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get each image during generating

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get each image during generating
This commit is contained in:
lllyasviel
2023-10-26 17:17:05 -07:00
parent f6eee62520
commit 4607316c2f
4 changed files with 44 additions and 14 deletions
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modules/async_worker.py
+25 -11
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@@ -3,10 +3,11 @@ import threading
buffer = []
outputs = []
global_results = []
def worker():
global buffer, outputs
global buffer, outputs, global_results
import traceback
import numpy as np
@@ -47,6 +48,20 @@ def worker():
print(f'[Fooocus] {text}')
outputs.append(['preview', (number, text, None)])
def yield_result(imgs, do_not_show_finished_images=False):
global global_results
if not isinstance(imgs, list):
imgs = [imgs]
global_results = global_results + imgs
if do_not_show_finished_images:
return
outputs.append(['results', global_results])
return
@torch.no_grad()
@torch.inference_mode()
def handler(args):
@@ -356,7 +371,7 @@ def worker():
if direct_return:
d = [('Upscale (Fast)', '2x')]
log(uov_input_image, d, single_line_number=1)
outputs.append(['results', [uov_input_image]])
yield_result(uov_input_image, do_not_show_finished_images=True)
return
tiled = True
@@ -408,7 +423,7 @@ def worker():
pipeline.final_unet.model.diffusion_model.in_inpaint = True
if advanced_parameters.debugging_cn_preprocessor:
outputs.append(['results', inpaint_worker.current_task.visualize_mask_processing()])
yield_result(inpaint_worker.current_task.visualize_mask_processing(), do_not_show_finished_images=True)
return
progressbar(13, 'VAE Inpaint encoding ...')
@@ -454,7 +469,7 @@ def worker():
cn_img = HWC3(cn_img)
task[0] = core.numpy_to_pytorch(cn_img)
if advanced_parameters.debugging_cn_preprocessor:
outputs.append(['results', [cn_img]])
yield_result(cn_img, do_not_show_finished_images=True)
return
for task in cn_tasks[flags.cn_cpds]:
cn_img, cn_stop, cn_weight = task
@@ -463,7 +478,7 @@ def worker():
cn_img = HWC3(cn_img)
task[0] = core.numpy_to_pytorch(cn_img)
if advanced_parameters.debugging_cn_preprocessor:
outputs.append(['results', [cn_img]])
yield_result(cn_img, do_not_show_finished_images=True)
return
for task in cn_tasks[flags.cn_ip]:
cn_img, cn_stop, cn_weight = task
@@ -474,7 +489,7 @@ def worker():
task[0] = ip_adapter.preprocess(cn_img)
if advanced_parameters.debugging_cn_preprocessor:
outputs.append(['results', [cn_img]])
yield_result(cn_img, do_not_show_finished_images=True)
return
if len(cn_tasks[flags.cn_ip]) > 0:
@@ -490,7 +505,6 @@ def worker():
advanced_parameters.freeu_s2
)
results = []
all_steps = steps * image_number
preparation_time = time.perf_counter() - execution_start_time
@@ -566,7 +580,7 @@ def worker():
d.append((f'LoRA [{n}] weight', w))
log(x, d, single_line_number=3)
results += imgs
yield_result(imgs, do_not_show_finished_images=len(tasks) == 1)
except fcbh.model_management.InterruptProcessingException as e:
if shared.last_stop == 'skip':
print('User skipped')
@@ -578,8 +592,6 @@ def worker():
execution_time = time.perf_counter() - execution_start_time
print(f'Generating and saving time: {execution_time:.2f} seconds')
outputs.append(['results', results])
pipeline.prepare_text_encoder(async_call=True)
return
@@ -591,7 +603,9 @@ def worker():
handler(task)
except:
traceback.print_exc()
outputs.append(['results', []])
if len(buffer) == 0:
outputs.append(['finish', global_results])
global_results = []
pass