importmodules.scriptsasscriptsimportgradioasgrimportosfrommodulesimportimagesfrommodules.processingimportprocess_images,Processedfrommodules.processingimportProcessedfrommodules.sharedimportopts,cmd_opts,stateclassScript(scripts.Script):# The title of the script. This is what will be displayed in the dropdown menu.   deftitle(self):       return"Flip/Rotate Output"# Determines when the script should be shown in the dropdown menu via the# returned value. As an example:# is_img2img is True if the current tab is img2img, and False if it is txt2img.# Thus, return is_img2img to only show the script on the img2img tab.   defshow(self,is_img2img):       returnis_img2img# How the script's is displayed in the UI. See https://gradio.app/docs/#components# for the different UI components you can use and how to create them.# Most UI components can return a value, such as a boolean for a checkbox.# The returned values are passed to the run method as parameters.   defui(self,is_img2img):       angle=gr.Slider(minimum=0.0,maximum=360.0,step=1,value=0,       label="Angle")       hflip=gr.Checkbox(False,label="Horizontal flip")       vflip=gr.Checkbox(False,label="Vertical flip")       overwrite=gr.Checkbox(False,label="Overwrite existing files")       return [angle,hflip,vflip,overwrite]# This is where the additional processing is implemented. The parameters include# self, the model object "p" (a StableDiffusionProcessing class, see# processing.py), and the parameters returned by the ui method.# Custom functions can be defined here, and additional libraries can be imported# to be used in processing. The return value should be a Processed object, which is# what is returned by the process_images method.   defrun(self,p,angle,hflip,vflip,overwrite):       # function which takes an image from the Processed object,# and the angle and two booleans indicating horizontal and       # vertical flips from the UI, then returns the       # image rotated and flipped accordingly       defrotate_and_flip(im,angle,hflip,vflip):           fromPILimportImage                       raf=im                       ifangle!=0:               raf=raf.rotate(angle,expand=True)           ifhflip:               raf=raf.transpose(Image.FLIP_LEFT_RIGHT)           ifvflip:               raf=raf.transpose(Image.FLIP_TOP_BOTTOM)           returnraf         # If overwrite is false, append the rotation information to the filename       # using the "basename" parameter and save it in the same directory.       # If overwrite is true, stop the model from saving its outputs and       # save the rotated and flipped images instead.       basename=""       if(notoverwrite):           ifangle!=0:               basename+="rotated_"+str(angle)           ifhflip:               basename+="_hflip"           ifvflip:               basename+="_vflip"       else:           p.do_not_save_samples=True       proc=process_images(p)       # rotate and flip each image in the processed images# use the save_images method from images.py to save# them.       foriinrange(len(proc.images)):           proc.images[i]=rotate_and_flip(proc.images[i],angle,hflip,vflip)           images.save_image(proc.images[i],p.outpath_samples,basename,           proc.seed+i,proc.prompt,opts.samples_format,info=proc.info,p=p)       returnproc