api validation

Signed-off-by: Vladimir Mandic <mandic00@live.com>

modules/api/docs.py

@@ -90,7 +90,3 @@ def create_redocs(app: FastAPI):
             redoc_favicon_url='/file=html/favicon.svg',
         )
         return res
-
-"""
-https://github.com/Amoenus/SwaggerDark/blob/master/SwaggerDark.css
-"""

modules/api/helpers.py

@@ -14,7 +14,7 @@ def validate_sampler_name(name):
     return name
 
 
-def decode_base64_to_image(encoding):
+def decode_base64_to_image(encoding, quiet=False):
     if encoding.startswith("data:image/"):
         encoding = encoding.split(";")[1].split(",")[1]
     try:
@@ -22,7 +22,10 @@ def decode_base64_to_image(encoding):
         return image
     except Exception as e:
         shared.log.warning(f'API cannot decode image: {e}')
-        raise HTTPException(status_code=500, detail="Invalid encoded image") from e
+        if not quiet:
+            raise HTTPException(status_code=500, detail="Invalid encoded image") from e
+        else:
+            return None
 
 
 def encode_pil_to_base64(image):

modules/api/models.py

@@ -194,8 +194,10 @@ ReqTxt2Img = PydanticModelGenerator(
     "StableDiffusionProcessingTxt2Img",
     StableDiffusionProcessingTxt2Img,
     [
-        {"key": "sampler_index", "type": str, "default": "UniPC"},
-        {"key": "script_name", "type": str, "default": None},
+        {"key": "sampler_index", "type": int, "default": 0},
+        {"key": "sampler_name", "type": str, "default": "UniPC"},
+        {"key": "hr_sampler_name", "type": str, "default": "Same as primary"},
+        {"key": "script_name", "type": str, "default": "none"},
         {"key": "script_args", "type": list, "default": []},
         {"key": "send_images", "type": bool, "default": True},
         {"key": "save_images", "type": bool, "default": False},
@@ -216,7 +218,11 @@ ReqImg2Img = PydanticModelGenerator(
     "StableDiffusionProcessingImg2Img",
     StableDiffusionProcessingImg2Img,
     [
-        {"key": "sampler_index", "type": str, "default": "UniPC"},
+        {"key": "sampler_index", "type": int, "default": 0},
+        {"key": "sampler_name", "type": str, "default": "UniPC"},
+        {"key": "hr_sampler_name", "type": str, "default": "Same as primary"},
+        {"key": "script_name", "type": str, "default": "none"},
+        {"key": "script_args", "type": list, "default": []},
         {"key": "init_images", "type": list, "default": None},
         {"key": "denoising_strength", "type": float, "default": 0.5},
         {"key": "mask", "type": str, "default": None},

modules/api/script.py

@@ -3,18 +3,25 @@ from fastapi.exceptions import HTTPException
 import gradio as gr
 from modules.api import models
 from modules import scripts
+from modules.errors import log
 
 
 def script_name_to_index(name, scripts_list):
+    if name is None or len(name) == 0:
+        return None
     try:
         return [script.title().lower() for script in scripts_list].index(name.lower())
-    except Exception as e:
-        raise HTTPException(status_code=422, detail=f"Script '{name}' not found") from e
+    except Exception:
+        log.error(f'API: script={name} not found')
+        return None
+        # raise HTTPException(status_code=422, detail=f"Script '{name}' not found") from e
 
 def get_selectable_script(script_name, script_runner):
     if script_name is None or script_name == "":
         return None, None
     script_idx = script_name_to_index(script_name, script_runner.selectable_scripts)
+    if script_idx is None:
+        return None, None
     script = script_runner.selectable_scripts[script_idx]
     return script, script_idx
 
@@ -36,6 +43,8 @@ def get_script(script_name, script_runner):
     if script_name is None or script_name == "":
         return None, None
     script_idx = script_name_to_index(script_name, script_runner.scripts)
+    if script_idx is None:
+        return None
     return script_runner.scripts[script_idx]
 
 def init_default_script_args(script_runner):

modules/processing_args.py

@@ -6,9 +6,11 @@ import time
 import inspect
 import torch
 import numpy as np
+from PIL import Image
 from modules import shared, errors, sd_models, processing, processing_vae, processing_helpers, sd_hijack_hypertile, prompt_parser_diffusers, timer
 from modules.processing_callbacks import diffusers_callback_legacy, diffusers_callback, set_callbacks_p
 from modules.processing_helpers import resize_hires, fix_prompts, calculate_base_steps, calculate_hires_steps, calculate_refiner_steps, get_generator, set_latents, apply_circular # pylint: disable=unused-import
+from modules.api import helpers
 
 
 debug = shared.log.trace if os.environ.get('SD_DIFFUSERS_DEBUG', None) is not None else lambda *args, **kwargs: None
@@ -18,7 +20,8 @@ def task_specific_kwargs(p, model):
     task_args = {}
     is_img2img_model = bool('Zero123' in shared.sd_model.__class__.__name__)
     if len(getattr(p, 'init_images', [])) > 0:
-        p.init_images = [p.convert('RGB') for p in p.init_images]
+        p.init_images = [helpers.decode_base64_to_image(i, quiet=True) for i in p.init_images if isinstance(i, str)]
+        p.init_images = [i.convert('RGB') for i in p.init_images if isinstance(i, Image.Image)]
     if sd_models.get_diffusers_task(model) == sd_models.DiffusersTaskType.TEXT_2_IMAGE or len(getattr(p, 'init_images', [])) == 0 and not is_img2img_model:
         p.ops.append('txt2img')
         if hasattr(p, 'width') and hasattr(p, 'height'):

modules/processing_class.py

@@ -21,7 +21,7 @@ class StableDiffusionProcessing:
                  sd_model=None, # pylint: disable=unused-argument # local instance of sd_model
                  # base params
                  prompt: str = "",
-                 negative_prompt: str = None,
+                 negative_prompt: str = "",
                  seed: int = -1,
                  subseed: int = -1,
                  subseed_strength: float = 0,

modules/processing_helpers.py

@@ -47,16 +47,23 @@ def apply_overlay(image: Image, paste_loc, index, overlays):
         return image
     debug(f'Apply overlay: image={image} loc={paste_loc} index={index} overlays={overlays}')
     overlay = overlays[index]
-    if paste_loc is not None:
-        x, y, w, h = paste_loc
-        if image.width != w or image.height != h or x != 0 or y != 0:
-            base_image = Image.new('RGBA', (overlay.width, overlay.height))
-            image = images.resize_image(2, image, w, h)
-            base_image.paste(image, (x, y))
-            image = base_image
-    image = image.convert('RGBA')
-    image.alpha_composite(overlay)
-    image = image.convert('RGB')
+    if not isinstance(image, Image.Image) or not isinstance(overlay, Image.Image):
+        return image
+    try:
+        if paste_loc is not None and (isinstance(paste_loc, tuple) or isinstance(paste_loc, list)):
+            x, y, w, h = paste_loc
+            if x is None or y is None or w is None or h is None:
+                return image
+            if image.width != w or image.height != h or x != 0 or y != 0:
+                base_image = Image.new('RGBA', (overlay.width, overlay.height))
+                image = images.resize_image(2, image, w, h)
+                base_image.paste(image, (x, y))
+                image = base_image
+        image = image.convert('RGBA')
+        image.alpha_composite(overlay)
+        image = image.convert('RGB')
+    except Exception as e:
+        shared.log.error(f'Apply overlay: {e}')
     return image