better model

image_transformation.py

@@ -15,7 +15,7 @@ if is_vision_available():
     from PIL import Image
 
 if is_diffusers_available():
-    from diffusers import ControlNetModel, StableDiffusionControlNetPipeline, UniPCMultistepScheduler
+    from diffusers import ControlNetModel, StableDiffusionControlNetPipeline, DPMSolverMultistepScheduler
 
 if is_opencv_available():
     import cv2
@@ -30,7 +30,7 @@ IMAGE_TRANSFORMATION_DESCRIPTION = (
 
 class ImageTransformationTool(Tool):
     default_stable_diffusion_checkpoint = "runwayml/stable-diffusion-v1-5"
-    default_controlnet_checkpoint = "lllyasviel/control_v11p_sd15_canny"
+    default_controlnet_checkpoint = "lllyasviel/control_v11e_sd15_ip2p"
     description = IMAGE_TRANSFORMATION_DESCRIPTION
     inputs = ['image', 'text']
     outputs = ['image']
@@ -66,7 +66,7 @@ class ImageTransformationTool(Tool):
         self.pipeline = StableDiffusionControlNetPipeline.from_pretrained(
             self.stable_diffusion_checkpoint, controlnet=self.controlnet
         )
-        self.pipeline.scheduler = UniPCMultistepScheduler.from_config(self.pipeline.scheduler.config)
+        self.pipeline.scheduler = DPMSolverMultistepScheduler.from_config(self.pipeline.scheduler.config)
 
         self.pipeline.to(self.device)
         if self.device.type == "cuda":
@@ -78,9 +78,6 @@ class ImageTransformationTool(Tool):
         if not self.is_initialized:
             self.setup()
 
-        initial_prompt = "super-hero character, best quality, extremely detailed"
-        prompt = initial_prompt + prompt
-
         low_threshold = 100
         high_threshold = 200