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Fix to XY_Grid script console progress bar and other progress bar improvements (#890)

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Fix to XY_Grid script console progress bar and other progress bar improvements #890
This commit is contained in:
RnDMonkey
2022-09-23 22:09:59 -07:00
committed by GitHub
parent 7aec029423
commit ed8b8b3b8c
3 changed files with 36 additions and 5 deletions
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32
scripts/xy_grid.py
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@@ -102,7 +102,7 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend):
for iy, y in enumerate(ys):
for ix, x in enumerate(xs):
state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
state.job = f"Image {ix + iy * len(xs) + 1} out of {state.job_count}"
processed = cell(x, y)
if first_pocessed is None:
@@ -141,10 +141,11 @@ class Script(scripts.Script):
y_values = gr.Textbox(label="Y values", visible=False, lines=1)
draw_legend = gr.Checkbox(label='Draw legend', value=True)
return [x_type, x_values, y_type, y_values, draw_legend]
fixed_seeds = gr.Checkbox(label='Resolve random seeds before plotting (only applies when plotting "-1" seed values for X or Y axis)', value=False)
def run(self, p, x_type, x_values, y_type, y_values, draw_legend):
return [x_type, x_values, y_type, y_values, draw_legend, fixed_seeds]
def run(self, p, x_type, x_values, y_type, y_values, draw_legend, fixed_seeds):
modules.processing.fix_seed(p)
p.batch_size = 1
@@ -207,6 +208,29 @@ class Script(scripts.Script):
y_opt = axis_options[y_type]
ys = process_axis(y_opt, y_values)
def fix_axis_seeds(axis_opt, axis_list):
if axis_opt.label == 'Seed':
return [int(random.randrange(4294967294)) if val is None or val == '' or val == -1 else val for val in axis_list]
else:
return axis_list
if fixed_seeds == True:
xs = fix_axis_seeds(x_opt, xs)
ys = fix_axis_seeds(y_opt, ys)
if x_opt.label == 'Steps':
total_steps = sum(xs) * len(ys)
elif y_opt.label == 'Steps':
total_steps = sum(ys) * len(xs)
else:
total_steps = p.steps * len(xs) * len(ys)
if p.n_iter > 1:
print(f"Number of seeds/images per prompt is {p.n_iter}.")
print(f"X/Y plot will create {len(xs) * len(ys) * p.n_iter} images on a {len(xs)} x {len(ys)} grid. (Total steps to process: {total_steps * p.n_iter})")
shared.total_tqdm.updateTotal(total_steps * p.n_iter)
def cell(x, y):
pc = copy(p)
x_opt.apply(pc, x, xs)