add execution timings to output

change the text output element to HTML

1 files changed, 34 insertions, 8 deletions

diff --git a/webui.py b/webui.py
index 742615e1..51ce02c7 100644
--- a/webui.py
+++ b/webui.py
@@ -12,6 +12,8 @@ from contextlib import contextmanager, nullcontext
 import mimetypes

 import random

 import math

+import html

+import time

 

 import k_diffusion as K

 from ldm.util import instantiate_from_config

@@ -160,6 +162,11 @@ def save_image(image, path, basename, seed, prompt, extension, info=None, short_
     image.save(os.path.join(path, filename), quality=opt.jpeg_quality, pnginfo=pnginfo)

 

 

+def plaintext_to_html(text):

+    text = "".join([f"<p>{html.escape(x)}</p>\n" for x in text.split('\n')])

+    return text

+

+

 def load_GFPGAN():

     model_name = 'GFPGANv1.3'

     model_path = os.path.join(GFPGAN_dir, 'experiments/pretrained_models', model_name + '.pth')

@@ -331,6 +338,20 @@ def check_prompt_length(prompt, comments):
     comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")

 

 

+def wrap_gradio_call(func):

+    def f(*p1, **p2):

+        t = time.perf_counter()

+        res = list(func(*p1, **p2))

+        elapsed = time.perf_counter() - t

+

+        # last item is always HTML

+        res[-1] = res[-1] + f"<p class='performance'>Time taken: {elapsed:.2f}s</p>"

+

+        return tuple(res)

+

+    return f

+

+

 def process_images(outpath, func_init, func_sample, prompt, seed, sampler_name, batch_size, n_iter, steps, cfg_scale, width, height, prompt_matrix, use_GFPGAN, do_not_save_grid=False):

     """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"""

 

@@ -484,7 +505,7 @@ def txt2img(prompt: str, ddim_steps: int, sampler_name: str, use_GFPGAN: bool, p
 

     del sampler

 

-    return output_images, seed, info

+    return output_images, seed, plaintext_to_html(info)

 

 

 class Flagging(gr.FlaggingCallback):

@@ -529,7 +550,7 @@ class Flagging(gr.FlaggingCallback):
 

 

 txt2img_interface = gr.Interface(

-    txt2img,

+    wrap_gradio_call(txt2img),

     inputs=[

         gr.Textbox(label="Prompt", placeholder="A corgi wearing a top hat as an oil painting.", lines=1),

         gr.Slider(minimum=1, maximum=150, step=1, label="Sampling Steps", value=50),

@@ -547,7 +568,7 @@ txt2img_interface = gr.Interface(
     outputs=[

         gr.Gallery(label="Images"),

         gr.Number(label='Seed'),

-        gr.Textbox(label="Copy-paste generation parameters"),

+        gr.HTML(),

     ],

     title="Stable Diffusion Text-to-Image K",

     description="Generate images from text with Stable Diffusion (using K-LMS)",

@@ -650,14 +671,14 @@ def img2img(prompt: str, init_img, ddim_steps: int, use_GFPGAN: bool, prompt_mat
 

     del sampler

 

-    return output_images, seed, info

+    return output_images, seed, plaintext_to_html(info)

 

 

 sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"

 sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None

 

 img2img_interface = gr.Interface(

-    img2img,

+    wrap_gradio_call(img2img),

     inputs=[

         gr.Textbox(placeholder="A fantasy landscape, trending on artstation.", lines=1),

         gr.Image(value=sample_img2img, source="upload", interactive=True, type="pil"),

@@ -677,7 +698,7 @@ img2img_interface = gr.Interface(
     outputs=[

         gr.Gallery(),

         gr.Number(label='Seed'),

-        gr.Textbox(label="Copy-paste generation parameters"),

+        gr.HTML(),

     ],

     title="Stable Diffusion Image-to-Image",

     description="Generate images from images with Stable Diffusion",

@@ -698,7 +719,7 @@ def run_GFPGAN(image, strength):
     if strength < 1.0:

         res = Image.blend(image, res, strength)

 

-    return res

+    return res, 0, ''

 

 

 if GFPGAN is not None:

@@ -710,6 +731,8 @@ if GFPGAN is not None:
         ],

         outputs=[

             gr.Image(label="Result"),

+            gr.Number(label='Seed', visible=False),

+            gr.HTML(),

         ],

         title="GFPGAN",

         description="Fix faces on images",

@@ -719,7 +742,10 @@ if GFPGAN is not None:
 demo = gr.TabbedInterface(

     interface_list=[x[0] for x in interfaces],

     tab_names=[x[1] for x in interfaces],

-    css=("" if opt.no_progressbar_hiding else css_hide_progressbar)

+    css=("" if opt.no_progressbar_hiding else css_hide_progressbar) + """

+.output-html p {margin: 0 0.5em;}

+.performance { font-size: 0.85em; color: #444; }

+"""

 )

 

 demo.launch()