diff options
| -rw-r--r-- | modules/processing.py | 9 | ||||
| -rw-r--r-- | scripts/prompts_from_file.py | 36 |
2 files changed, 33 insertions, 12 deletions
diff --git a/modules/processing.py b/modules/processing.py index 3a4ff224..6a99d383 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -188,7 +188,11 @@ def fix_seed(p): 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"""
- assert p.prompt is not None
+ if type(p.prompt) == list:
+ assert(len(p.prompt) > 0)
+ else:
+ assert p.prompt is not None
+
devices.torch_gc()
fix_seed(p)
@@ -265,6 +269,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed: seeds = all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
subseeds = all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
+ if (len(prompts) == 0):
+ break
+
#uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt])
#c = p.sd_model.get_learned_conditioning(prompts)
uc = prompt_parser.get_learned_conditioning(len(prompts) * [p.negative_prompt], p.steps)
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index d9b01c81..513d9a1c 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -13,28 +13,42 @@ from modules.shared import opts, cmd_opts, state class Script(scripts.Script):
def title(self):
- return "Prompts from file"
+ return "Prompts from file or textbox"
def ui(self, is_img2img):
+ # This checkbox would look nicer as two tabs, but there are two problems:
+ # 1) There is a bug in Gradio 3.3 that prevents visibility from working on Tabs
+ # 2) Even with Gradio 3.3.1, returning a control (like Tabs) that can't be used as input
+ # causes a AttributeError: 'Tabs' object has no attribute 'preprocess' assert,
+ # due to the way Script assumes all controls returned can be used as inputs.
+ # Therefore, there's no good way to use grouping components right now,
+ # so we will use a checkbox! :)
+ checkbox_txt = gr.Checkbox(label="Show Textbox", value=False)
file = gr.File(label="File with inputs", type='bytes')
-
- return [file]
-
- def run(self, p, data: bytes):
- lines = [x.strip() for x in data.decode('utf8', errors='ignore').split("\n")]
+ prompt_txt = gr.TextArea(label="Prompts")
+ checkbox_txt.change(fn=lambda x: [gr.File.update(visible = not x), gr.TextArea.update(visible = x)], inputs=[checkbox_txt], outputs=[file, prompt_txt])
+ return [checkbox_txt, file, prompt_txt]
+
+ def run(self, p, checkbox_txt, data: bytes, prompt_txt: str):
+ if (checkbox_txt):
+ lines = [x.strip() for x in prompt_txt.splitlines()]
+ else:
+ lines = [x.strip() for x in data.decode('utf8', errors='ignore').split("\n")]
lines = [x for x in lines if len(x) > 0]
- batch_count = math.ceil(len(lines) / p.batch_size)
- print(f"Will process {len(lines) * p.n_iter} images in {batch_count * p.n_iter} batches.")
+ img_count = len(lines) * p.n_iter
+ batch_count = math.ceil(img_count / p.batch_size)
+ loop_count = math.ceil(batch_count / p.n_iter)
+ print(f"Will process {img_count} images in {batch_count} batches.")
p.do_not_save_grid = True
state.job_count = batch_count
images = []
- for batch_no in range(batch_count):
- state.job = f"{batch_no + 1} out of {batch_count * p.n_iter}"
- p.prompt = lines[batch_no*p.batch_size:(batch_no+1)*p.batch_size] * p.n_iter
+ for loop_no in range(loop_count):
+ state.job = f"{loop_no + 1} out of {loop_count}"
+ p.prompt = lines[loop_no*p.batch_size:(loop_no+1)*p.batch_size] * p.n_iter
proc = process_images(p)
images += proc.images
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