| import math | |
| import modules.scripts as scripts | |
| import gradio as gr | |
| from PIL import Image, ImageDraw | |
| from modules import images, processing, devices | |
| from modules.processing import Processed, process_images | |
| from modules.shared import opts, cmd_opts, state | |
| class Script(scripts.Script): | |
| def title(self): | |
| return "Poor man's outpainting" | |
| def show(self, is_img2img): | |
| return is_img2img | |
| def ui(self, is_img2img): | |
| if not is_img2img: | |
| return None | |
| pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=self.elem_id("pixels")) | |
| mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id=self.elem_id("mask_blur")) | |
| inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", elem_id=self.elem_id("inpainting_fill")) | |
| direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'], elem_id=self.elem_id("direction")) | |
| return [pixels, mask_blur, inpainting_fill, direction] | |
| def run(self, p, pixels, mask_blur, inpainting_fill, direction): | |
| initial_seed = None | |
| initial_info = None | |
| p.mask_blur = mask_blur * 2 | |
| p.inpainting_fill = inpainting_fill | |
| p.inpaint_full_res = False | |
| left = pixels if "left" in direction else 0 | |
| right = pixels if "right" in direction else 0 | |
| up = pixels if "up" in direction else 0 | |
| down = pixels if "down" in direction else 0 | |
| init_img = p.init_images[0] | |
| target_w = math.ceil((init_img.width + left + right) / 64) * 64 | |
| target_h = math.ceil((init_img.height + up + down) / 64) * 64 | |
| if left > 0: | |
| left = left * (target_w - init_img.width) // (left + right) | |
| if right > 0: | |
| right = target_w - init_img.width - left | |
| if up > 0: | |
| up = up * (target_h - init_img.height) // (up + down) | |
| if down > 0: | |
| down = target_h - init_img.height - up | |
| img = Image.new("RGB", (target_w, target_h)) | |
| img.paste(init_img, (left, up)) | |
| mask = Image.new("L", (img.width, img.height), "white") | |
| draw = ImageDraw.Draw(mask) | |
| draw.rectangle(( | |
| left + (mask_blur * 2 if left > 0 else 0), | |
| up + (mask_blur * 2 if up > 0 else 0), | |
| mask.width - right - (mask_blur * 2 if right > 0 else 0), | |
| mask.height - down - (mask_blur * 2 if down > 0 else 0) | |
| ), fill="black") | |
| latent_mask = Image.new("L", (img.width, img.height), "white") | |
| latent_draw = ImageDraw.Draw(latent_mask) | |
| latent_draw.rectangle(( | |
| left + (mask_blur//2 if left > 0 else 0), | |
| up + (mask_blur//2 if up > 0 else 0), | |
| mask.width - right - (mask_blur//2 if right > 0 else 0), | |
| mask.height - down - (mask_blur//2 if down > 0 else 0) | |
| ), fill="black") | |
| devices.torch_gc() | |
| grid = images.split_grid(img, tile_w=p.width, tile_h=p.height, overlap=pixels) | |
| grid_mask = images.split_grid(mask, tile_w=p.width, tile_h=p.height, overlap=pixels) | |
| grid_latent_mask = images.split_grid(latent_mask, tile_w=p.width, tile_h=p.height, overlap=pixels) | |
| p.n_iter = 1 | |
| p.batch_size = 1 | |
| p.do_not_save_grid = True | |
| p.do_not_save_samples = True | |
| work = [] | |
| work_mask = [] | |
| work_latent_mask = [] | |
| work_results = [] | |
| for (y, h, row), (_, _, row_mask), (_, _, row_latent_mask) in zip(grid.tiles, grid_mask.tiles, grid_latent_mask.tiles): | |
| for tiledata, tiledata_mask, tiledata_latent_mask in zip(row, row_mask, row_latent_mask): | |
| x, w = tiledata[0:2] | |
| if x >= left and x+w <= img.width - right and y >= up and y+h <= img.height - down: | |
| continue | |
| work.append(tiledata[2]) | |
| work_mask.append(tiledata_mask[2]) | |
| work_latent_mask.append(tiledata_latent_mask[2]) | |
| batch_count = len(work) | |
| print(f"Poor man's outpainting will process a total of {len(work)} images tiled as {len(grid.tiles[0][2])}x{len(grid.tiles)}.") | |
| state.job_count = batch_count | |
| for i in range(batch_count): | |
| p.init_images = [work[i]] | |
| p.image_mask = work_mask[i] | |
| p.latent_mask = work_latent_mask[i] | |
| state.job = f"Batch {i + 1} out of {batch_count}" | |
| processed = process_images(p) | |
| if initial_seed is None: | |
| initial_seed = processed.seed | |
| initial_info = processed.info | |
| p.seed = processed.seed + 1 | |
| work_results += processed.images | |
| image_index = 0 | |
| for y, h, row in grid.tiles: | |
| for tiledata in row: | |
| x, w = tiledata[0:2] | |
| if x >= left and x+w <= img.width - right and y >= up and y+h <= img.height - down: | |
| continue | |
| tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height)) | |
| image_index += 1 | |
| combined_image = images.combine_grid(grid) | |
| if opts.samples_save: | |
| images.save_image(combined_image, p.outpath_samples, "", initial_seed, p.prompt, opts.grid_format, info=initial_info, p=p) | |
| processed = Processed(p, [combined_image], initial_seed, initial_info) | |
| return processed | |