update

cli/generate.py

@@ -342,15 +342,17 @@ async def main():
             break
         stats.images += len(data.image)
         t1 = time.perf_counter()
-        avg[scheduler] = (t1 - t0) / len(data.image)
+        if len(data.image) > 0:
+            avg[scheduler] = (t1 - t0) / len(data.image)
         stats.generate += t1 - t0
         _image = grid(data)
         data = await upscale(data)
         t2 = time.perf_counter()
         stats.upscale += t2 - t1
         stats.wall += t2 - t0
-        its = sd.generate.steps / ((t1 - t0) / len(data.image))
-        log.info({ 'time' : { 'wall': round(t1 - t0), 'average': round((t1 - t0) / len(data.image)), 'upscale': round(t2 - t1), 'its': round(its, 2) } })
+        its = sd.generate.steps / ((t1 - t0) / len(data.image)) if len(data.image) > 0 else 0
+        avg_time = round((t1 - t0) / len(data.image)) if len(data.image) > 0 else 0
+        log.info({ 'time' : { 'wall': round(t1 - t0), 'average': avg_time, 'upscale': round(t2 - t1), 'its': round(its, 2) } })
         log.info({ 'generated': stats.images, 'max': params.max, 'progress': round(100 * stats.images / params.max, 1) })
         if params.max != 0 and stats.images >= params.max:
             break

modules/api/api.py

@@ -192,8 +192,8 @@ class Api:
 
         populate = txt2imgreq.copy(update={ # Override __init__ params
             "sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index),
-            "do_not_save_samples": True,
-            "do_not_save_grid": True
+            "do_not_save_samples": True if not 'do_not_save_samples' in vars(txt2imgreq) else txt2imgreq.do_not_save_samples,
+            "do_not_save_grid": True if not 'do_not_save_grid' in vars(txt2imgreq) else txt2imgreq.do_not_save_grid,
             }
         )
         if populate.sampler_name:
@@ -202,6 +202,9 @@ class Api:
         args = vars(populate)
         args.pop('script_name', None)
 
+        send_images = True if not 'do_not_send_images' in args else not args['do_not_send_images']
+        args.pop('do_not_send_images', None)
+
         with self.queue_lock:
             p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
 
@@ -215,7 +218,7 @@ class Api:
                 processed = process_images(p)
             shared.state.end()
 
-        b64images = list(map(encode_pil_to_base64, processed.images))
+        b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
 
         return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
 
@@ -232,8 +235,8 @@ class Api:
 
         populate = img2imgreq.copy(update={ # Override __init__ params
             "sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
-            "do_not_save_samples": True,
-            "do_not_save_grid": True,
+            "do_not_save_samples": True if not 'do_not_save_samples' in img2imgreq else img2imgreq.do_not_save_samples,
+            "do_not_save_grid": True if not 'do_not_save_grid' in img2imgreq else img2imgreq.do_not_save_grid,
             "mask": mask
             }
         )
@@ -244,6 +247,9 @@ class Api:
         args.pop('include_init_images', None)  # this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine.
         args.pop('script_name', None)
 
+        send_images = True if not 'do_not_send_images' in args else not args['do_not_send_images']
+        args.pop('do_not_send_images', None)
+
         with self.queue_lock:
             p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
             p.init_images = [decode_base64_to_image(x) for x in init_images]
@@ -258,7 +264,7 @@ class Api:
                 processed = process_images(p)
             shared.state.end()
 
-        b64images = list(map(encode_pil_to_base64, processed.images))
+        b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
 
         if not img2imgreq.include_init_images:
             img2imgreq.init_images = None

modules/api/models.py

@@ -14,8 +14,8 @@ API_NOT_ALLOWED = [
     "outpath_samples",
     "outpath_grids",
     "sampler_index",
-    "do_not_save_samples",
-    "do_not_save_grid",
+    # "do_not_save_samples",
+    # "do_not_save_grid",
     "extra_generation_params",
     "overlay_images",
     "do_not_reload_embeddings",
@@ -100,13 +100,27 @@ class PydanticModelGenerator:
 StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
     "StableDiffusionProcessingTxt2Img",
     StableDiffusionProcessingTxt2Img,
-    [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}]
+    [
+        {"key": "sampler_index", "type": str, "default": "Euler"},
+        {"key": "script_name", "type": str, "default": None},
+        {"key": "script_args", "type": list, "default": []},
+        {"key": "do_not_send_images", "type": bool, "default": False}
+    ]
 ).generate_model()
 
 StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
     "StableDiffusionProcessingImg2Img",
     StableDiffusionProcessingImg2Img,
-    [{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "init_images", "type": list, "default": None}, {"key": "denoising_strength", "type": float, "default": 0.75}, {"key": "mask", "type": str, "default": None}, {"key": "include_init_images", "type": bool, "default": False, "exclude" : True}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}]
+    [
+        {"key": "sampler_index", "type": str, "default": "Euler"},
+        {"key": "init_images", "type": list, "default": None},
+        {"key": "denoising_strength", "type": float, "default": 0.75},
+        {"key": "mask", "type": str, "default": None},
+        {"key": "include_init_images", "type": bool, "default": False, "exclude" : True},
+        {"key": "script_name", "type": str, "default": None},
+        {"key": "script_args", "type": list, "default": []},
+        {"key": "do_not_send_images", "type": bool, "default": False}
+    ]
 ).generate_model()
 
 class TextToImageResponse(BaseModel):

modules/images.py

@@ -489,6 +489,9 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
     """
     namegen = FilenameGenerator(p, seed, prompt, image)
 
+    if path is None: # set default path to avoid errors when functions are triggered manually or via api and param is not set
+        path = opts.outdir_save
+
     if save_to_dirs is None:
         save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt)