feat: add checkbox, config and handling for saving only the final enhanced image (#61)

args_manager.py

@@ -17,7 +17,7 @@ args_parser.parser.add_argument("--disable-offload-from-vram", action="store_tru
 
 args_parser.parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
 args_parser.parser.add_argument("--disable-image-log", action='store_true',
-                                help="Prevent writing images and logs to hard drive.")
+                                help="Prevent writing images and logs to the outputs folder.")
 
 args_parser.parser.add_argument("--disable-analytics", action='store_true',
                                 help="Disables analytics for Gradio.")

language/en.json

@@ -69,6 +69,9 @@
     "Read wildcards in order": "Read wildcards in order",
     "Black Out NSFW": "Black Out NSFW",
     "Use black image if NSFW is detected.": "Use black image if NSFW is detected.",
+    "Save only final enhanced image": "Save only final enhanced image",
+    "Save Metadata to Images": "Save Metadata to Images",
+    "Adds parameters to generated images allowing manual regeneration.": "Adds parameters to generated images allowing manual regeneration.",
     "\ud83d\udcda History Log": "\uD83D\uDCDA History Log",
     "Image Style": "Image Style",
     "Fooocus V2": "Fooocus V2",

modules/async_worker.py

@@ -96,6 +96,7 @@ class AsyncTask:
         self.inpaint_advanced_masking_checkbox = args.pop()
         self.invert_mask_checkbox = args.pop()
         self.inpaint_erode_or_dilate = args.pop()
+        self.save_final_enhanced_image_only = args.pop() if not args_manager.args.disable_image_log else False
         self.save_metadata_to_images = args.pop() if not args_manager.args.disable_metadata else False
         self.metadata_scheme = MetadataScheme(
             args.pop()) if not args_manager.args.disable_metadata else MetadataScheme.FOOOCUS
@@ -278,7 +279,7 @@ def worker():
     def process_task(all_steps, async_task, callback, controlnet_canny_path, controlnet_cpds_path, current_task_id,
                      denoising_strength, final_scheduler_name, goals, initial_latent, steps, switch, positive_cond,
                      negative_cond, task, loras, tiled, use_expansion, width, height, base_progress, preparation_steps,
-                     total_count, show_intermediate_results):
+                     total_count, show_intermediate_results, persist_image=True):
         if async_task.last_stop is not False:
             ldm_patched.modules.model_management.interrupt_current_processing()
         if 'cn' in goals:
@@ -315,9 +316,8 @@ def worker():
         if modules.config.default_black_out_nsfw or async_task.black_out_nsfw:
             progressbar(async_task, current_progress, 'Checking for NSFW content ...')
             imgs = default_censor(imgs)
-        progressbar(async_task, current_progress,
+        progressbar(async_task, current_progress, f'Saving image {current_task_id + 1}/{total_count} to system ...')
-                    f'Saving image {current_task_id + 1}/{total_count} to system ...')
+        img_paths = save_and_log(async_task, height, imgs, task, use_expansion, width, loras, persist_image)
-        img_paths = save_and_log(async_task, height, imgs, task, use_expansion, width, loras)
         yield_result(async_task, img_paths, current_progress, async_task.black_out_nsfw, False,
                      do_not_show_finished_images=not show_intermediate_results or async_task.disable_intermediate_results)
 
@@ -333,7 +333,7 @@ def worker():
             async_task.adaptive_cfg
         )
 
-    def save_and_log(async_task, height, imgs, task, use_expansion, width, loras) -> list:
+    def save_and_log(async_task, height, imgs, task, use_expansion, width, loras, persist_image=True) -> list:
         img_paths = []
         for x in imgs:
             d = [('Prompt', 'prompt', task['log_positive_prompt']),
@@ -388,7 +388,7 @@ def worker():
             d.append(('Metadata Scheme', 'metadata_scheme',
                       async_task.metadata_scheme.value if async_task.save_metadata_to_images else async_task.save_metadata_to_images))
             d.append(('Version', 'version', 'Fooocus v' + fooocus_version.version))
-            img_paths.append(log(x, d, metadata_parser, async_task.output_format, task))
+            img_paths.append(log(x, d, metadata_parser, async_task.output_format, task, persist_image))
 
         return img_paths
 
@@ -963,7 +963,7 @@ def worker():
                         inpaint_engine, inpaint_respective_field, inpaint_strength,
                         prompt, negative_prompt, final_scheduler_name, goals, height, img, mask,
                         preparation_steps, steps, switch, tiled, total_count, use_expansion, use_style,
-                        use_synthetic_refiner, width, show_intermediate_results=True):
+                        use_synthetic_refiner, width, show_intermediate_results=True, persist_image=True):
         base_model_additional_loras = []
         inpaint_head_model_path = None
         inpaint_parameterized = inpaint_engine != 'None'  # inpaint_engine = None, improve detail
@@ -985,7 +985,7 @@ def worker():
                     progressbar(async_task, current_progress, 'Checking for NSFW content ...')
                     img = default_censor(img)
                 progressbar(async_task, current_progress, f'Saving image {current_task_id + 1}/{total_count} to system ...')
-                uov_image_path = log(img, d, output_format=async_task.output_format)
+                uov_image_path = log(img, d, output_format=async_task.output_format, persist_image=persist_image)
                 yield_result(async_task, uov_image_path, current_progress, async_task.black_out_nsfw, False,
                              do_not_show_finished_images=not show_intermediate_results or async_task.disable_intermediate_results)
                 return current_progress, img, prompt, negative_prompt
@@ -1019,7 +1019,8 @@ def worker():
                                                          final_scheduler_name, goals, initial_latent, steps, switch,
                                                          task_enhance['c'], task_enhance['uc'], task_enhance, loras,
                                                          tiled, use_expansion, width, height, current_progress,
-                                                         preparation_steps, total_count, show_intermediate_results)
+                                                         preparation_steps, total_count, show_intermediate_results,
+                                                         persist_image)
 
         del task_enhance['c'], task_enhance['uc']  # Save memory
         return current_progress, imgs[0], prompt, negative_prompt
@@ -1027,7 +1028,7 @@ def worker():
     def enhance_upscale(all_steps, async_task, base_progress, callback, controlnet_canny_path, controlnet_cpds_path,
                         current_task_id, denoising_strength, done_steps_inpainting, done_steps_upscaling, enhance_steps,
                         prompt, negative_prompt, final_scheduler_name, height, img, preparation_steps, switch, tiled,
-                        total_count, use_expansion, use_style, use_synthetic_refiner, width):
+                        total_count, use_expansion, use_style, use_synthetic_refiner, width, persist_image=True):
         # reset inpaint worker to prevent tensor size issues and not mix upscale and inpainting
         inpaint_worker.current_task = None
 
@@ -1045,7 +1046,7 @@ def worker():
                     controlnet_cpds_path, current_progress, current_task_id, denoising_strength, False,
                     'None', 0.0, 0.0, prompt, negative_prompt, final_scheduler_name,
                     goals_enhance, height, img, None, preparation_steps, steps, switch, tiled, total_count,
-                    use_expansion, use_style, use_synthetic_refiner, width)
+                    use_expansion, use_style, use_synthetic_refiner, width, persist_image=persist_image)
 
             except ldm_patched.modules.model_management.InterruptProcessingException:
                 if async_task.last_stop == 'skip':
@@ -1168,6 +1169,8 @@ def worker():
             current_progress += 1
             progressbar(async_task, current_progress, 'Image processing ...')
 
+        should_enhance = async_task.enhance_checkbox and (async_task.enhance_uov_method != flags.disabled.casefold() or len(async_task.enhance_ctrls) > 0)
+
         if 'vary' in goals:
             async_task.uov_input_image, denoising_strength, initial_latent, width, height, current_progress = apply_vary(
                 async_task, async_task.uov_method, denoising_strength, async_task.uov_input_image, switch,
@@ -1273,8 +1276,8 @@ def worker():
                 int(current_progress + async_task.callback_steps),
                 f'Sampling step {step + 1}/{total_steps}, image {current_task_id + 1}/{total_count} ...', y)])
 
-        should_enhance = async_task.enhance_checkbox and (async_task.enhance_uov_method != flags.disabled.casefold() or len(async_task.enhance_ctrls) > 0)
         show_intermediate_results = len(tasks) > 1 or should_enhance
+        persist_image = not should_enhance or not async_task.save_final_enhanced_image_only
 
         for current_task_id, task in enumerate(tasks):
             progressbar(async_task, current_progress, f'Preparing task {current_task_id + 1}/{async_task.image_number} ...')
@@ -1287,7 +1290,8 @@ def worker():
                                                                  initial_latent, async_task.steps, switch, task['c'],
                                                                  task['uc'], task, loras, tiled, use_expansion, width,
                                                                  height, current_progress, preparation_steps,
-                                                                 async_task.image_number, show_intermediate_results)
+                                                                 async_task.image_number, show_intermediate_results,
+                                                                 persist_image)
 
                 current_progress = int(preparation_steps + (100 - preparation_steps) / float(all_steps) * async_task.steps * (current_task_id + 1))
                 images_to_enhance += imgs
@@ -1314,8 +1318,12 @@ def worker():
 
         active_enhance_tabs = len(async_task.enhance_ctrls)
         should_process_enhance_uov = async_task.enhance_uov_method != flags.disabled.casefold()
+        enhance_uov_before = False
+        enhance_uov_after = False
         if should_process_enhance_uov:
             active_enhance_tabs += 1
+            enhance_uov_before = async_task.enhance_uov_processing_order == flags.enhancement_uov_before
+            enhance_uov_after = async_task.enhance_uov_processing_order == flags.enhancement_uov_after
         total_count = len(images_to_enhance) * active_enhance_tabs
 
         base_progress = current_progress
@@ -1330,13 +1338,14 @@ def worker():
             last_enhance_prompt = async_task.prompt
             last_enhance_negative_prompt = async_task.negative_prompt
 
-            if should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_before:
+            if enhance_uov_before:
                 current_task_id += 1
+                persist_image = not async_task.save_final_enhanced_image_only or active_enhance_tabs == 0
                 current_task_id, done_steps_inpainting, done_steps_upscaling, img, exception_result = enhance_upscale(
                     all_steps, async_task, base_progress, callback, controlnet_canny_path, controlnet_cpds_path,
                     current_task_id, denoising_strength, done_steps_inpainting, done_steps_upscaling, enhance_steps,
                     async_task.prompt, async_task.negative_prompt, final_scheduler_name, height, img, preparation_steps,
-                    switch, tiled, total_count, use_expansion, use_style, use_synthetic_refiner, width)
+                    switch, tiled, total_count, use_expansion, use_style, use_synthetic_refiner, width, persist_image)
                 if exception_result == 'continue':
                     continue
                 elif exception_result == 'break':
@@ -1348,6 +1357,8 @@ def worker():
                 current_progress = int(base_progress + (100 - preparation_steps) / float(all_steps) * (done_steps_upscaling + done_steps_inpainting))
                 progressbar(async_task, current_progress, f'Preparing enhancement {current_task_id + 1}/{total_count} ...')
                 enhancement_task_start_time = time.perf_counter()
+                is_last_enhance_for_image = (current_task_id + 1) % active_enhance_tabs == 0 and not enhance_uov_after
+                persist_image = not async_task.save_final_enhanced_image_only or is_last_enhance_for_image
 
                 extras = {}
                 if enhance_mask_model == 'sam':
@@ -1383,8 +1394,7 @@ def worker():
                 print(f'[Enhance] {sam_detection_count} segments detected in boxes')
                 print(f'[Enhance] {sam_detection_on_mask_count} segments applied to mask')
 
-                if enhance_mask_model == 'sam' and (
+                if enhance_mask_model == 'sam' and (dino_detection_count == 0 or not async_task.debugging_dino and sam_detection_on_mask_count == 0):
-                        dino_detection_count == 0 or not async_task.debugging_dino and sam_detection_on_mask_count == 0):
                     print(f'[Enhance] No "{enhance_mask_dino_prompt_text}" detected, skipping')
                     continue
 
@@ -1397,7 +1407,7 @@ def worker():
                         enhance_inpaint_engine, enhance_inpaint_respective_field, enhance_inpaint_strength,
                         enhance_prompt, enhance_negative_prompt, final_scheduler_name, goals_enhance, height, img, mask,
                         preparation_steps, enhance_steps, switch, tiled, total_count, use_expansion, use_style,
-                        use_synthetic_refiner, width)
+                        use_synthetic_refiner, width, persist_image=persist_image)
 
                     if (should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_after
                             and async_task.enhance_uov_prompt_type == flags.enhancement_uov_prompt_type_last_filled):
@@ -1424,14 +1434,16 @@ def worker():
             if exception_result == 'break':
                 break
 
-            if should_process_enhance_uov and async_task.enhance_uov_processing_order == flags.enhancement_uov_after:
+            if enhance_uov_after:
                 current_task_id += 1
+                # last step in enhance, always save
+                persist_image = True
                 current_task_id, done_steps_inpainting, done_steps_upscaling, img, exception_result = enhance_upscale(
                     all_steps, async_task, base_progress, callback, controlnet_canny_path, controlnet_cpds_path,
                     current_task_id, denoising_strength, done_steps_inpainting, done_steps_upscaling, enhance_steps,
                     last_enhance_prompt, last_enhance_negative_prompt, final_scheduler_name, height, img,
                     preparation_steps, switch, tiled, total_count, use_expansion, use_style, use_synthetic_refiner,
-                    width)
+                    width, persist_image)
                 if exception_result == 'continue':
                     continue
                 elif exception_result == 'break':

modules/config.py

@@ -562,6 +562,12 @@ default_black_out_nsfw = get_config_item_or_set_default(
     validator=lambda x: isinstance(x, bool),
     expected_type=bool
 )
+default_save_only_final_enhanced_image = get_config_item_or_set_default(
+    key='default_save_only_final_enhanced_image',
+    default_value=False,
+    validator=lambda x: isinstance(x, bool),
+    expected_type=bool
+)
 default_save_metadata_to_images = get_config_item_or_set_default(
     key='default_save_metadata_to_images',
     default_value=False,

modules/private_logger.py

@@ -21,8 +21,8 @@ def get_current_html_path(output_format=None):
     return html_name
 
 
-def log(img, metadata, metadata_parser: MetadataParser | None = None, output_format=None, task=None) -> str:
+def log(img, metadata, metadata_parser: MetadataParser | None = None, output_format=None, task=None, persist_image=True) -> str:
-    path_outputs = modules.config.temp_path if args_manager.args.disable_image_log else modules.config.path_outputs
+    path_outputs = modules.config.temp_path if args_manager.args.disable_image_log or not persist_image else modules.config.path_outputs
     output_format = output_format if output_format else modules.config.default_output_format
     date_string, local_temp_filename, only_name = generate_temp_filename(folder=path_outputs, extension=output_format)
     os.makedirs(os.path.dirname(local_temp_filename), exist_ok=True)

webui.py

@@ -753,6 +753,10 @@ with shared.gradio_root:
                                               inputs=black_out_nsfw, outputs=disable_preview, queue=False,
                                               show_progress=False)
 
+                        if not args_manager.args.disable_image_log:
+                            save_final_enhanced_image_only = gr.Checkbox(label='Save only final enhanced image',
+                                                                         value=modules.config.default_save_only_final_enhanced_image)
+
                         if not args_manager.args.disable_metadata:
                             save_metadata_to_images = gr.Checkbox(label='Save Metadata to Images', value=modules.config.default_save_metadata_to_images,
                                                                   info='Adds parameters to generated images allowing manual regeneration.')
@@ -992,6 +996,9 @@ with shared.gradio_root:
         ctrls += freeu_ctrls
         ctrls += inpaint_ctrls
 
+        if not args_manager.args.disable_image_log:
+            ctrls += [save_final_enhanced_image_only]
+
         if not args_manager.args.disable_metadata:
             ctrls += [save_metadata_to_images, metadata_scheme]