:
- Use the negative_prompts field to automatically append all words as a negative prompt. *Don't* add --neg in the negative_prompts field!
- Prompts are stored in JSON format. If you've got an error, check it in a JSON Validator
""")
with gr.Row():
animation_prompts = gr.Textbox(label="Prompts", lines=8, interactive=True, value = DeforumAnimPrompts())
with gr.Row():
animation_prompts_positive = gr.Textbox(label="Prompts positive", lines=1, interactive=True, value = "")
with gr.Row():
animation_prompts_negative = gr.Textbox(label="Prompts negative", lines=1, interactive=True, value = "")
# COMPOSABLE MASK SCHEDULING ACCORD
with gr.Accordion('Composable Mask scheduling', open=False):
gr.HTML("""
- To enable, check use_mask in the Init tab
- Supports boolean operations: (! - negation, & - and, | - or, ^ - xor, \ - difference, () - nested operations)
- default variables: in \{\}, like \{init_mask\}, \{video_mask\}, \{everywhere\}
- masks from files: in [], like [mask1.png]
- description-based: word masks in <>, like <apple>, <hair>
""")
with gr.Row():
mask_schedule = gr.Textbox(label="Mask schedule", lines=1, value = da.mask_schedule, interactive=True)
with gr.Row():
use_noise_mask = gr.Checkbox(label="Use noise mask", value=da.use_noise_mask, interactive=True)
with gr.Row():
noise_mask_schedule = gr.Textbox(label="Noise mask schedule", lines=1, value = da.noise_mask_schedule, interactive=True)
# INIT MAIN TAB
with gr.Tab('Init'):
# IMAGE INIT INNER-TAB
with gr.Tab('Image Init'):
with gr.Row():
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=True, interactive=True)
with gr.Column(min_width=170):
strength = gr.Slider(label="Strength", minimum=0, maximum=1, step=0.01, value=0, interactive=True)
with gr.Row():
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():
video_init_path = gr.Textbox(label="Video init path", lines=1, value = da.video_init_path, interactive=True)
with gr.Row():
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():
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():
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():
mask_file = gr.Textbox(label="Mask file", lines=1, interactive=True, value = d.mask_file)
with gr.Row():
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():
choice = mask_fill_choices[d.fill]
fill = gr.Radio(label='Mask fill', choices=mask_fill_choices, value=choice, type="index")
with gr.Row():
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)
# PARSEQ ACCORD
with gr.Accordion('Parseq', open=False):
gr.HTML("""
Use an sd-parseq manifest for your animation (leave blank to ignore).
Note that parseq overrides:
- Run: seed, subseed, subseed strength.
- Keyframes: generation settings (noise, strength, contrast, scale).
- Keyframes: motion parameters for 2D and 3D (angle, zoom, translation, rotation, perspective flip).
Parseq does not override:
- Run: Sampler, Width, Height, tiling, resize seed.
- Keyframes: animation settings (animation mode, max frames, border)
- Keyframes: coherence (color coherence & cadence)
- Keyframes: depth warping
- Output settings: all settings (including fps and max frames)
""")
with gr.Row():
parseq_manifest = gr.Textbox(label="Parseq Manifest (JSON or URL)", lines=4, value = dp.parseq_manifest, interactive=True)
with gr.Row():
parseq_use_deltas = gr.Checkbox(label="Use delta values for movement parameters", value=dp.parseq_use_deltas, interactive=True)
def show_hybrid_html_msg(choice):
if choice not in ['2D','3D']:
return gr.update(visible=True)
else:
return gr.update(visible=False)
def change_hybrid_tab_status(choice):
if choice in ['2D','3D']:
return gr.update(visible=True)
else:
return gr.update(visible=False)
# CONTROLNET TAB
with gr.Tab('ControlNet'):
gr.HTML("""
Requires the ControlNet extension to be installed.
*Work In Progress*. All params below are going to be keyframable at some point. If you want to speedup the integration, join Deforum's development. 😉
Due to ControlNet base extension's inner works it needs its models to be located at 'extensions/deforum-for-automatic1111-webui/models'. So copy, symlink or move them there until a more elegant solution is found. And, as of now, it requires use_init checked for the first run. The ControlNet extension version used in the dev process is a24089a62e70a7fae44b7bf35b51fd584dd55e25, if even with all the other options above used it still breaks, upgrade/downgrade your CN version to this one.
""")
controlnet_dict = setup_controlnet_ui()
# HYBRID VIDEO TAB
with gr.Tab('Hybrid Video'):
# this html only shows when not in 2d/3d mode
hybrid_msg_html = gr.HTML(value='Please, change animation mode to 2D or 3D to enable Hybrid Mode',visible=False, elem_id='hybrid_msg_html')
# HYBRID INFO ACCORD
with gr.Accordion("Info & Help", open=False):
hybrid_html = "Hybrid Video Compositing in 2D/3D Modeby reallybigname
"
hybrid_html += "- Composite video with previous frame init image in 2D or 3D animation_mode (not for Video Input mode)
"
hybrid_html += "- Uses your Init settings for video_init_path, extract_nth_frame, overwrite_extracted_frames
"
hybrid_html += "- In Keyframes tab, you can also set color_coherence = 'Video Input'
"
hybrid_html += "- color_coherence_video_every_N_frames lets you only match every N frames
"
hybrid_html += "- Color coherence may be used with hybrid composite off, to just use video color.
"
hybrid_html += "- Hybrid motion may be used with hybrid composite off, to just use video motion.
"
hybrid_html += "Hybrid Video Schedules"
hybrid_html += "- The alpha schedule controls overall alpha for video mix, whether using a composite mask or not.
"
hybrid_html += "- The hybrid_comp_mask_blend_alpha_schedule only affects the 'Blend' hybrid_comp_mask_type.
"
hybrid_html += "- Mask contrast schedule is from 0-255. Normal is 1. Affects all masks.
"
hybrid_html += "- Autocontrast low/high cutoff schedules 0-100. Low 0 High 100 is full range.
(hybrid_comp_mask_auto_contrast must be enabled)
"
hybrid_html += "Click Here for more info/ a Guide."
gr.HTML(hybrid_html)
# HYBRID SETTINGS ACCORD
with gr.Accordion("Hybrid Settings", open=True) as hybrid_settings_accord:
with gr.Row(variant='compact'):
with gr.Column(min_width=340):
with gr.Row(variant='compact'):
hybrid_generate_inputframes = gr.Checkbox(label="Generate inputframes", value=False, interactive=True)
hybrid_composite = gr.Checkbox(label="Hybrid composite", value=False, interactive=True)
with gr.Column(min_width=340) as hybrid_2nd_column:
with gr.Row(variant='compact'):
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_motion_use_prev_img = gr.Checkbox(label="Motion use prev img", value=False, interactive=True, visible=False)
with gr.Row() as hybrid_flow_row:
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(['DIS Medium', 'Farneback'], label="Flow method", value=da.hybrid_flow_method, elem_id="hybrid_flow_method", visible=False)
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=False, 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', 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.Tab('Output'):
# 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)
# NOT VISIBLE AS OF 11-02-23 moving to ffmpeg-only!
output_format = gr.Dropdown(visible=False, label="Output format", choices=['FFMPEG mp4'], value='FFMPEG mp4', type="value", elem_id="output_format", interactive=True)
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)
soundtrack_path = gr.Textbox(label="Soundtrack path", lines=1, interactive=True, value = dv.soundtrack_path)
with gr.Row(variant='compact'):
skip_video_for_run_all = gr.Checkbox(label="Skip video for run all", value=dv.skip_video_for_run_all, interactive=True)
store_frames_in_ram = gr.Checkbox(label="Store frames in ram", value=dv.store_frames_in_ram, interactive=True)
save_depth_maps = gr.Checkbox(label="Save depth maps", value=da.save_depth_maps, interactive=True)
# the following param only shows for windows and linux users!
make_gif = gr.Checkbox(label="Make GIF", value=dv.make_gif, interactive=True)
with gr.Row(equal_height=True, variant='compact', visible=(True if dr.current_user_os in ["Windows", "Linux", "Mac"] else False)) as r_upscale_row:
r_upscale_video = gr.Checkbox(label="Upscale", value=dv.r_upscale_video, interactive=True)
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)
with gr.Accordion('FFmpeg settings', visible=True, open=False) as ffmpeg_quality_accordion:
with gr.Row(equal_height=True, variant='compact', visible=True) as ffmpeg_set_row:
ffmpeg_crf = gr.Slider(minimum=0, maximum=51, step=1, label="CRF", value=dv.ffmpeg_crf, interactive=True)
ffmpeg_preset = gr.Dropdown(label="Preset", choices=['veryslow', 'slower', 'slow', 'medium', 'fast', 'faster', 'veryfast', 'superfast', 'ultrafast'], interactive=True, value = dv.ffmpeg_preset, type="value")
with gr.Row(equal_height=True, variant='compact', visible=True) as ffmpeg_location_row:
ffmpeg_location = gr.Textbox(label="Location", lines=1, interactive=True, value = dv.ffmpeg_location)
# FRAME INTERPOLATION TAB
with gr.Tab('Frame Interoplation') as frame_interp_tab:
with gr.Accordion('Important notes and Help', open=False):
gr.HTML("""
Use RIFE / FILM Frame Interpolation to smooth out, slow-mo (or both) any video.
Supported engines:
Important notes:
- Frame Interpolation will *not* run if any of the following are enabled: 'Store frames in ram' / 'Skip video for run all'.
- Audio (if provided) will *not* be transferred to the interpolated video if Slow-Mo is enabled.
- '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.
""")
with gr.Column(variant='compact'):
with gr.Row(variant='compact'):
# Interpolation Engine
frame_interpolation_engine = gr.Dropdown(label="Engine", choices=['None','RIFE v4.6','FILM'], value=dv.frame_interpolation_engine, type="value", elem_id="frame_interpolation_engine", interactive=True)
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)
# 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)
# TODO: move these from here when done
def hide_slow_mo(choice):
return gr.update(visible=True) if choice else gr.update(visible=False)
def hide_interp_by_interp_status(choice):
return gr.update(visible=False) if choice == 'None' else gr.update(visible=True)
def change_interp_x_max_limit(engine_name, current_value):
if engine_name == 'FILM':
return gr.update(maximum=300)
elif current_value > 10:
return gr.update(maximum=10, value=2)
return gr.update(maximum=10)
frame_interpolation_slow_mo_enabled.change(fn=hide_slow_mo,inputs=frame_interpolation_slow_mo_enabled,outputs=frame_interp_slow_mo_amount_column)
interp_hide_list = [frame_interpolation_slow_mo_enabled,frame_interpolation_keep_imgs,frame_interp_amounts_row]
for output in interp_hide_list:
frame_interpolation_engine.change(fn=hide_interp_by_interp_status,inputs=frame_interpolation_engine,outputs=output)
frame_interpolation_engine.change(fn=change_interp_x_max_limit,inputs=[frame_interpolation_engine,frame_interpolation_x_amount],outputs=frame_interpolation_x_amount)
with gr.Row(visible=False) as interp_existing_video_row:
# Intrpolate any existing video from the connected PC
with gr.Accordion('Interpolate an existing video', open=False) as interp_existing_video_accord:
# 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")
with gr.Row(variant='compact'):
# 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='---')
# This is the actual button that's pressed to initiate the interpolation:
interpolate_button = gr.Button(value="*Interpolate uploaded video*")
# Show a text about CLI outputs:
gr.HTML("* check your CLI for outputs")
# 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, ffmpeg_location, ffmpeg_crf, ffmpeg_preset, in_vid_fps_ui_window])
[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 above 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])
#TODO: move this from here
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)
# TODO: add upscalers parameters to the settings and make them a part of the pipeline
# VIDEO UPSCALE TAB
with gr.Tab('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.Tab('Upscale V2') as ncnn_upscale_tab:
with gr.Row(variant='compact') as ncnn_upload_vid_stats_row:
# Non interactive textbox showing uploaded input vid total Frame Count
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 FPS
ncnn_upscale_in_vid_fps_ui_window = gr.Textbox(label="In FPS", lines=1, interactive=False, value='---')
# Non interactive textbox showing uploaded input resolution
ncnn_upscale_in_vid_res = gr.Textbox(label="In Res", lines=1, interactive=False, value='---')
# Non interactive textbox showing expected output resolution
ncnn_upscale_out_vid_res = gr.Textbox(label="Out Res", value='---')
with gr.Column():
with gr.Row(variant='compact', visible=(True if dr.current_user_os in ["Windows", "Linux", "Mac"] else False)) 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, ffmpeg_location, ffmpeg_crf, ffmpeg_preset])
with gr.Tab('Upscale V1'):
with gr.Column():
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
upscale_btn.click(upload_vid_to_upscale,inputs=[vid_to_upscale_chosen_file, selected_tab, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_keep_imgs, ffmpeg_location, ffmpeg_crf, ffmpeg_preset])
# STITCH FRAMES TO VID TAB
with gr.Tab('Frames to Video') as stitch_imgs_to_vid_row:
with gr.Row(visible=False):
path_name_modifier = gr.Dropdown(label="Path name modifier", choices=['x0_pred', 'x'], value=dv.path_name_modifier, type="value", elem_id="path_name_modifier", interactive=True, visible=False)
gr.HTML("""
Important Notes:
- Enter relative to webui folder or Full-Absolute path, and make sure it ends with something like this: '20230124234916_%05d.png', just replace 20230124234916 with your batch ID. The %05d is important, don't forget it!
""")
with gr.Row(variant='compact'):
image_path = gr.Textbox(label="Image path", lines=1, interactive=True, value = dv.image_path)
with gr.Row(visible=False):
mp4_path = gr.Textbox(label="MP4 path", lines=1, interactive=True, value = dv.mp4_path)
# not visible as of 06-02-23 since render_steps is disabled as well and they work together. Need to fix both.
with gr.Row(visible=False):
# rend_step Never worked - set to visible false 28-1-23 # MOVE OUT FROM HERE!
render_steps = gr.Checkbox(label="Render steps", value=dv.render_steps, interactive=True, visible=False)
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, ffmpeg_location, ffmpeg_crf, ffmpeg_preset, add_soundtrack, soundtrack_path])
# **OLD + NON ACTIVES AREA**
with gr.Accordion(visible=False, label='INVISIBLE') as not_in_use_accordion:
# NOT VISIBLE AS OF 09-02-23
mask_contrast_adjust = gr.Slider(label="Mask contrast adjust", minimum=0, maximum=1, step=0.01, value=d.mask_contrast_adjust, interactive=True)
mask_brightness_adjust = gr.Slider(label="Mask brightness adjust", minimum=0, maximum=1, step=0.01, value=d.mask_brightness_adjust, interactive=True)
from_img2img_instead_of_link = gr.Checkbox(label="from_img2img_instead_of_link", value=False, interactive=False, visible=False)
# INVISIBLE AS OF 08-02 (with static value of 8 for both W and H). Was in Perlin section before Perlin Octaves/Persistence
with gr.Column(min_width=200, visible=False):
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)
with gr.Row(visible=False):
filename_format = gr.Textbox(label="Filename format", lines=1, interactive=True, value = d.filename_format, visible=False)
with gr.Row(visible=False):
save_settings = gr.Checkbox(label="save_settings", value=d.save_settings, interactive=True)
with gr.Row(visible=False):
save_samples = gr.Checkbox(label="save_samples", value=d.save_samples, interactive=True)
display_samples = gr.Checkbox(label="display_samples", value=False, interactive=False)
# NOT VISIBLE 11-02-23 htai
with gr.Accordion('Subseed controls & More', open=False, visible=False):
# Not visible until fixed, 06-02-23
# NOT VISIBLE as of 11-02 - we have sch now. will delete the actual params in a later date
with gr.Row(variant='compact', visible=False):
seed_enable_extras = gr.Checkbox(label="Enable subseed controls", value=False)
n_batch = gr.Number(label="N Batch", value=d.n_batch, interactive=True, precision=0, visible=False)
with gr.Row(visible=False):
save_sample_per_step = gr.Checkbox(label="Save sample per step", value=d.save_sample_per_step, interactive=True)
show_sample_per_step = gr.Checkbox(label="Show sample per step", value=d.show_sample_per_step, interactive=True)
# Gradio's Change functions - hiding and renaming elements based on other elements
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)
animation_mode.change(fn=change_diffusion_cadence_visibility, inputs=animation_mode, outputs=diffusion_cadence)
animation_mode.change(fn=disble_3d_related_stuff, inputs=animation_mode, outputs=depth_3d_warping_accord)
animation_mode.change(fn=disble_3d_related_stuff, inputs=animation_mode, outputs=fov_accord)
animation_mode.change(fn=disble_3d_related_stuff, inputs=animation_mode, outputs=only_3d_motion_column)
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=force_grayscale_column)
animation_mode.change(fn=disable_pers_flip_accord, inputs=animation_mode, outputs=perspective_flip_accord)
animation_mode.change(fn=disable_pers_flip_accord, inputs=animation_mode, outputs=both_anim_mode_motion_params_column)
#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)
hybrid_comp_mask_type.change(fn=change_comp_mask_x_visibility, inputs=hybrid_comp_mask_type, outputs=hybrid_comp_mask_row)
hybrid_motion.change(fn=disable_by_non_optical_flow, inputs=hybrid_motion, outputs=hybrid_flow_method)
hybrid_motion.change(fn=disable_by_comp_mask, inputs=hybrid_motion, outputs=hybrid_motion_use_prev_img)
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]
for output in hybrid_composite_outputs:
hybrid_composite.change(fn=disable_by_hybrid_composite, 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=disable_by_comp_mask, 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)
noise_type.change(fn=change_perlin_visibility, inputs=noise_type, outputs=perlin_row)
skip_video_for_run_all_outputs = [fps_out_format_row, soundtrack_row, ffmpeg_quality_accordion, store_frames_in_ram, make_gif, r_upscale_row]
for output in skip_video_for_run_all_outputs:
skip_video_for_run_all.change(fn=change_visibility_from_skip_video, inputs=skip_video_for_run_all, outputs=output)
# 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,
rotation_3d_x, rotation_3d_y, rotation_3d_z,
enable_perspective_flip,
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, 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,
kernel_schedule, sigma_schedule, amount_schedule, threshold_schedule,
color_coherence, color_coherence_video_every_N_frames, color_force_grayscale,
diffusion_cadence,
noise_type, perlin_w, perlin_h, perlin_octaves, perlin_persistence,
use_depth_warping, 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_method, hybrid_composite, 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_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, ddim_eta,
n_batch,
save_settings, save_samples, display_samples,
save_sample_per_step, show_sample_per_step,
batch_name, filename_format,
seed_behavior, seed_iter_N,
use_init, from_img2img_instead_of_link, 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'''
).replace("\n", "").replace("\r", "").replace(" ", "").split(',')
video_args_names = str(r'''skip_video_for_run_all,
fps, make_gif, output_format, ffmpeg_location, ffmpeg_crf, ffmpeg_preset,
add_soundtrack, soundtrack_path,
r_upscale_video, r_upscale_model, r_upscale_factor, r_upscale_keep_imgs,
render_steps,
path_name_modifier, image_path, mp4_path, 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(',')
component_names = ['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()
settings_component_names = [name for name in 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'] + 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_latent'] = None
args_dict['init_sample'] = None
args_dict['init_c'] = 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):
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'])
positive_prompts = args_dict_main['animation_prompts_positive']
negative_prompts = args_dict_main['animation_prompts_negative']
# remove --neg from negative_prompts if recieved by mistake
negative_prompts = negative_prompts.replace('--neg', '')
for key in root.animation_prompts:
animationPromptCurr = root.animation_prompts[key]
root.animation_prompts[key] = f"{positive_prompts} {animationPromptCurr} {'' if '--neg' in animationPromptCurr else '--neg'} {negative_prompts}"
from deforum_helpers.settings import load_args
if override_settings_with_file:
load_args(args_dict, anim_args_dict, parseq_args_dict, loop_args_dict, controlnet_args_dict, custom_settings_file, root)
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 % 64, (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
p.ddim_eta = args.ddim_eta
# TODO: Handle batch name dynamically?
current_arg_list = [args, anim_args, video_args, parseq_args]
args.outdir = os.path.join(p.outpath_samples, 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)
args.seed = get_fixed_seed(args.seed)
args.timestring = time.strftime('%Y%m%d%H%M%S')
args.strength = max(0.0, min(1.0, args.strength))
if not args.use_init:
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
return root, args, anim_args, video_args, parseq_args, loop_args, controlnet_args
def print_args(args):
print("ARGS: /n")
for key, value in args.__dict__.items():
print(f"{key}: {value}")
# 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, f_location, f_crf, f_preset, 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 :)")
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)
# Local gradio-to-upscalers function. *Needs* to stay here since we do Root() and use gradio elements directly, to be changed in the future
def upload_vid_to_upscale(vid_to_upscale_chosen_file, selected_tab, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_keep_imgs, ffmpeg_location, ffmpeg_crf, ffmpeg_preset):
# print msg and do nothing if vid not uploaded
if not vid_to_upscale_chosen_file:
return print("Please upload a video :)")
process_upscale_vid_upload_logic(vid_to_upscale_chosen_file, selected_tab, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, vid_to_upscale_chosen_file.orig_name, upscale_keep_imgs, ffmpeg_location, ffmpeg_crf, ffmpeg_preset)
def ncnn_upload_vid_to_upscale(vid_path, in_vid_fps, in_vid_res, out_vid_res, upscale_model, upscale_factor, keep_imgs, f_location, f_crf, f_preset):
if vid_path is None:
print("Please upload a video :)")
return
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)