Clean up image transformation

image_transformation.py

@@ -6,7 +6,6 @@ from transformers.tools.base import Tool, get_default_device
 from transformers.utils import (
     is_accelerate_available,
     is_diffusers_available,
-    is_opencv_available,
     is_vision_available,
 )
 
@@ -17,9 +16,6 @@ if is_vision_available():
 if is_diffusers_available():
     from diffusers import DiffusionPipeline
 
-if is_opencv_available():
-    import cv2
-
 
 IMAGE_TRANSFORMATION_DESCRIPTION = (
     "This is a tool that transforms an image according to a prompt. It takes two inputs: `image`, which should be "
@@ -41,8 +37,6 @@ class ImageTransformationTool(Tool):
             raise ImportError("Diffusers should be installed in order to use the StableDiffusionTool.")
         if not is_vision_available():
             raise ImportError("Pillow should be installed in order to use the StableDiffusionTool.")
-        if not is_opencv_available():
-            raise ImportError("opencv should be installed in order to use the StableDiffusionTool.")
 
         super().__init__()
 
@@ -63,10 +57,13 @@ class ImageTransformationTool(Tool):
 
         self.is_initialized = True
 
-    def __call__(self, image, prompt, negative_prompt="low quality, bad quality, deformed, low resolution", added_prompt=" , highest quality, highly realistic, very high resolution"):
+    def __call__(self, image, prompt):
         if not self.is_initialized:
             self.setup()
 
+        negative_prompt = "low quality, bad quality, deformed, low resolution"
+        added_prompt = " , highest quality, highly realistic, very high resolution"
+
         return self.pipeline(
             prompt + added_prompt,
             image,