import numpy as np import datetime import random import math import os from PIL import Image LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) def resample_image(im, width, height): im = Image.fromarray(im) im = im.resize((int(width), int(height)), resample=LANCZOS) return np.array(im) def resize_image(im, width, height, resize_mode=1): """ Resizes an image with the specified resize_mode, width, and height. Args: resize_mode: The mode to use when resizing the image. 0: Resize the image to the specified width and height. 1: Resize the image to fill the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, cropping the excess. 2: Resize the image to fit within the specified width and height, maintaining the aspect ratio, and then center the image within the dimensions, filling empty with data from image. im: The image to resize. width: The width to resize the image to. height: The height to resize the image to. """ im = Image.fromarray(im) def resize(im, w, h): return im.resize((w, h), resample=LANCZOS) if resize_mode == 0: res = resize(im, width, height) elif resize_mode == 1: ratio = width / height src_ratio = im.width / im.height src_w = width if ratio > src_ratio else im.width * height // im.height src_h = height if ratio <= src_ratio else im.height * width // im.width resized = resize(im, src_w, src_h) res = Image.new("RGB", (width, height)) res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2)) else: ratio = width / height src_ratio = im.width / im.height src_w = width if ratio < src_ratio else im.width * height // im.height src_h = height if ratio >= src_ratio else im.height * width // im.width resized = resize(im, src_w, src_h) res = Image.new("RGB", (width, height)) res.paste(resized, box=(width // 2 - src_w // 2, height // 2 - src_h // 2)) if ratio < src_ratio: fill_height = height // 2 - src_h // 2 if fill_height > 0: res.paste(resized.resize((width, fill_height), box=(0, 0, width, 0)), box=(0, 0)) res.paste(resized.resize((width, fill_height), box=(0, resized.height, width, resized.height)), box=(0, fill_height + src_h)) elif ratio > src_ratio: fill_width = width // 2 - src_w // 2 if fill_width > 0: res.paste(resized.resize((fill_width, height), box=(0, 0, 0, height)), box=(0, 0)) res.paste(resized.resize((fill_width, height), box=(resized.width, 0, resized.width, height)), box=(fill_width + src_w, 0)) return np.array(res) def get_shape_ceil(h, w): return math.ceil(((h * w) ** 0.5) / 64.0) * 64.0 def get_image_shape_ceil(im): H, W = im.shape[:2] return get_shape_ceil(H, W) def set_image_shape_ceil(im, shape_ceil): shape_ceil = float(shape_ceil) H_origin, W_origin, _ = im.shape H, W = H_origin, W_origin for _ in range(256): current_shape_ceil = get_shape_ceil(H, W) if abs(current_shape_ceil - shape_ceil) < 0.1: break k = shape_ceil / current_shape_ceil H = int(round(float(H) * k / 64.0) * 64) W = int(round(float(W) * k / 64.0) * 64) if H == H_origin and W == W_origin: return im return resample_image(im, width=W, height=H) def HWC3(x): assert x.dtype == np.uint8 if x.ndim == 2: x = x[:, :, None] assert x.ndim == 3 H, W, C = x.shape assert C == 1 or C == 3 or C == 4 if C == 3: return x if C == 1: return np.concatenate([x, x, x], axis=2) if C == 4: color = x[:, :, 0:3].astype(np.float32) alpha = x[:, :, 3:4].astype(np.float32) / 255.0 y = color * alpha + 255.0 * (1.0 - alpha) y = y.clip(0, 255).astype(np.uint8) return y def remove_empty_str(items, default=None): items = [x for x in items if x != ""] if len(items) == 0 and default is not None: return [default] return items def join_prompts(*args, **kwargs): prompts = [str(x) for x in args if str(x) != ""] if len(prompts) == 0: return "" if len(prompts) == 1: return prompts[0] return ', '.join(prompts) def generate_temp_filename(folder='./outputs/', extension='png'): current_time = datetime.datetime.now() date_string = current_time.strftime("%Y-%m-%d") time_string = current_time.strftime("%Y-%m-%d_%H-%M-%S") random_number = random.randint(1000, 9999) filename = f"{time_string}_{random_number}.{extension}" result = os.path.join(folder, date_string, filename) return date_string, os.path.abspath(os.path.realpath(result)), filename def get_files_from_folder(folder_path, exensions=None, name_filter=None): if not os.path.isdir(folder_path): raise ValueError("Folder path is not a valid directory.") filenames = [] for root, dirs, files in os.walk(folder_path): relative_path = os.path.relpath(root, folder_path) if relative_path == ".": relative_path = "" for filename in files: _, file_extension = os.path.splitext(filename) if (exensions == None or file_extension.lower() in exensions) and (name_filter == None or name_filter in _): path = os.path.join(relative_path, filename) filenames.append(path) return sorted(filenames, key=lambda x: -1 if os.sep in x else 1)