Merge branch 'portrai' into portrai-macos-experimental

.gitignore

@@ -6,14 +6,14 @@ __pycache__
 /SwinIR/*
 /repositories
 /venv
+/venv-torch-nightly
 /tmp
 /model.ckpt
 /models/**/*
 /GFPGANv1.3.pth
 /gfpgan/weights/*.pth
 /ui-config.json
 /outputs
-/config.json
 /log
 /webui.settings.bat
 /embeddings

config.json

@@ -0,0 +1,158 @@
+{
+    "samples_save": true,
+    "samples_format": "png",
+    "samples_filename_pattern": "",
+    "save_images_add_number": true,
+    "grid_save": true,
+    "grid_format": "png",
+    "grid_extended_filename": false,
+    "grid_only_if_multiple": true,
+    "grid_prevent_empty_spots": false,
+    "n_rows": -1,
+    "enable_pnginfo": false,
+    "save_txt": false,
+    "save_images_before_face_restoration": false,
+    "save_images_before_highres_fix": false,
+    "save_images_before_color_correction": false,
+    "save_mask": false,
+    "save_mask_composite": false,
+    "jpeg_quality": 80,
+    "webp_lossless": false,
+    "export_for_4chan": true,
+    "img_downscale_threshold": 4.0,
+    "target_side_length": 4000,
+    "img_max_size_mp": 200,
+    "use_original_name_batch": true,
+    "use_upscaler_name_as_suffix": false,
+    "save_selected_only": true,
+    "do_not_add_watermark": false,
+    "temp_dir": "",
+    "clean_temp_dir_at_start": false,
+    "outdir_samples": "",
+    "outdir_txt2img_samples": "outputs/txt2img-images",
+    "outdir_img2img_samples": "outputs/img2img-images",
+    "outdir_extras_samples": "outputs/extras-images",
+    "outdir_grids": "",
+    "outdir_txt2img_grids": "outputs/txt2img-grids",
+    "outdir_img2img_grids": "outputs/img2img-grids",
+    "outdir_save": "log/images",
+    "save_to_dirs": true,
+    "grid_save_to_dirs": true,
+    "use_save_to_dirs_for_ui": false,
+    "directories_filename_pattern": "[date]",
+    "directories_max_prompt_words": 8,
+    "ESRGAN_tile": 192,
+    "ESRGAN_tile_overlap": 8,
+    "realesrgan_enabled_models": [
+        "R-ESRGAN 4x+",
+        "R-ESRGAN 4x+ Anime6B"
+    ],
+    "upscaler_for_img2img": null,
+    "face_restoration_model": "CodeFormer",
+    "code_former_weight": 0.5,
+    "face_restoration_unload": false,
+    "show_warnings": false,
+    "memmon_poll_rate": 8,
+    "samples_log_stdout": false,
+    "multiple_tqdm": true,
+    "print_hypernet_extra": false,
+    "unload_models_when_training": false,
+    "pin_memory": false,
+    "save_optimizer_state": false,
+    "save_training_settings_to_txt": true,
+    "dataset_filename_word_regex": "",
+    "dataset_filename_join_string": " ",
+    "training_image_repeats_per_epoch": 1,
+    "training_write_csv_every": 500,
+    "training_xattention_optimizations": false,
+    "training_enable_tensorboard": false,
+    "training_tensorboard_save_images": false,
+    "training_tensorboard_flush_every": 120,
+    "sd_model_checkpoint": "deliberate_v2.safetensors [9aba26abdf]",
+    "sd_checkpoint_cache": 0,
+    "sd_vae_checkpoint_cache": 0,
+    "sd_vae": "Automatic",
+    "sd_vae_as_default": true,
+    "inpainting_mask_weight": 1.0,
+    "initial_noise_multiplier": 1.0,
+    "img2img_color_correction": false,
+    "img2img_fix_steps": false,
+    "img2img_background_color": "#ffffff",
+    "enable_quantization": false,
+    "enable_emphasis": true,
+    "enable_batch_seeds": true,
+    "comma_padding_backtrack": 20,
+    "CLIP_stop_at_last_layers": 1,
+    "upcast_attn": false,
+    "use_old_emphasis_implementation": false,
+    "use_old_karras_scheduler_sigmas": false,
+    "no_dpmpp_sde_batch_determinism": false,
+    "use_old_hires_fix_width_height": false,
+    "interrogate_keep_models_in_memory": false,
+    "interrogate_return_ranks": false,
+    "interrogate_clip_num_beams": 1,
+    "interrogate_clip_min_length": 24,
+    "interrogate_clip_max_length": 48,
+    "interrogate_clip_dict_limit": 1500,
+    "interrogate_clip_skip_categories": [],
+    "interrogate_deepbooru_score_threshold": 0.5,
+    "deepbooru_sort_alpha": true,
+    "deepbooru_use_spaces": false,
+    "deepbooru_escape": true,
+    "deepbooru_filter_tags": "",
+    "extra_networks_default_view": "cards",
+    "extra_networks_default_multiplier": 1.0,
+    "extra_networks_card_width": 0,
+    "extra_networks_card_height": 0,
+    "extra_networks_add_text_separator": " ",
+    "sd_hypernetwork": "None",
+    "return_grid": true,
+    "return_mask": false,
+    "return_mask_composite": false,
+    "do_not_show_images": false,
+    "add_model_hash_to_info": true,
+    "add_model_name_to_info": true,
+    "disable_weights_auto_swap": true,
+    "send_seed": true,
+    "send_size": true,
+    "font": "",
+    "js_modal_lightbox": true,
+    "js_modal_lightbox_initially_zoomed": true,
+    "show_progress_in_title": true,
+    "samplers_in_dropdown": true,
+    "dimensions_and_batch_together": true,
+    "keyedit_precision_attention": 0.1,
+    "keyedit_precision_extra": 0.05,
+    "quicksettings": "sd_model_checkpoint",
+    "hidden_tabs": [],
+    "ui_reorder": "inpaint, sampler, checkboxes, hires_fix, dimensions, cfg, seed, batch, override_settings, scripts",
+    "ui_extra_networks_tab_reorder": "",
+    "localization": "None",
+    "show_progressbar": true,
+    "live_previews_enable": true,
+    "show_progress_grid": true,
+    "show_progress_every_n_steps": 4,
+    "show_progress_type": "Approx NN",
+    "live_preview_content": "Prompt",
+    "live_preview_refresh_period": 1000,
+    "hide_samplers": [],
+    "eta_ddim": 0.0,
+    "eta_ancestral": 1.0,
+    "ddim_discretize": "uniform",
+    "s_churn": 0.0,
+    "s_tmin": 0.0,
+    "s_noise": 1.0,
+    "eta_noise_seed_delta": 0,
+    "always_discard_next_to_last_sigma": false,
+    "uni_pc_variant": "bh1",
+    "uni_pc_skip_type": "time_uniform",
+    "uni_pc_order": 3,
+    "uni_pc_lower_order_final": true,
+    "postprocessing_enable_in_main_ui": [],
+    "postprocessing_operation_order": [],
+    "upscaling_max_images_in_cache": 5,
+    "disabled_extensions": [],
+    "disable_all_extensions": "none",
+    "sd_checkpoint_hash": "9aba26abdfcd46073e0a1d42027a3a3bcc969f562d58a03637bf0a0ded6586c9",
+    "restore_config_state_file": ""
+}

modules/api/api.py

@@ -34,6 +34,11 @@
 import piexif.helper
 from contextlib import closing
 
+from modules.api import jobs
+
+current_task = None
+pending_tasks = {}
+finished_tasks = []
 
 def script_name_to_index(name, scripts):
     try:
@@ -215,6 +220,10 @@ def __init__(self, app: FastAPI, queue_lock: Lock):
         self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ExtrasBatchImagesResponse)
         self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=models.PNGInfoResponse)
         self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=models.ProgressResponse)
+
+        self.add_api_route("/sdapi/v1/new-progress", self.newprogressapi, methods=["POST"], response_model=models.NewProgressResponse)
+        self.add_api_route("/sdapi/v1/cancel", self.cancel, methods=["POST"])
+
         self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"])
@@ -338,6 +347,7 @@ def init_script_args(self, request, default_script_args, selectable_scripts, sel
         return script_args
 
     def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
+        global current_task
         script_runner = scripts.scripts_txt2img
         if not script_runner.scripts:
             script_runner.initialize_scripts(False)
@@ -363,7 +373,9 @@ def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
 
         send_images = args.pop('send_images', True)
         args.pop('save_images', None)
+        args.pop('generation_id', None)
 
+        jobs.add_task_to_queue(txt2imgreq.generation_id)
         with self.queue_lock:
             with closing(StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)) as p:
                 p.is_api = True
@@ -373,13 +385,17 @@ def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
 
                 try:
                     shared.state.begin(job="scripts_txt2img")
+                    jobs.start_task(txt2imgreq.generation_id)
                     if selectable_scripts is not None:
                         p.script_args = script_args
                         processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
                     else:
                         p.script_args = tuple(script_args) # Need to pass args as tuple here
                         processed = process_images(p)
                 finally:
+                    jobs.record_results(txt2imgreq.generation_id, processed)
+                    jobs.finish_task(txt2imgreq.generation_id)
+
                     shared.state.end()
                     shared.total_tqdm.clear()
 
@@ -515,6 +531,49 @@ def progressapi(self, req: models.ProgressRequest = Depends()):
 
         return models.ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo)
 
+    def newprogressapi(self, req: models.NewProgressRequest):
+        active = req.id_task == jobs.current_task
+        queued = req.id_task in jobs.pending_tasks
+        completed = req.id_task in jobs.finished_tasks
+
+        if not active:
+            position_in_queue = sum(1 for job_id, timestamp in jobs.pending_tasks.items() if timestamp < jobs.pending_tasks[req.id_task]) + 1
+            return models.NewProgressResponse(active=active, queued=queued, completed=completed, eta=position_in_queue, textinfo="In queue..." if queued else "Waiting...")
+
+        progress = 0
+
+        job_count, job_no = shared.state.job_count, shared.state.job_no
+        sampling_steps, sampling_step = shared.state.sampling_steps, shared.state.sampling_step
+
+        if job_count > 0:
+            progress += job_no / job_count
+        if sampling_steps > 0 and job_count > 0:
+            progress += 1 / job_count * sampling_step / sampling_steps
+
+        progress = min(progress, 1)
+
+        elapsed_since_start = time.time() - shared.state.time_start
+        predicted_duration = elapsed_since_start / progress if progress > 0 else None
+        eta = predicted_duration - elapsed_since_start if predicted_duration is not None else None
+
+        shared.state.set_current_image()
+        image = shared.state.current_image
+
+        if image is not None:
+            buffered = io.BytesIO()
+            image.save(buffered, format="png")
+            live_preview = base64.b64encode(buffered.getvalue()).decode("ascii")
+        else:
+            live_preview = None
+
+        return models.NewProgressResponse(active=active, queued=queued, completed=completed, progress=progress, eta=eta, live_preview=live_preview, textinfo=shared.state.textinfo)
+
+    def cancel(self, req: models.CancelRequest):
+        if req.id_task == jobs.current_task:
+            shared.state.interrupt()
+
+        jobs.cancel_task(req.id_task)
+
     def interrogateapi(self, interrogatereq: models.InterrogateRequest):
         image_b64 = interrogatereq.image
         if image_b64 is None:

modules/api/jobs.py

@@ -0,0 +1,40 @@
+import time
+
+current_task = None
+pending_tasks = {}
+finished_tasks = []
+recorded_results = []
+recorded_results_limit = 2
+
+def start_task(id_task):
+    global current_task
+
+    current_task = id_task
+    pending_tasks.pop(id_task, None)
+
+def finish_task(id_task):
+    global current_task
+
+    if current_task == id_task:
+        current_task = None
+
+    finished_tasks.append(id_task)
+    if len(finished_tasks) > 16:
+        finished_tasks.pop(0)
+
+def cancel_task(id_task):
+    global current_task
+
+    if current_task == id_task:
+        current_task = None
+
+    pending_tasks.pop(id_task, None)
+
+def record_results(id_task, res):
+    recorded_results.append((id_task, res))
+    if len(recorded_results) > recorded_results_limit:
+        recorded_results.pop(0)
+
+
+def add_task_to_queue(id_job):
+    pending_tasks[id_job] = time.time()

modules/api/models.py

@@ -107,6 +107,7 @@ def generate_model(self):
         {"key": "send_images", "type": bool, "default": True},
         {"key": "save_images", "type": bool, "default": False},
         {"key": "alwayson_scripts", "type": dict, "default": {}},
+        {"key": "generation_id", "type": str, "default": None},
     ]
 ).generate_model()
 
@@ -182,13 +183,28 @@ class PNGInfoResponse(BaseModel):
 class ProgressRequest(BaseModel):
     skip_current_image: bool = Field(default=False, title="Skip current image", description="Skip current image serialization")
 
+class NewProgressRequest(BaseModel):
+    id_task: str = Field(default=None, title="Task ID", description="id of the task to get progress for")
+
+class CancelRequest(BaseModel):
+    id_task: str = Field(default=None, title="Task ID", description="id of the task to cancel")
+
 class ProgressResponse(BaseModel):
     progress: float = Field(title="Progress", description="The progress with a range of 0 to 1")
     eta_relative: float = Field(title="ETA in secs")
     state: dict = Field(title="State", description="The current state snapshot")
     current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
     textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
 
+class NewProgressResponse(BaseModel):
+    active: bool = Field(title="Whether the task is being worked on right now")
+    queued: bool = Field(title="Whether the task is in queue")
+    completed: bool = Field(title="Whether the task has already finished")
+    progress: float = Field(default=None, title="Progress", description="The progress with a range of 0 to 1")
+    eta: float = Field(default=None, title="ETA in secs")
+    live_preview: str = Field(default=None, title="Live preview image", description="Current live preview; a data: uri")
+    textinfo: str = Field(default=None, title="Info text", description="Info text used by WebUI.")
+
 class InterrogateRequest(BaseModel):
     image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
     model: str = Field(default="clip", title="Model", description="The interrogate model used.")

webui-user.bat

@@ -3,6 +3,6 @@
 set PYTHON=
 set GIT=
 set VENV_DIR=
-set COMMANDLINE_ARGS=
+set COMMANDLINE_ARGS=--listen --nowebui --port=7860 --cors-allow-origins=*
 
 call webui.bat