diff options
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | javascript/dragdrop.js | 24 | ||||
| -rw-r--r-- | javascript/ui.js | 5 | ||||
| -rw-r--r-- | modules/processing.py | 2 | ||||
| -rw-r--r-- | modules/shared.py | 3 | ||||
| -rw-r--r-- | script.js | 21 | ||||
| -rw-r--r-- | scripts/img2imgalt.py | 68 |
7 files changed, 104 insertions, 20 deletions
@@ -21,3 +21,4 @@ __pycache__ /user.css /.idea notification.mp3 +/SwinIR diff --git a/javascript/dragdrop.js b/javascript/dragdrop.js index c01f66e2..5aac57f7 100644 --- a/javascript/dragdrop.js +++ b/javascript/dragdrop.js @@ -68,13 +68,19 @@ window.addEventListener('paste', e => { if ( ! isValidImageList( files ) ) { return; } - [...gradioApp().querySelectorAll('input[type=file][accept="image/x-png,image/gif,image/jpeg"]')] - .filter(input => !input.matches('.\\!hidden input[type=file]')) - .forEach(input => { - input.files = files; - input.dispatchEvent(new Event('change')) - }); - [...gradioApp().querySelectorAll('[data-testid="image"]')] - .filter(imgWrap => !imgWrap.closest('.\\!hidden')) - .forEach(imgWrap => dropReplaceImage( imgWrap, files )); + + const visibleImageFields = [...gradioApp().querySelectorAll('[data-testid="image"]')] + .filter(el => uiElementIsVisible(el)); + if ( ! visibleImageFields.length ) { + return; + } + + const firstFreeImageField = visibleImageFields + .filter(el => el.querySelector('input[type=file]'))?.[0]; + + dropReplaceImage( + firstFreeImageField ? + firstFreeImageField : + visibleImageFields[visibleImageFields.length - 1] + , files ); }); diff --git a/javascript/ui.js b/javascript/ui.js index 076e9436..7db4db48 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -1,9 +1,8 @@ // various functions for interation with ui.py not large enough to warrant putting them in separate files function selected_gallery_index(){ - var gr = gradioApp() - var buttons = gradioApp().querySelectorAll(".gallery-item") - var button = gr.querySelector(".gallery-item.\\!ring-2") + var buttons = gradioApp().querySelectorAll('[style="display: block;"].tabitem .gallery-item') + var button = gradioApp().querySelector('[style="display: block;"].tabitem .gallery-item.\\!ring-2') var result = -1 buttons.forEach(function(v, i){ if(v==button) { result = i } }) diff --git a/modules/processing.py b/modules/processing.py index 0246e094..3abf3181 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -406,7 +406,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: index_of_first_image = 1
if opts.grid_save:
- images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p)
+ images.save_image(grid, p.outpath_grids, "grid", all_seeds[0], all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
devices.torch_gc()
return Processed(p, output_images, all_seeds[0], infotext(), subseed=all_subseeds[0], all_prompts=all_prompts, all_seeds=all_seeds, all_subseeds=all_subseeds, index_of_first_image=index_of_first_image)
diff --git a/modules/shared.py b/modules/shared.py index c32da110..bd030fe8 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -66,7 +66,7 @@ class State: job = ""
job_no = 0
job_count = 0
- job_timestamp = 0
+ job_timestamp = '0'
sampling_step = 0
sampling_steps = 0
current_latent = None
@@ -80,6 +80,7 @@ class State: self.job_no += 1
self.sampling_step = 0
self.current_image_sampling_step = 0
+
def get_job_timestamp(self):
return datetime.datetime.now().strftime("%Y%m%d%H%M%S")
@@ -39,3 +39,24 @@ document.addEventListener("DOMContentLoaded", function() { }); mutationObserver.observe( gradioApp(), { childList:true, subtree:true }) }); + +/** + * checks that a UI element is not in another hidden element or tab content + */ +function uiElementIsVisible(el) { + let isVisible = !el.closest('.\\!hidden'); + if ( ! isVisible ) { + return false; + } + + while( isVisible = el.closest('.tabitem')?.style.display !== 'none' ) { + if ( ! isVisible ) { + return false; + } else if ( el.parentElement ) { + el = el.parentElement + } else { + break; + } + } + return isVisible; +}
\ No newline at end of file diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py index 7b4ba244..0ef137f7 100644 --- a/scripts/img2imgalt.py +++ b/scripts/img2imgalt.py @@ -59,7 +59,55 @@ def find_noise_for_image(p, cond, uncond, cfg_scale, steps): return x / x.std()
-Cached = namedtuple("Cached", ["noise", "cfg_scale", "steps", "latent", "original_prompt", "original_negative_prompt"])
+Cached = namedtuple("Cached", ["noise", "cfg_scale", "steps", "latent", "original_prompt", "original_negative_prompt", "sigma_adjustment"])
+
+
+# Based on changes suggested by briansemrau in https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/736
+def find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg_scale, steps):
+ x = p.init_latent
+
+ s_in = x.new_ones([x.shape[0]])
+ dnw = K.external.CompVisDenoiser(shared.sd_model)
+ sigmas = dnw.get_sigmas(steps).flip(0)
+
+ shared.state.sampling_steps = steps
+
+ for i in trange(1, len(sigmas)):
+ shared.state.sampling_step += 1
+
+ x_in = torch.cat([x] * 2)
+ sigma_in = torch.cat([sigmas[i - 1] * s_in] * 2)
+ cond_in = torch.cat([uncond, cond])
+
+ c_out, c_in = [K.utils.append_dims(k, x_in.ndim) for k in dnw.get_scalings(sigma_in)]
+
+ if i == 1:
+ t = dnw.sigma_to_t(torch.cat([sigmas[i] * s_in] * 2))
+ else:
+ t = dnw.sigma_to_t(sigma_in)
+
+ eps = shared.sd_model.apply_model(x_in * c_in, t, cond=cond_in)
+ denoised_uncond, denoised_cond = (x_in + eps * c_out).chunk(2)
+
+ denoised = denoised_uncond + (denoised_cond - denoised_uncond) * cfg_scale
+
+ if i == 1:
+ d = (x - denoised) / (2 * sigmas[i])
+ else:
+ d = (x - denoised) / sigmas[i - 1]
+
+ dt = sigmas[i] - sigmas[i - 1]
+ x = x + d * dt
+
+ sd_samplers.store_latent(x)
+
+ # This shouldn't be necessary, but solved some VRAM issues
+ del x_in, sigma_in, cond_in, c_out, c_in, t,
+ del eps, denoised_uncond, denoised_cond, denoised, d, dt
+
+ shared.state.nextjob()
+
+ return x / sigmas[-1]
class Script(scripts.Script):
@@ -78,9 +126,10 @@ class Script(scripts.Script): cfg = gr.Slider(label="Decode CFG scale", minimum=0.0, maximum=15.0, step=0.1, value=1.0)
st = gr.Slider(label="Decode steps", minimum=1, maximum=150, step=1, value=50)
randomness = gr.Slider(label="Randomness", minimum=0.0, maximum=1.0, step=0.01, value=0.0)
- return [original_prompt, original_negative_prompt, cfg, st, randomness]
+ sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False)
+ return [original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment]
- def run(self, p, original_prompt, original_negative_prompt, cfg, st, randomness):
+ def run(self, p, original_prompt, original_negative_prompt, cfg, st, randomness, sigma_adjustment):
p.batch_size = 1
p.batch_count = 1
@@ -88,7 +137,10 @@ class Script(scripts.Script): def sample_extra(conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
lat = (p.init_latent.cpu().numpy() * 10).astype(int)
- same_params = self.cache is not None and self.cache.cfg_scale == cfg and self.cache.steps == st and self.cache.original_prompt == original_prompt and self.cache.original_negative_prompt == original_negative_prompt
+ same_params = self.cache is not None and self.cache.cfg_scale == cfg and self.cache.steps == st \
+ and self.cache.original_prompt == original_prompt \
+ and self.cache.original_negative_prompt == original_negative_prompt \
+ and self.cache.sigma_adjustment == sigma_adjustment
same_everything = same_params and self.cache.latent.shape == lat.shape and np.abs(self.cache.latent-lat).sum() < 100
if same_everything:
@@ -97,8 +149,11 @@ class Script(scripts.Script): shared.state.job_count += 1
cond = p.sd_model.get_learned_conditioning(p.batch_size * [original_prompt])
uncond = p.sd_model.get_learned_conditioning(p.batch_size * [original_negative_prompt])
- rec_noise = find_noise_for_image(p, cond, uncond, cfg, st)
- self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt)
+ if sigma_adjustment:
+ rec_noise = find_noise_for_image_sigma_adjustment(p, cond, uncond, cfg, st)
+ else:
+ rec_noise = find_noise_for_image(p, cond, uncond, cfg, st)
+ self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt, sigma_adjustment)
rand_noise = processing.create_random_tensors(p.init_latent.shape[1:], [p.seed + x + 1 for x in range(p.init_latent.shape[0])])
@@ -121,6 +176,7 @@ class Script(scripts.Script): p.extra_generation_params["Decode CFG scale"] = cfg
p.extra_generation_params["Decode steps"] = st
p.extra_generation_params["Randomness"] = randomness
+ p.extra_generation_params["Sigma Adjustment"] = sigma_adjustment
processed = processing.process_images(p)
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