get each image during generating

get each image during generating

fooocus_version.py

@@ -1 +1 @@
-version = '2.1.749'
+version = '2.1.750'

modules/async_worker.py

@@ -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
 
 

update_log.md

@@ -1,3 +1,7 @@
+# 2.1.750
+
+* New UI: now you can get each image during generating.
+
 # 2.1.743
 
 * Improved GPT2 by removing some tokens that may corrupt styles.

webui.py

@@ -22,10 +22,13 @@ from modules.auth import auth_enabled, check_auth
 
 
 def generate_clicked(*args):
+    # outputs=[progress_html, progress_window, progress_gallery, gallery]
+
     execution_start_time = time.perf_counter()
 
     yield gr.update(visible=True, value=modules.html.make_progress_html(1, 'Initializing ...')), \
         gr.update(visible=True, value=None), \
+        gr.update(visible=False, value=None), \
         gr.update(visible=False)
 
     worker.buffer.append(list(args))
@@ -39,9 +42,16 @@ def generate_clicked(*args):
                 percentage, title, image = product
                 yield gr.update(visible=True, value=modules.html.make_progress_html(percentage, title)), \
                     gr.update(visible=True, value=image) if image is not None else gr.update(), \
+                    gr.update(), \
                     gr.update(visible=False)
             if flag == 'results':
+                yield gr.update(visible=True), \
+                    gr.update(visible=True), \
+                    gr.update(visible=True, value=product), \
+                    gr.update(visible=False)
+            if flag == 'finish':
                 yield gr.update(visible=False), \
+                    gr.update(visible=False), \
                     gr.update(visible=False), \
                     gr.update(visible=True, value=product)
                 finished = True
@@ -60,7 +70,9 @@ shared.gradio_root = gr.Blocks(
 with shared.gradio_root:
     with gr.Row():
         with gr.Column(scale=2):
-            progress_window = grh.Image(label='Preview', show_label=True, height=640, visible=False)
+            with gr.Row():
+                progress_window = grh.Image(label='Preview', show_label=True, height=640, visible=False)
+                progress_gallery = gr.Gallery(label='Finished Images', show_label=True, object_fit='contain', height=640, visible=False)
             progress_html = gr.HTML(value=modules.html.make_progress_html(32, 'Progress 32%'), visible=False, elem_id='progress-bar', elem_classes='progress-bar')
             gallery = gr.Gallery(label='Gallery', show_label=False, object_fit='contain', height=745, visible=True, elem_classes='resizable_area')
             with gr.Row(elem_classes='type_row'):
@@ -356,7 +368,7 @@ with shared.gradio_root:
         generate_button.click(lambda: (gr.update(visible=True, interactive=True), gr.update(visible=True, interactive=True), gr.update(visible=False), []), outputs=[stop_button, skip_button, generate_button, gallery]) \
             .then(fn=refresh_seed, inputs=[seed_random, image_seed], outputs=image_seed) \
             .then(advanced_parameters.set_all_advanced_parameters, inputs=adps) \
-            .then(fn=generate_clicked, inputs=ctrls, outputs=[progress_html, progress_window, gallery]) \
+            .then(fn=generate_clicked, inputs=ctrls, outputs=[progress_html, progress_window, progress_gallery, gallery]) \
             .then(lambda: (gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)), outputs=[generate_button, stop_button, skip_button]) \
             .then(fn=None, _js='playNotification')