import math, time, os import numpy as np from typing import Callable, Any from PIL import Image, ImageFilter, ImageOps, ImageDraw from modules.ui import plaintext_to_html import modules.shared as shared from modules.paths_internal import script_path from .helpers import ( fix_env_Path_ffprobe, closest_upper_divisible_by_eight, load_model_from_setting, do_upscaleImg, ) from .sd_helpers import renderImg2Img, renderTxt2Img from .image import shrink_and_paste_on_blank from .video import ContinuousVideoWriter from .InfZoomConfig import InfZoomConfig class InfZoomer: def __init__(self, config: InfZoomConfig) -> None: self.C = config self.prompts = {} self.main_frames = [] self.out_config = {} for x in self.C.prompts_array: try: key = int(x[0]) value = str(x[1]) self.prompts[key] = value except ValueError: pass assert len(self.C.prompts_array) > 0, "prompts is empty" fix_env_Path_ffprobe() self.out_config = self.prepare_output_path() self.width = closest_upper_divisible_by_eight(self.C.outputsizeW) self.height = closest_upper_divisible_by_eight(self.C.outputsizeH) self.current_seed = self.C.seed self.mask_width = self.width * 1//4 # was initially 512px => 128px self.mask_height = self.height * 1//4 # was initially 512px => 128px self.num_interpol_frames = round(self.C.video_frame_rate * self.C.zoom_speed) if (self.C.outpaintStrategy == "Corners"): self.fnOutpaintMainFrames = self.outpaint_steps_cornerStrategy self.fnInterpolateFrames = self.interpolateFramesOutIn elif (self.C.outpaintStrategy == "Center"): self.fnOutpaintMainFrames = self.outpaint_steps_v8hid self.fnInterpolateFrames = self.interpolateFramesSmallCenter else: raise ValueError("Unsupported outpaint strategy in Infinite Zoom") outerZoom = True # scale from overscan to target viewport # object properties, different from user input config out_config = {} prompts = {} main_frames:Image = [] outerZoom: bool mask_width: int mask_height: int current_seed: int contVW: ContinuousVideoWriter fnOutpaintMainFrames: Callable fnInterpolateFrames: Callable def create_zoom(self): for i in range(self.C.batchcount): print(f"Batch {i+1}/{self.C.batchcount}") result = self.create_zoom_single() return result def create_zoom_single(self): self.main_frames.append(self.prepareInitImage()) load_model_from_setting("infzoom_inpainting_model", self.C.progress, "Loading Model for inpainting/img2img: ") processed = self.fnOutpaintMainFrames() if (self.C.upscale_do): self.doUpscaling() if self.C.video_zoom_mode: self.main_frames = self.main_frames[::-1] self.contVW = ContinuousVideoWriter(self.out_config["video_filename"], self.main_frames[0],self.C.video_frame_rate,int(self.C.video_start_frame_dupe_amount)) self.fnInterpolateFrames() # changes main_frame and writes to video self.contVW.finish(self.main_frames[-1],int(self.C.video_last_frame_dupe_amount)) print("Video saved in: " + os.path.join(script_path, self.out_config["video_filename"])) return ( self.out_config["video_filename"], self.main_frames, processed.js(), plaintext_to_html(processed.info), plaintext_to_html(""), ) def doUpscaling(self): for idx,mf in enumerate(self.main_frames): print (f"\033[KInfZoom: Upscaling mainframe: {idx} \r") self.main_frames[idx]=do_upscaleImg(mf, self.C.upscale_do, self.C.upscaler_name, self.C.upscale_by) self.width = self.main_frames[0].width self.height = self.main_frames[0].height self.mask_width = math.trunc(self.mask_width*self.C.upscale_by) self.mask_height = math.trunc(self.mask_height *self.C.upscale_by) def prepareInitImage(self) -> Image: if self.C.custom_init_image: current_image = Image.new(mode="RGBA", size=(self.width, self.height)) current_image = current_image.convert("RGB") current_image = self.C.custom_init_image.resize( (self.width, self.height), resample=Image.LANCZOS ) self.save2Collect(current_image, f"init_custom.png") else: load_model_from_setting("infzoom_txt2img_model", self.C.progress, "Loading Model for txt2img: ") processed, newseed = self.renderFirstFrame() if len(processed.images) > 0: current_image = processed.images[0] self.save2Collect(current_image, f"init_txt2img.png") self.current_seed = newseed return current_image def renderFirstFrame(self): pr = self.getInitialPrompt() return renderTxt2Img( f"{self.C.common_prompt_pre}\n{pr}\n{self.C.common_prompt_suf}".strip(), self.C.negative_prompt, self.C.sampler, self.C.num_inference_steps, self.C.guidance_scale, self.current_seed, self.width, self.height ) def getInitialPrompt(self): return self.prompts[min(k for k in self.prompts.keys() if k >= 0)] def outpaint_steps_cornerStrategy(self): currentImage = self.main_frames[-1] original_width, original_height = currentImage.size new_width = original_width + self.mask_width*2 new_height = original_height + self.mask_height*2 left = right = int(self.mask_width) top = bottom = int(self.mask_height) corners = [ (0, 0), (new_width - 512, 0), (0, new_height - 512), (new_width - 512, new_height - 512), ] masked_images = [] for idx, corner in enumerate(corners): white = Image.new("1", (new_width,new_height), 1) draw = ImageDraw.Draw(white) draw.rectangle([corner[0], corner[1], corner[0]+512, corner[1]+512], fill=0) masked_images.append(white) outpaint_steps=self.C.num_outpainting_steps for i in range(outpaint_steps): print (f"Outpaint step: {str(i + 1)}/{str(outpaint_steps)} Seed: {str(self.current_seed)}") currentImage = self.main_frames[-1] if self.C.custom_exit_image and ((i + 1) == outpaint_steps): currentImage = self.C.custom_exit_image.resize( (self.C.width, self.C.height), resample=Image.LANCZOS ) self.main_frames.append(currentImage.convert("RGB")) # print("using Custom Exit Image") self.save2Collect(currentImage, self.out_config, f"exit_img.png") else: expanded_image = ImageOps.expand(currentImage, (left, top, right, bottom), fill=(0, 0, 0)) pr = self.prompts[max(k for k in self.prompts.keys() if k <= i)] # outpaint 4 corners loop for idx,cornermask in enumerate(masked_images): processed, newseed = renderImg2Img( f"{self.C.common_prompt_pre}\n{pr}\n{self.C.common_prompt_suf}".strip(), self.C.negative_prompt, self.C.sampler, self.C.num_inference_steps, self.C.guidance_scale, self.current_seed, 512, #outpaintsizeW 512, #outpaintsizeH expanded_image, cornermask, 1, #inpainting_denoising_strength, 0, # inpainting_mask_blur, 2, ## noise? fillmode True, # only masked, not full, keep size of expandedimage! 0 #inpainting_padding, ) expanded_image = processed.images[0] # if len(processed.images) > 0: zoomed_img = expanded_image.resize((self.width,self.height), Image.Resampling.LANCZOS) self.main_frames.append(zoomed_img) processed.images[0]=self.main_frames[-1] self.save2Collect(processed.images[0], f"outpaint_step_{i}.png") seed = newseed # TODO: seed behavior return processed def outpaint_steps_v8hid(self): for i in range(self.C.num_outpainting_steps): print (f"Outpaint step: {str(i + 1)} / {str(self.C.num_outpainting_steps)} Seed: {str(self.current_seed)}") current_image = self.main_frames[-1] current_image = shrink_and_paste_on_blank( current_image, self.mask_width, self.mask_height ) mask_image = np.array(current_image)[:, :, 3] mask_image = Image.fromarray(255 - mask_image).convert("RGB") if self.C.custom_exit_image and ((i + 1) == self.C.num_outpainting_steps): current_image = self.C.custom_exit_image.resize( (self.width, self.height), resample=Image.LANCZOS ) self.main_frames.append(current_image.convert("RGB")) # print("using Custom Exit Image") self.save2Collect(current_image, f"exit_img.png") else: pr = self.prompts[max(k for k in self.prompts.keys() if k <= i)] processed, newseed = renderImg2Img( f"{self.C.common_prompt_pre}\n{pr}\n{self.C.common_prompt_suf}".strip(), self.C.negative_prompt, self.C.sampler, self.C.num_inference_steps, self.C.guidance_scale, self.current_seed, self.width, self.height, current_image, mask_image, self.C.inpainting_denoising_strength, self.C.inpainting_mask_blur, self.C.inpainting_fill_mode, self.C.inpainting_full_res, self.C.inpainting_padding, ) if len(processed.images) > 0: self.main_frames.append(processed.images[0].convert("RGB")) self.save2Collect(processed.images[0], f"outpain_step_{i}.png") seed = newseed # TODO: seed behavior return processed def outpaint_steps_smallCenter(self): # one mask for all steps and outpaints mask_image = np.array(shrink_and_paste_on_blank( self.main_frames[0], self.mask_width+self.C.overmask, self.mask_height+self.C.overmask) )[:, :, 3] mask_image = Image.fromarray(255 - mask_image).convert("RGB") # if (self.C.inpainting_fill_mode == 1): # ORIGINAL outpaint_steps=self.C.num_outpainting_steps for i in range(outpaint_steps): print (f"Outpaint step: {str(i + 1)}/{str(outpaint_steps)} Seed: {str(self.current_seed)}") currentImage = self.main_frames[-1] if self.C.custom_exit_image and ((i + 1) == outpaint_steps): currentImage = self.C.custom_exit_image.resize( (self.C.width, self.C.height), resample=Image.LANCZOS ) self.main_frames.append(currentImage.convert("RGB")) # print("using Custom Exit Image") self.save2Collect(currentImage, self.out_config, f"exit_img.png") else: smaller_image = shrink_and_paste_on_blank(currentImage,self.mask_width,self.mask_height) pr = self.prompts[max(k for k in self.prompts.keys() if k <= i)] processed, newseed = renderImg2Img( f"{self.C.common_prompt_pre}\n{pr}\n{self.C.common_prompt_suf}".strip(), self.C.negative_prompt, self.C.sampler, self.C.num_inference_steps, self.C.guidance_scale, self.current_seed, 512, #outpaintsizeW 512, #outpaintsizeH smaller_image, mask_image, 1, #inpainting_denoising_strength, self.C.inpainting_mask_blur, self.C.inpainting_fill_mode, True, # only masked, not full, keep size of expandedimage! 0 #inpainting_padding, ) if len(processed.images) > 0: self.main_frames.append(processed.images[0]) self.save2Collect(processed.images[0], f"outpaint_step_{i}.png") seed = newseed # TODO: seed behavior return processed def interpolateFramesOutIn(self): for i in range(len(self.main_frames) - 1): # interpolation steps between 2 inpainted images (=sequential zoom and crop) for j in range(self.num_interpol_frames - 1): print (f"\033[KInfZoom: Interpolate frame: main/inter: {i}/{j} \r") #todo: howto zoomIn when writing each frame; self.main_frames are inverted, howto interpolate? if self.C.video_zoom_mode: current_image = self.main_frames[i + 1] else: current_image = self.main_frames[i + 1] interpol_image = current_image self.save2Collect(interpol_image, f"interpol_img_{i}_{j}].png") interpol_width = math.ceil( ( 1 - (1 - 2 * self.mask_width / self.width) **(1 - (j + 1) / self.num_interpol_frames) ) * self.width / 2 ) interpol_height = math.ceil( ( 1 - (1 - 2 * self.mask_height / self.height) ** (1 - (j + 1) / self.num_interpol_frames) ) * self.height/2 ) interpol_image = interpol_image.crop( ( interpol_width, interpol_height, self.width - interpol_width, self.height - interpol_height, ) ) interpol_image = interpol_image.resize((self.width, self.height)) self.save2Collect(interpol_image, f"interpol_resize_{i}_{j}.png") # paste the higher resolution previous image in the middle to avoid drop in quality caused by zooming interpol_width2 = math.ceil( (1 - (self.width - 2 * self.mask_width) / (self.width - 2 * interpol_width)) / 2 * self.width ) interpol_height2 = math.ceil( (1 - (self.height - 2 * self.mask_height) / (self.height - 2 * interpol_height)) / 2 * self.height ) prev_image_fix_crop = shrink_and_paste_on_blank( self.main_frames[i], interpol_width2, interpol_height2 ) interpol_image.paste(prev_image_fix_crop, mask=prev_image_fix_crop) self.save2Collect(interpol_image, f"interpol_prevcrop_{i}_{j}.png") self.contVW.append([interpol_image]) self.contVW.append([current_image]) def interpolateFramesSmallCenter(self): for i in range(len(self.main_frames) - 1): # interpolation steps between 2 inpainted images (=sequential zoom and crop) for j in range(self.num_interpol_frames - 1): print (f"\033[KInfZoom: Interpolate frame: main/inter: {i}/{j} \r") #todo: howto zoomIn when writing each frame; self.main_frames are inverted, howto interpolate? if self.C.video_zoom_mode: current_image = self.main_frames[i + 1] else: current_image = self.main_frames[i + 1] interpol_image = current_image self.save2Collect(interpol_image, f"interpol_img_{i}_{j}].png") interpol_width = math.ceil( ( 1 - (1 - 2 * self.mask_width / self.width) **(1 - (j + 1) / self.num_interpol_frames) ) * self.width / 2 ) interpol_height = math.ceil( ( 1 - (1 - 2 * self.mask_height / self.height) ** (1 - (j + 1) / self.num_interpol_frames) ) * self.height/2 ) interpol_image = interpol_image.crop( ( interpol_width, interpol_height, self.width - interpol_width, self.height - interpol_height, ) ) interpol_image = interpol_image.resize((self.width, self.height)) self.save2Collect(interpol_image, f"interpol_resize_{i}_{j}.png") # paste the higher resolution previous image in the middle to avoid drop in quality caused by zooming interpol_width2 = math.ceil( (1 - (self.width - 2 * self.mask_width) / (self.width - 2 * interpol_width)) / 2 * self.width ) interpol_height2 = math.ceil( (1 - (self.height - 2 * self.mask_height) / (self.height - 2 * interpol_height)) / 2 * self.height ) prev_image_fix_crop = shrink_and_paste_on_blank( self.main_frames[i], interpol_width2, interpol_height2 ) interpol_image.paste(prev_image_fix_crop, mask=prev_image_fix_crop) self.save2Collect(interpol_image, f"interpol_prevcrop_{i}_{j}.png") self.contVW.append([interpol_image]) self.contVW.append([current_image]) def prepare_output_path(self): isCollect = shared.opts.data.get("infzoom_collectAllResources", False) output_path = shared.opts.data.get("infzoom_outpath", "outputs") save_path = os.path.join( output_path, shared.opts.data.get("infzoom_outSUBpath", "infinite-zooms") ) if isCollect: save_path = os.path.join(save_path, "iz_collect" + str(int(time.time()))) if not os.path.exists(save_path): os.makedirs(save_path) video_filename = os.path.join( save_path, "infinite_zoom_" + str(int(time.time())) + ".mp4" ) return { "isCollect": isCollect, "save_path": save_path, "video_filename": video_filename, } def save2Collect(self, img, name): if self.out_config["isCollect"]: img.save(f'{self.out_config["save_path"]}/{name}.png') def frame2Collect(self,all_frames): self.save2Collect(all_frames[-1], self.out_config, f"frame_{len(all_frames)}") def frames2Collect(self, all_frames): for i, f in enumerate(all_frames): self.save2Collect(f, self.out_config, f"frame_{i}") def crop_inner_image(self, outpainted_img, width_offset, height_offset): width, height = outpainted_img.size center_x, center_y = int(width / 2), int(height / 2) # Crop the image to the center cropped_img = outpainted_img.crop( ( center_x - width_offset, center_y - height_offset, center_x + width_offset, center_y + height_offset, ) ) prev_step_img = cropped_img.resize((width, height), resample=Image.LANCZOS) # resized_img = resized_img.filter(ImageFilter.SHARPEN) return prev_step_img