├── .gitignore ├── LICENSE ├── README.md ├── loopback-cc-experiments.py └── manual_tests ├── curl-webui.sh ├── dali.b64 ├── dirs2vid.sh ├── hulk.b64 ├── land.b64 └── split-image-list.sh /.gitignore: -------------------------------------------------------------------------------- 1 | demo 2 | *.bin 3 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 Robin Fernandes 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Advanced color correction script forstable-diffusion-webui img2img loopback 2 | 3 | ## **Update:** Color correction is no longer necessary in most cases, thanks to VAEs. [See here for details](https://www.reddit.com/r/StableDiffusion/comments/ydwnc3/good_news_vae_prevents_the_loopback_magenta_skew/). 4 | 5 | 6 | [Stable Diffusion](https://stability.ai/blog/stable-diffusion-public-release) is an AI image generation tool. [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) is a web ui for that tool. 7 | 8 | This repo provides a script for that web ui that implements an extra img2img loopback mode with advanced color correction options. Specifically, it allows you to color-correct the input to each generated frame to the average histogram of a sliding window of previously generated frames. 9 | 10 | 11 | ## Installation 12 | 13 | * Copy `loopback-cc-experiments.py` into the scripts subdirectory in [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui). 14 | * After restarting the webui, you will see a script called `Loopback - color correction experiments` in the scripts list: 15 | 16 | 17 | ## Background 18 | 19 | When repeatedly looping a generated image back in as the input image for a subsequent generation, Stable Diffusion skews to magenta. 20 | 21 | This recreates in all forks I've tried, as well as in Dream Studio – including on model v1.5. As a result, most UIs now incorporate some form of colour correction to work around the issue, namely by matching the output of every frame to the input's colour range. You can see some examples on https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/847. 22 | 23 | Colour-correcting in this way has some drawbacks, such masking desirable colour shifts (e.g. you can't colorise a black and white photo). Therefore, this script is an attempt to provide more control over the color correction logic so that you can tweak it to better suit your usecase. 24 | 25 | This is just a workaround: ideally we'd prevent Stable Diffusion's magenta skew, and none of this would be necessary. However, there doesn't appear to be a known root cause for this issue yet, so in the mean time, this script might be useful to some. 26 | 27 | 28 | ## Usage 29 | 30 | The script provides the following options: 31 | 32 | * **Include input image in target** whether to use the colours of the input image when applying colour correction. 33 | * `never` - don't use the colours of the input image at all in the colour correction process. 34 | * `first` - (default) only use the colours of the input image when processing the first frame. 35 | * `always` - always add the initial image to the list of images to use for color correction. How much influence the initial image has depends on how many other images are in the color correction window. For example, if you set the window size to `0` and this value to `always`, all frames will be color corrected to the input image (same behaviour as the default with normal loopback mode). 36 | * window size (default: -1) how many frames to average over when computing the target color histogram. -1 means grow the window frames a processed, always starting at frame 0 and ending at the processed frame if slide rate is 1. 37 | * **window slide rate** (default: 1) how fast to move the end of the window relative to the frame generation. For example, if the loopback is 80 frames long, a slide rate of `0.5` means that on the last generated frame, the window ends on frame 40. 38 | * **window lag** (default: 0) how many frames the end of the window should lag behind the current frame. For example, a delay of `5` means the first 5 frames will have no color correction, and from the 6th frame, a window ending at frame 0 will begin to apply. 39 | * **color correction interval** (default: 1) do color correction every Nth frame, skip other frames. Default of 1 means color correction is applied on every frame. 40 | 41 | ### Notes 42 | With this script: 43 | 44 | * Color correction is applied **regardless of whether you have color correction enabled in the settings**. The script's sole purpose is to do color correction. If you don't want color correction, use the main loopback script. :) 45 | * Color correction is **always applied after saving the image** for a given loop, but before feeding the image into the next generation step. This is different from "official" color correction logic, where the default behaviour is to save the image after color correction, and you optionally save an extra file before color correction (which typically looks better). See https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/847 for details. 46 | 47 | 48 | ## Examples 49 | 50 | All examples below were generated with this script, then converted to video with a color histogram using ffmpeg (see [dir2vid.sh](https://github.com/rewbs/stable-diffusion-loopback-color-correction-script/blob/master/manual_tests/dirs2vid.sh) for specifics). The videos were combined into a grid [following this approach, also with ffmpeg](https://ottverse.com/stack-videos-horizontally-vertically-grid-with-ffmpeg/). 51 | 52 | 53 | ### Natural skin tones from a green init image 54 | 55 | * Prompt: `Classy studio photo portrait with (natural skin tones).` 56 | * Params: Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 8-87, Denoising strength: 0.5 57 | * Initial image: 58 | 59 | 60 | In the video below: 61 | * **Top-left:** (for reference) No color correction. Here we see the image rapidly skewing to magenta. 62 | * **Top-right:** (for reference) Correct all frames to the input histogram, i.e. default official behaviour. Here we see the generated images cannot pull away from the green palette of the input. 63 | * **Mid-left:** Correct to the average of input plus all previously generated frames (window size: -1; slide rate: 1; lag: 0). Here we see natural skin tones emerging. 64 | * **Mid-right:** Correct to average of a window 10 frames wide, moving at 75% the speed of generation (window size: 10; slide rate: 0.75; lag: 0). This is roughly equivalent to the previous. 65 | * **Bot-left:** Correct to the average of a window 5 frames wide, running up to the last generated frame (window size: 5; slide rate: 1; lag: 0). Here we see a blue skew emerging towards the end of the loop, which is common with narrow windows that only account for the most recently generated images. The cause is not known but is possibly a cyan skew related to overcorrecting away from the magenta skew. 66 | * **Bot-right:** Correct to the average of a window 5 frames wide, lagging 4 frames behind the last generated frame (window size: 5; slide rate: 1; lag: 4). This helps mitigate the cyan/blue skew, resulting in simlar results to the middle row. 67 | 68 | https://user-images.githubusercontent.com/74455/192528827-c4696a99-9cf6-4ff7-8771-78ef835e7d0c.mp4 69 | 70 | 71 | ### Colour from a black and white init image 72 | 73 | * Prompt: `(Colorful) color photo of a man with yellow hair and a rainbow hat.` 74 | * Params: Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 24-103, Denoising strength: 0.68 75 | * Initial image: 76 | 77 | 78 | In the video below: 79 | * **Top-left:** (for reference) No color correction. Here the image does not skew to magenta too quickly because the denoise strength is a bit higher. However, the image still degrades aggressively. 80 | * **Top-right:** (for reference) Correct all frames to the input histogram, i.e. default official behaviour. Here we see the generated images struggle to introduce colour: each generation adds a bit of colour, but is reset to B&W before being fed back into the loop, resulting in a washed out result overall. 81 | * **Mid-left:** Correct to the average of input plus all previously generated frames (window size: -1; slide rate: 1; lag: 0). Here we get pretty good results but still a little washed out. 82 | * **Mid-right:** Correct to average of the first 75% of images generated so far (window size: -1; slide rate: 0.75; lag: 0). It's interesting to see how a little change in color palette can lead to completely different output images from about frame 15. 83 | * **Bot-left:** Correct to the average of a window 5 frames wide, running up to the last generated frame (window size: 5; slide rate: 1; lag: 0). 84 | * **Bot-right:** Correct to the average of a window 5 frames wide, lagging 4 frames behind the last generated frame (window size: 5; slide rate: 1; lag: 4). 85 | 86 | https://user-images.githubusercontent.com/74455/192535122-dbb1d5b4-3338-4410-bdc4-eee7e33818f5.mp4 87 | 88 | ### Counter example 89 | 90 | In this example, the "official" color correction is clearly the winner. The input color palette is perfectly fine for the type of output being generated. Any attempt to apply a different correction seems to result in a reduction of the colours used, and ultimately a simplification and/or undesirable color fade. I don't know why this is: the alternative color corrections should theoretically allow the animation to veer into different colors, without necessarily converging into murkiness. :) 91 | 92 | * Prompt: Dramatic 4k high detail urban dense utopian cityscape at sunset. 93 | * Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 20-99, Size: 512x512, Denoising strength: 0.6 94 | * Initial image: 95 | 96 | 97 | https://user-images.githubusercontent.com/74455/192546570-6ea0c224-daea-46e8-b578-7fee30f6808d.mp4 98 | -------------------------------------------------------------------------------- /loopback-cc-experiments.py: -------------------------------------------------------------------------------- 1 | # +--( Advanced color correction script for stable-diffusion-webui img2img loopback )--+ 2 | # | | 3 | # | For more information and the latest version: | 4 | # | https://github.com/rewbs/stable-diffusion-loopback-color-correction-script | 5 | # | | 6 | # +-----------------------------------------------------------------------------------+ 7 | 8 | import numpy as np 9 | import logging 10 | from pprint import pformat 11 | from tqdm import trange 12 | import glob 13 | import cv2 14 | 15 | import modules.scripts as scripts 16 | import gradio as gr 17 | 18 | from modules import processing, shared, sd_samplers, images 19 | from modules.processing import Processed 20 | from modules.sd_samplers import samplers 21 | from modules.shared import opts, cmd_opts, state 22 | 23 | class Script(scripts.Script): 24 | def title(self): 25 | return "Loopback - color correction experiments" 26 | 27 | def show(self, is_img2img): 28 | return is_img2img 29 | 30 | def ui(self, is_img2img): 31 | loops = gr.Slider(minimum=1, maximum=500, step=1, label='Loops', value=4) 32 | denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1) 33 | cc_include_input = gr.Radio(label='Include input image in color target', choices=['never', 'first', 'always'], value='first') 34 | cc_window_size = gr.Slider(minimum=-1, maximum=50, step=1, label='Color correction window size', value=-1) 35 | cc_window_rate = gr.Slider(minimum=0.1, maximum=1, step=0.1, label='Color correction window slide rate', value=1) 36 | cc_window_delay = gr.Slider(minimum=1, maximum=10, step=1, label='Color correction window lag', value=0) 37 | cc_interval = gr.Slider(minimum=1, maximum=50, step=1, label='Color correction interval', value=1) 38 | 39 | return [loops, denoising_strength_change_factor, cc_include_input, cc_window_size, cc_window_rate, cc_window_delay, cc_interval] 40 | 41 | def run(self, p, loops, denoising_strength_change_factor, cc_include_input, cc_window_size, cc_window_rate, cc_window_delay, cc_interval): 42 | logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.DEBUG) 43 | 44 | processing.fix_seed(p) 45 | batch_count = p.n_iter 46 | 47 | logging.info(f"Starting loopback with: \n" 48 | f"loops: {loops}; \n" 49 | f"initial seed: {p.seed}; \n" 50 | f"initial denoising strength: {p.denoising_strength}; \n" 51 | f"denoising strength change factor: {denoising_strength_change_factor}; \n" 52 | f"color correction enabled in main options?: {opts.img2img_color_correction}; \n" 53 | f"Color correction window size: {cc_window_size} \n" 54 | f"Color correction window slide rate: {cc_window_rate} \n" 55 | f"Color correction window start delay: {cc_window_delay} \n" 56 | f"apply cc every N loops: {cc_interval} \n") 57 | 58 | p.batch_size = 1 59 | p.n_iter = 1 60 | 61 | output_images, info = None, None 62 | initial_seed = None 63 | initial_info = None 64 | 65 | grids = [] 66 | all_images = [] 67 | state.job_count = loops * batch_count 68 | 69 | # HACK - ideally scripts could opt in to hooks at various points in the processing loop including file saving. 70 | logging.info("Overriding color correction option to false in main processing so that we can control color correction in the script loop.") 71 | old_cc_opt = opts.img2img_color_correction 72 | opts.img2img_color_correction = False 73 | p.color_corrections = None 74 | 75 | original_input_image_resized = images.resize_image(p.resize_mode, p.init_images[0], p.width, p.height) 76 | 77 | try: 78 | 79 | for n in range(batch_count): 80 | history = [] 81 | uncorrected_images = [] 82 | 83 | for i in range(loops): 84 | p.n_iter = 1 85 | p.batch_size = 1 86 | p.do_not_save_grid = True 87 | 88 | loop_index = i+1 89 | cc_window_start, cc_window_end = self.compute_cc_target_window(loop_index, cc_window_delay, cc_window_size, cc_window_rate) 90 | do_cc = loop_index%cc_interval==0 91 | 92 | state.job = f"Iteration {loop_index}/{loops}, batch {n + 1}/{batch_count}" 93 | logging.info(f"it:{loop_index} - seed:{p.seed}; denoising_strength:{p.denoising_strength}; ") 94 | 95 | processed = processing.process_images(p) 96 | 97 | if initial_seed is None: 98 | initial_seed = processed.seed 99 | initial_info = processed.info 100 | 101 | init_img = processed.images[0] 102 | 103 | uncorrected_images.append(processed.images[0]) 104 | if (cc_window_end>0): 105 | target_images = uncorrected_images[cc_window_start:cc_window_end] 106 | else: 107 | target_images = [] 108 | 109 | if cc_include_input == 'first' and cc_window_start==0: 110 | target_images.append(original_input_image_resized) 111 | logging.info(f"Window start is 0 so including initital image in correction target (total target images: {len(target_images)})") 112 | elif cc_include_input == 'always': 113 | target_images.append(original_input_image_resized) 114 | logging.info(f"Forcing initital image into correction target (total target images: {len(target_images)})") 115 | else: 116 | logging.info(f"Initital image NOT included in correction target (total target images: {len(target_images)})") 117 | target_histogram = self.compute_cc_target(target_images) 118 | 119 | 120 | p.extra_generation_params = { 121 | "Batch": n, 122 | "Loop": loop_index, 123 | "Denoising strength change factor": denoising_strength_change_factor, 124 | "Color correction interval": cc_interval, 125 | "Color correction input image use": cc_include_input, 126 | "Color correction on this image": do_cc, 127 | "Color correction window size (desired)": cc_window_size, 128 | "Color correction window size (effective)": len(target_images) if target_images is not None else 0, 129 | "Color correction window slide rate": cc_window_rate, 130 | "Color correction window lag": cc_window_delay, 131 | "Color correction window pos start on this image": cc_window_start, 132 | "Color correction window pos end on this image": cc_window_end 133 | } 134 | logging.info(pformat(p.extra_generation_params)) 135 | 136 | if do_cc: 137 | if target_histogram is None: 138 | logging.info(f"Skipping color correction on loop {loop_index} (cc interval: {cc_interval}, target frames: {cc_window_start} to {cc_window_end})") 139 | else: 140 | logging.info(f"Applying color correction on loop {loop_index} (cc interval: {cc_interval}; target frames: {cc_window_start} to {cc_window_end}; effective window size: {len(target_images)})") 141 | init_img = processing.apply_color_correction(target_histogram, init_img) 142 | #images.save_image(init_img, p.outpath_samples, "", p.seed, p.prompt, opts.samples_format, info=None, p=p, suffix="-after-color-correction") 143 | else: 144 | logging.debug(f"Skipping color correction on loop {loop_index} because interval condition not met (interval: {cc_interval}), target frames: {cc_window_start} to {cc_window_end})") 145 | 146 | p.init_images = [init_img] 147 | p.seed = processed.seed + 1 148 | p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1) 149 | history.append(processed.images[0]) 150 | 151 | grid = images.image_grid(history, rows=1) 152 | if opts.grid_save: 153 | images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p) 154 | 155 | grids.append(grid) 156 | all_images += history 157 | 158 | if opts.return_grid: 159 | all_images = grids + all_images 160 | 161 | processed = Processed(p, all_images, initial_seed, initial_info) 162 | return processed 163 | 164 | finally: 165 | logging.info("Restoring CC option to: %s", old_cc_opt) 166 | opts.img2img_color_correction = old_cc_opt 167 | logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.WARNING) 168 | 169 | def compute_cc_target_window(self, current_pos, window_delay, window_size, window_rate): 170 | cc_window_end = round((current_pos-window_delay)*window_rate) 171 | if window_size == -1: 172 | cc_window_start = 0 173 | else: 174 | cc_window_start = max(0, cc_window_end-window_size) 175 | return cc_window_start, cc_window_end 176 | 177 | def compute_cc_target(self, target_images): 178 | if target_images is None or len(target_images)==0: 179 | return None 180 | 181 | target_histogram = (cv2.cvtColor(np.asarray(target_images[0].copy()), cv2.COLOR_RGB2LAB)*0).astype('float64') 182 | for img in target_images: 183 | target_histogram_component = cv2.cvtColor(np.asarray(img.copy()), cv2.COLOR_RGB2LAB).astype('float64') 184 | target_histogram += (target_histogram_component/len(target_images)).astype('float64') 185 | 186 | target_histogram=target_histogram.astype('uint8') 187 | 188 | return target_histogram -------------------------------------------------------------------------------- /manual_tests/curl-webui.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | set -o nounset 3 | 4 | #!/bin/bash 5 | set -o nounset 6 | 7 | function runCurl() { 8 | CC_TYPE=$1 9 | CC_WIDTH=$2 10 | CC_RATE=$3 11 | CC_DELAY=$4 12 | CC_INT=$5 13 | 14 | echo '{"fn_index":28,"data":[0,"'$PROMPT'","","None","None","'$(cat $FILE)'",null,null,null,"Draw mask",'$STEPS',"'$DIFF'",4,"fill",'$RESTORE_FACES',false,1,1,7,'$DENOISE','$SEED',-1,0,0,0,false,512,512,"Just resize",false,32,"Inpaint masked","","","Loopback - color correction experiments","Seed","","Steps","",true,false,"

Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8

",128,8,["left","right","up","down"],1,0.05,"","",1,50,0,false,null,"",'$LOOPS',1,"'$CC_TYPE'",'$CC_WIDTH','$CC_RATE','$CC_DELAY','$CC_INT',false,128,4,"fill",["left","right","up","down"],4,1,"

Will upscale the image to twice the dimensions; use width and height sliders to set tile size

",64,"None",null,"",""],"session_hash":"nb79h3wwdee"}' > data.bin 15 | 16 | curl "$HOST" \ 17 | -H 'accept: */*' \ 18 | -H 'content-type: application/json' \ 19 | --data '@./data.bin' \ 20 | --compressed >> out-$(date +%s).bin 21 | } 22 | 23 | # function runCurl_origLoopback() { 24 | # 25 | # echo '{"fn_index":27,"data":[0,"'$PROMPT'","","None","None","'$(cat $FILE)'",null,null,null,"Draw mask",20,"Euler a",4,"fill",'$RESTORE_FACES',false,1,1,7,'$DENOISE','$SEED',-1,0,0,0,false,512,512,"Just resize",false,32,"Inpaint masked","","","Loopback","Seed","","Steps","",true,"

Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8

",128,4,["left","right","up","down"],1,0.05,"","",1,50,0,false,null,"",false,128,4,"fill",["left","right","up","down"],'$LOOPS',1,"

Will upscale the image to twice the dimensions; use width and height sliders to set tile size

",64,"None",null,"",""],"session_hash":"n61d76buoh"}' > data.bin 26 | # 27 | # curl "$HOST" \ 28 | # -H 'accept: */*' \ 29 | # -H 'content-type: application/json' \ 30 | # --data '@./data.bin' \ 31 | # --compressed >> out-$(date +%s).bin 32 | # 33 | # } 34 | 35 | # function setColorCorrection() { 36 | # echo "WARNING: setting color correction nukes all setting changes" 37 | 38 | # curl "$HOST" \ 39 | # -H 'accept: */*' \ 40 | # -H 'content-type: application/json' \ 41 | # --data-raw '{"fn_index":38,"data":["",true,true,"","","outputs/txt2img-images","outputs/img2img-images","outputs/extras-images","","outputs/txt2img-grids","outputs/img2img-grids","log/images",true,false,"png",false,true,false,"png",false,true,4,100,false,true,false,'$1',true,true,true,"",true,true,true,192,8,["Real-ESRGAN 4x plus","Real-ESRGAN 4x plus anime 6B"],192,8,100,1,1,[],null,true,10,true,8,"CodeFormer",0.5,true,false,false,true,1,24,48,1500,null,true,true,false],"session_hash":"n61d76buoh"}' \ 42 | # --compressed 43 | 44 | # } 45 | 46 | HOST="https://29300.gradio.app/api/predict/" 47 | 48 | DIFF="Euler a" 49 | STEPS=20 50 | RESTORE_FACES=false 51 | SEED=8 52 | LOOPS=80 53 | DENOISE=0.5 54 | 55 | function doAll() { 56 | echo "No color correction" 57 | runCurl "window" -1 1 0 1000 58 | 59 | echo "Color correct every frame to the input histogram" 60 | runCurl "input" -1 1 0 1 61 | 62 | echo "Color correct every frame to average of all frames so far" 63 | runCurl "window" -1 1 0 1 64 | 65 | echo "Color correct every frame to average of last 5 frames." 66 | runCurl "window" 5 1 0 1 67 | 68 | echo "Color correct every frame to average of last 10 frames." 69 | runCurl "window" 10 1 0 1 70 | 71 | echo "Color correct every frame to average of 5 frames lagging 4 frames behind the current frame." 72 | runCurl "window" 5 1 4 1 73 | 74 | echo "Color correct every frame to average of 20 frames shifting at 75% the rate of the image generation" 75 | runCurl "window" 20 0.75 0 1 76 | 77 | echo "Color correct every frame to average of first 75% of frames generated so far." 78 | runCurl "window" -1 0.75 0 1 79 | 80 | } 81 | 82 | 83 | # PROMPT="Classy studio photo portrait with (natural skin tones)." 84 | # FILE='hulk.b64' 85 | # DENOISE=0.5 86 | # doAll 87 | 88 | PROMPT="Dramatic 4k high detail urban dense utopian cityscape at sunset." 89 | FILE='land.b64' 90 | SEED=20 91 | DENOISE=0.6 92 | doAll 93 | 94 | # PROMPT="(Colorful) color photo of a man with yellow hair and a rainbow hat." 95 | # FILE='dali.b64' 96 | # SEED=24 97 | # DENOISE=0.68 98 | # RESTORE_FACES=true 99 | # doAll -------------------------------------------------------------------------------- /manual_tests/dirs2vid.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | for d in */ ; do 4 | EXP_NAME=${d%?} 5 | echo "Converting $EXP_NAME..." 6 | ffmpeg -framerate 10 -pattern_type glob -i $EXP_NAME/'*.png' -vf "drawtext=fontfile=Verdana.ttf: text='$EXP_NAME; frame %{frame_num}': start_number=1: x=w-tw*1.1: y=h-lh*1.5: fontcolor=blue: fontsize=20: box=1: boxcolor=white@0.4: boxborderw=5" -c:v libx264 -pix_fmt yuv420p ./$EXP_NAME.mp4 7 | ffmpeg -framerate 10 -pattern_type glob -i $EXP_NAME/'*.png' -filter_complex "histogram=display_mode=overlay,scale=512:512" -an -c:v libx264 -pix_fmt yuv420p ./$EXP_NAME-histo.mp4 8 | ffmpeg -i ./$EXP_NAME.mp4 -i ./$EXP_NAME-histo.mp4 -filter_complex hstack ./$EXP_NAME-combined.mp4 9 | done -------------------------------------------------------------------------------- /manual_tests/hulk.b64: -------------------------------------------------------------------------------- 1 | data:image/png;base64,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 -------------------------------------------------------------------------------- /manual_tests/split-image-list.sh: -------------------------------------------------------------------------------- 1 | #!/bin/zsh 2 | 3 | function move() { 4 | NUM=$1 5 | DEST=$2 6 | mkdir $DEST 7 | mv -- *(D.[1,$NUM]) $DEST 8 | } 9 | 10 | move 160 no-cc 11 | move 160 cc-to-input 12 | move 160 cc-to-average 13 | move 160 cc-5-last-frames 14 | move 160 cc-5-last-frames-lag-1 15 | move 160 cc-5-last-frames-lag-4 16 | move 160 cc-10-frames-75pc-behind 17 | move 160 cc-first-75pc-frames --------------------------------------------------------------------------------