From 93e7dbaa7164c3b7d1dcb6907d5908cc3fa29d30 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 28 Aug 2022 16:38:59 +0300 Subject: [PATCH] support for running custom code (primarily to generate various labeled grids) export for 4chan option --- README.md | 43 +++++++++++++ images/scripting.jpg | Bin 0 -> 1053723 bytes webui.py | 145 +++++++++++++++++++++++++++++-------------- 3 files changed, 140 insertions(+), 48 deletions(-) create mode 100644 images/scripting.jpg diff --git a/README.md b/README.md index a3d722c83..8e40dc68e 100644 --- a/README.md +++ b/README.md @@ -205,3 +205,46 @@ image will be upscaled to twice the original width and height, while width and h will specify the size of individual tiles. At the moment this method does not support batch size. ![](images/sd-upscale.jpg) + +### User scripts +If the program is launched with `--allow-code` option, an extra text input field for script code +is available in txt2img interface. It allows you to input python code that will do the work with +image. If this field is not empty, the processing that would happen normally is skipped. + +In code, access parameters from web UI using the `p` variable, and provide outputs for web UI +using the `display(images, seed, info)` function. All globals from script are also accessible. + +As an example, here is a script that draws a chart seen below (and also saves it as `test/gnomeplot/gnome5.png`): + +```python +steps = [4, 8,12,16, 20] +cfg_scales = [5.0,10.0,15.0] + +def cell(x, y, p=p): + p.steps = x + p.cfg_scale = y + return process_images(p).images[0] + +images = [draw_xy_grid( + xs = steps, + ys = cfg_scales, + x_label = lambda x: f'Steps = {x}', + y_label = lambda y: f'CFG = {y}', + cell = cell +)] + +save_image(images[0], 'test/gnomeplot', 'gnome5') +display(images) +``` + +![](images/scripting.jpg) + +A more simple script that would just process the image and output it normally: + +```python +processed = process_images(p) + +print("Seed was: " + str(processed.seed)) + +display(processed.images, processed.seed, processed.info) +``` diff --git a/images/scripting.jpg b/images/scripting.jpg new file mode 100644 index 0000000000000000000000000000000000000000..5830ea6d6c0c0089023ca2b498427e856223bd02 GIT binary patch literal 1053723 zcmeFZ2UJt-x-L3HM@mqTUZp5Xk=~nh0TBV|BE3qLW@v)aJ4lr#ReG<|oAfFqp%*Ed z&?P%asIo{IOF`2F-XRoGnsF``Mu?NzUQ6S(CamT;<1Xl3IGBD z00{dBTrUEO04~lS+aLdNu^S!%-X9wg0RcV%G0}}1#6-lzH%P&xH%Q1yh>6K=l97Wc zC~i{RAiYI-i-HpSp5l)$0sZkwTs$J|2PsI1Nw9nWliPJSaFd8YizFBqbQ8e23BtVz zy6y*L9-vmQjky0jsm>NtBvls5FP;Q%Qv_Sf9Ry$Q$xm&L)i05uRR-d`_&4Z&Zt;4eq` zD;E5hhr>!c@>wY{#IgAINlcziMcwdQfp*$~yiZ`q{)>Tt%QRZLTj&WxV(rpJnj2y`ruhX!=(mjo zMKj~YmKU^)>l`6Sw|3*ez2kd0gMVfgxH0dB6sixLWREkw2H*t7qde)947D-FH&_p) zW2#?G5wwamGLN+@-;%1|pY|BEqlkUR$Usw4IVC;$`pgJ0n)-)7iUV{z!}G=S;dGOu zvGokM3KFuIu+DnQinvsQP(oi!%O{|1vK$TH z-+%Gb|0#aa-ygAmHkyC`7${Ec9&YZ&$`mH}rFd42sZX=)WDP`b?uNo@Zj?)efxj?(+C~|0D-R{rJHn7*%kq zznrzOurTsuPEVUPPTb0#a}p98Y7B5B*MI=rRH5ev6VTgy_QM&;BtwUeYbP2J>t2c9 zo=wmn580;*8vc~1a;O#MWlsp^Bqqb3UY=(o&{`|Um5}CP?Xx>FhgkO8i^@c53>c}{HM$mQukJQ#%q8Y6^_6K^)H8PcC?}b z!YxUIynj6YGOkS8vpUW5`t8DL9nfy!+e8!hR55C;68d)6S|FndQf8)fN=RBmJDq1v8tPqh}-*a-GAVELbz z`wu+%@60{gO^;xSD_$fRN`M>Ljz0wPM4-w0X|IrTAN(?-=t8?b8UA-eynBzF`5E)V zZ}+(0H+>Y9-?sj_D5GwG-5-uhB08f2jQ>f@Kv>izw04hHT-~PuBRA-5f>%2eWh5ZuMvT3Sl4ryp-;M_3huYoUA1dY}z+tI6qQ*kpsN z4b-P0sG-VbtaU+Pr$ozqIk3^+eSqS_QFBL1;Ji9{h<0qHJzIV!Ljq1m`8A*tsE#nH z|7g&BU=uT(ahzlK_4UDEw&s%7vFKxamCw0UC8%1puYI`zE>58u&irnm9|u;h4iXSc zltE9s1@d`kG+tHjMrpyA?|aV-)yEvgqF%ZmF+8!=F+=Qe;|`v|*f`;50BeVL0RwVs zG|tc+N7*SuN)LTzCX=x5#ud5(vkLETxSKz*vSI&->fP8D(ues-3%4XY<$;SSCh;|I ze$yRitQqOy@DS)3hp4rS(s6w!B1l)kq0W-^liN*l!;< zz`Agk$T&n1y0+b7O5s8ze|t=>p>x9Bc{*~-|AE~1wxyvECAgCON32V11C=;J(>)W5KhbUDR+y$Qi03IQI(2`%Yu*4zbWuxfbL1W zb3mfEpW&FC9O`rO@wi@|M1mFVcV4PE!VrcB@W;T%QNQvBJB$M9^Ey~Bmk3vL9{D0# zCz)>QAG*m|lK2gH{I?pI+pONZHM#u;Vv-rDEi;eFCGP$lbKs$rcIny8L!DMD@sEa0R7tD9BVa)vA0hZWaA>Q7H* z;+wgYJ$pxn9F_SI4(;1-s|1x+8N}Rh`&SD~A#oD7H&w{rVVysdco{2LPIafQ}!|~+Z zuBiU#HfUv}Drn)m&BRuJ{}BH5hlTqwI3_hmRS$IUZ%Ow;CiVCx=FZBBS@F7A!#0oh zZ(KxiaaAbU=xHP0JDG%U^tQq#zUV%N?;nsyNybz1WHUfevrny$-PKpv10qxo%DCU% zKRnLH**KN%^QZou(m0jJ8-rhmp6qlz^-kEPp_Ykr3Ste>D z#ubxkyY7$E4T-EhHAu|ZO#)8CX-u$Vi29px|4SG`*6k{(bGls(iQAkriis3dan5>R z;dhkMXt?bE#4~V~NlUK*5joG=DN4lY7q_Oi^N^*Df>5O!n|ANkZqtRRhHdyhu^;%! 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parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware accleration in browser)") parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") parser.add_argument("--embeddings-dir", type=str, default='embeddings', help="embeddings dirtectory for textual inversion (default: embeddings)") +parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") cmd_opts = parser.parse_args() @@ -132,6 +133,7 @@ class Options: "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"), "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}), "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), + "export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"), "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"), "prompt_matrix_add_to_start": OptionInfo(True, "In prompt matrix, add the variable combination of text to the start of the prompt, rather than the end"), "sd_upscale_upscaler_index": OptionInfo("RealESRGAN", "Upscaler to use for SD upscale", gr.Radio, {"choices": list(sd_upscalers.keys())}), @@ -206,13 +208,12 @@ def torch_gc(): torch.cuda.ipc_collect() -def save_image(image, path, basename, seed, prompt, extension, info=None, short_filename=False): - prompt = sanitize_filename_part(prompt) +def save_image(image, path, basename, seed=None, prompt=None, extension='png', info=None, short_filename=False): - if short_filename: - filename = f"{basename}.{extension}" + if short_filename or prompt is None or seed is None: + filename = f"{basename}" else: - filename = f"{basename}-{seed}-{prompt[:128]}.{extension}" + filename = f"{basename}-{seed}-{sanitize_filename_part(prompt)[:128]}" if extension == 'png' and opts.enable_pnginfo and info is not None: pnginfo = PngImagePlugin.PngInfo() @@ -220,7 +221,23 @@ def save_image(image, path, basename, seed, prompt, extension, info=None, short_ else: pnginfo = None - image.save(os.path.join(path, filename), quality=opts.jpeg_quality, pnginfo=pnginfo) + os.makedirs(path, exist_ok=True) + fullfn = os.path.join(path, f"{filename}.{extension}") + image.save(fullfn, quality=opts.jpeg_quality, pnginfo=pnginfo) + + target_side_length = 4000 + oversize = image.width > target_side_length or image.height > target_side_length + if opts.export_for_4chan and (oversize or os.stat(fullfn).st_size > 4 * 1024 * 1024): + ratio = image.width / image.height + + if oversize and ratio > 1: + image = image.resize((target_side_length, image.height * target_side_length // image.width), LANCZOS) + elif oversize: + image = image.resize((image.width * target_side_length // image.height, target_side_length), LANCZOS) + + image.save(os.path.join(path, f"{filename}.jpg"), quality=opts.jpeg_quality, pnginfo=pnginfo) + + def sanitize_filename_part(text): @@ -244,16 +261,15 @@ def load_gfpgan(): return GFPGANer(model_path=model_path, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None) -def image_grid(imgs, batch_size, force_n_rows=None): - if force_n_rows is not None: - rows = force_n_rows - elif opts.n_rows > 0: - rows = opts.n_rows - elif opts.n_rows == 0: - rows = batch_size - else: - rows = math.sqrt(len(imgs)) - rows = round(rows) +def image_grid(imgs, batch_size=1, rows=None): + if rows is None: + if opts.n_rows > 0: + rows = opts.n_rows + elif opts.n_rows == 0: + rows = batch_size + else: + rows = math.sqrt(len(imgs)) + rows = round(rows) cols = math.ceil(len(imgs) / rows) @@ -427,6 +443,22 @@ def draw_prompt_matrix(im, width, height, all_prompts): return draw_grid_annotations(im, width, height, hor_texts, ver_texts) +def draw_xy_grid(xs, ys, x_label, y_label, cell): + res = [] + + ver_texts = [[GridAnnotation(y_label(y))] for y in ys] + hor_texts = [[GridAnnotation(x_label(x))] for x in xs] + + for y in ys: + for x in xs: + res.append(cell(x, y)) + + + grid = image_grid(res, rows=len(ys)) + grid = draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts) + + return grid + def resize_image(resize_mode, im, width, height): if resize_mode == 0: res = im.resize((width, height), resample=LANCZOS) @@ -742,7 +774,10 @@ class KDiffusionSampler: return samples_ddim -def process_images(p: StableDiffusionProcessing): +Processed = namedtuple('Processed', ['images','seed', 'info']) + + +def process_images(p: StableDiffusionProcessing) -> Processed: """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch""" prompt = p.prompt @@ -753,10 +788,7 @@ def process_images(p: StableDiffusionProcessing): seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed) - os.makedirs(p.outpath, exist_ok=True) - sample_path = os.path.join(p.outpath, "samples") - os.makedirs(sample_path, exist_ok=True) base_count = len(os.listdir(sample_path)) grid_count = len(os.listdir(p.outpath)) - 1 @@ -846,7 +878,7 @@ def process_images(p: StableDiffusionProcessing): if (p.prompt_matrix or opts.grid_save) and not p.do_not_save_grid: if p.prompt_matrix: - grid = image_grid(output_images, p.batch_size, force_n_rows=1 << ((len(prompt_matrix_parts)-1)//2)) + grid = image_grid(output_images, p.batch_size, rows=1 << ((len(prompt_matrix_parts)-1)//2)) try: grid = draw_prompt_matrix(grid, p.width, p.height, prompt_matrix_parts) @@ -863,7 +895,7 @@ def process_images(p: StableDiffusionProcessing): grid_count += 1 torch_gc() - return output_images, seed, infotext() + return Processed(output_images, seed, infotext()) class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): @@ -876,8 +908,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples_ddim = self.sampler.sample(self, x, conditioning, unconditional_conditioning) return samples_ddim - -def txt2img(prompt: str, ddim_steps: int, sampler_index: int, use_GFPGAN: bool, prompt_matrix: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int): +def txt2img(prompt: str, steps: int, sampler_index: int, use_GFPGAN: bool, prompt_matrix: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, height: int, width: int, code: str): outpath = opts.outdir or "outputs/txt2img-samples" p = StableDiffusionProcessingTxt2Img( @@ -887,7 +918,7 @@ def txt2img(prompt: str, ddim_steps: int, sampler_index: int, use_GFPGAN: bool, sampler_index=sampler_index, batch_size=batch_size, n_iter=n_iter, - steps=ddim_steps, + steps=steps, cfg_scale=cfg_scale, width=width, height=height, @@ -895,9 +926,29 @@ def txt2img(prompt: str, ddim_steps: int, sampler_index: int, use_GFPGAN: bool, use_GFPGAN=use_GFPGAN ) - output_images, seed, info = process_images(p) + if code != '' and cmd_opts.allow_code: + p.do_not_save_grid = True + p.do_not_save_samples = True - return output_images, seed, plaintext_to_html(info) + display_result_data = [[], -1, ""] + def display(imgs, s=display_result_data[1], i=display_result_data[2]): + display_result_data[0] = imgs + display_result_data[1] = s + display_result_data[2] = i + + from types import ModuleType + compiled = compile(code, '', 'exec') + module = ModuleType("testmodule") + module.__dict__.update(globals()) + module.p = p + module.display = display + exec(compiled, module.__dict__) + + processed = Processed(*display_result_data) + else: + processed = process_images(p) + + return processed.images, processed.seed, plaintext_to_html(processed.info) class Flagging(gr.FlaggingCallback): @@ -911,7 +962,7 @@ class Flagging(gr.FlaggingCallback): os.makedirs("log/images", exist_ok=True) # those must match the "txt2img" function - prompt, ddim_steps, sampler_name, use_gfpgan, prompt_matrix, ddim_eta, n_iter, n_samples, cfg_scale, request_seed, height, width, images, seed, comment = flag_data + prompt, ddim_steps, sampler_name, use_gfpgan, prompt_matrix, ddim_eta, n_iter, n_samples, cfg_scale, request_seed, height, width, code, images, seed, comment = flag_data filenames = [] @@ -955,6 +1006,7 @@ txt2img_interface = gr.Interface( gr.Number(label='Seed', value=-1), gr.Slider(minimum=64, maximum=2048, step=64, label="Height", value=512), gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512), + gr.Textbox(label="Python script", visible=cmd_opts.allow_code, lines=1) ], outputs=[ gr.Gallery(label="Images"), @@ -1042,29 +1094,30 @@ def img2img(prompt: str, init_img, ddim_steps: int, sampler_index: int, use_GFPG output_images, info = None, None history = [] initial_seed = None + initial_info = None for i in range(n_iter): p.n_iter = 1 p.batch_size = 1 p.do_not_save_grid = True - output_images, seed, info = process_images(p) + processed = process_images(p) if initial_seed is None: - initial_seed = seed + initial_seed = processed.seed + initial_info = processed.info - p.init_img = output_images[0] - p.seed = seed + 1 + p.init_img = processed.images[0] + p.seed = processed.seed + 1 p.denoising_strength = max(p.denoising_strength * 0.95, 0.1) - history.append(output_images[0]) + history.append(processed.images[0]) grid_count = len(os.listdir(outpath)) - 1 - grid = image_grid(history, batch_size, force_n_rows=1) + grid = image_grid(history, batch_size, rows=1) save_image(grid, outpath, f"grid-{grid_count:04}", initial_seed, prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename) - output_images = history - seed = initial_seed + processed = Processed(history, initial_seed, initial_info) elif sd_upscale: initial_seed = None @@ -1094,14 +1147,14 @@ def img2img(prompt: str, init_img, ddim_steps: int, sampler_index: int, use_GFPG for i in range(batch_count): p.init_images = work[i*p.batch_size:(i+1)*p.batch_size] - output_images, seed, info = process_images(p) + processed = process_images(p) if initial_seed is None: - initial_seed = seed - initial_info = info + initial_seed = processed.seed + initial_info = processed.info - p.seed = seed + 1 - work_results += output_images + p.seed = processed.seed + 1 + work_results += processed.images image_index = 0 for y, h, row in grid.tiles: @@ -1114,14 +1167,12 @@ def img2img(prompt: str, init_img, ddim_steps: int, sampler_index: int, use_GFPG grid_count = len(os.listdir(outpath)) - 1 save_image(combined_image, outpath, f"grid-{grid_count:04}", initial_seed, prompt, opts.grid_format, info=initial_info, short_filename=not opts.grid_extended_filename) - output_images = [combined_image] - seed = initial_seed - info = initial_info + processed = Processed([combined_image], initial_seed, initial_info) else: - output_images, seed, info = process_images(p) + processed = process_images(p) - return output_images, seed, plaintext_to_html(info) + return processed.images, processed.seed, plaintext_to_html(processed.info) sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg" @@ -1192,9 +1243,7 @@ def run_extras(image, GFPGAN_strength, RealESRGAN_upscaling, RealESRGAN_model_in if have_realesrgan and RealESRGAN_upscaling != 1.0: image = upscale_with_realesrgan(image, RealESRGAN_upscaling, RealESRGAN_model_index) - os.makedirs(outpath, exist_ok=True) base_count = len(os.listdir(outpath)) - save_image(image, outpath, f"{base_count:05}", None, '', opts.samples_format, short_filename=True) return image, 0, ''

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