util.py

import typing

import numpy as np
import datetime
import random
import math
import os
import cv2
import json

from PIL import Image
from hashlib import sha256

import modules.sdxl_styles

LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
HASH_SHA256_LENGTH = 10

def erode_or_dilate(x, k):
    k = int(k)
    if k > 0:
        return cv2.dilate(x, kernel=np.ones(shape=(3, 3), dtype=np.uint8), iterations=k)
    if k < 0:
        return cv2.erode(x, kernel=np.ones(shape=(3, 3), dtype=np.uint8), iterations=-k)
    return x


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(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, topdown=False):
        relative_path = os.path.relpath(root, folder_path)
        if relative_path == ".":
            relative_path = ""
        for filename in sorted(files, key=lambda s: s.casefold()):
            _, file_extension = os.path.splitext(filename)
            if (exensions is None or file_extension.lower() in exensions) and (name_filter is None or name_filter in _):
                path = os.path.join(relative_path, filename)
                filenames.append(path)

    return filenames


def calculate_sha256(filename, length=HASH_SHA256_LENGTH) -> str:
    hash_sha256 = sha256()
    blksize = 1024 * 1024

    with open(filename, "rb") as f:
        for chunk in iter(lambda: f.read(blksize), b""):
            hash_sha256.update(chunk)

    res = hash_sha256.hexdigest()
    return res[:length] if length else res


def quote(text):
    if ',' not in str(text) and '\n' not in str(text) and ':' not in str(text):
        return text

    return json.dumps(text, ensure_ascii=False)


def unquote(text):
    if len(text) == 0 or text[0] != '"' or text[-1] != '"':
        return text

    try:
        return json.loads(text)
    except Exception:
        return text


def unwrap_style_text_from_prompt(style_text, prompt):
    """
    Checks the prompt to see if the style text is wrapped around it. If so,
    returns True plus the prompt text without the style text. Otherwise, returns
    False with the original prompt.

    Note that the "cleaned" version of the style text is only used for matching
    purposes here. It isn't returned; the original style text is not modified.
    """
    stripped_prompt = prompt
    stripped_style_text = style_text
    if "{prompt}" in stripped_style_text:
        # Work out whether the prompt is wrapped in the style text. If so, we
        # return True and the "inner" prompt text that isn't part of the style.
        try:
            left, right = stripped_style_text.split("{prompt}", 2)
        except ValueError as e:
            # If the style text has multple "{prompt}"s, we can't split it into
            # two parts. This is an error, but we can't do anything about it.
            print(f"Unable to compare style text to prompt:\n{style_text}")
            print(f"Error: {e}")
            return False, prompt, ''

        left_pos = stripped_prompt.find(left)
        right_pos = stripped_prompt.find(right)
        if 0 <= left_pos < right_pos:
            real_prompt = stripped_prompt[left_pos + len(left):right_pos]
            prompt = stripped_prompt.replace(left + real_prompt + right, '', 1)
            if prompt.startswith(", "):
                prompt = prompt[2:]
            if prompt.endswith(", "):
                prompt = prompt[:-2]
            return True, prompt, real_prompt
    else:
        # Work out whether the given prompt starts with the style text. If so, we
        # return True and the prompt text up to where the style text starts.
        if stripped_prompt.endswith(stripped_style_text):
            prompt = stripped_prompt[: len(stripped_prompt) - len(stripped_style_text)]
            if prompt.endswith(", "):
                prompt = prompt[:-2]
            return True, prompt, prompt

    return False, prompt, ''


def extract_original_prompts(style, prompt, negative_prompt):
    """
    Takes a style and compares it to the prompt and negative prompt. If the style
    matches, returns True plus the prompt and negative prompt with the style text
    removed. Otherwise, returns False with the original prompt and negative prompt.
    """
    if not style.prompt and not style.negative_prompt:
        return False, prompt, negative_prompt

    match_positive, extracted_positive, real_prompt = unwrap_style_text_from_prompt(
        style.prompt, prompt
    )
    if not match_positive:
        return False, prompt, negative_prompt, ''

    match_negative, extracted_negative, _ = unwrap_style_text_from_prompt(
        style.negative_prompt, negative_prompt
    )
    if not match_negative:
        return False, prompt, negative_prompt, ''

    return True, extracted_positive, extracted_negative, real_prompt


def extract_styles_from_prompt(prompt, negative_prompt):
    extracted = []
    applicable_styles = []

    for style_name, (style_prompt, style_negative_prompt) in modules.sdxl_styles.styles.items():
        applicable_styles.append(PromptStyle(name=style_name, prompt=style_prompt, negative_prompt=style_negative_prompt))

    real_prompt = ''

    while True:
        found_style = None

        for style in applicable_styles:
            is_match, new_prompt, new_neg_prompt, new_real_prompt = extract_original_prompts(
                style, prompt, negative_prompt
            )
            if is_match:
                found_style = style
                prompt = new_prompt
                negative_prompt = new_neg_prompt
                if real_prompt == '' and new_real_prompt != '' and new_real_prompt != prompt:
                    real_prompt = new_real_prompt
                break

        if not found_style:
            break

        applicable_styles.remove(found_style)
        extracted.append(found_style.name)

    # add prompt expansion if not all styles could be resolved
    if prompt != '':
        if real_prompt != '':
            extracted.append(modules.sdxl_styles.fooocus_expansion)
        else:
            # find real_prompt when only prompt expansion is selected
            first_word = prompt.split(', ')[0]
            first_word_positions = [i for i in range(len(prompt)) if prompt.startswith(first_word, i)]
            if len(first_word_positions) > 1:
                real_prompt = prompt[:first_word_positions[-1]]
                extracted.append(modules.sdxl_styles.fooocus_expansion)
                if real_prompt.endswith(', '):
                    real_prompt = real_prompt[:-2]

    return list(reversed(extracted)), real_prompt, negative_prompt


class PromptStyle(typing.NamedTuple):
    name: str
    prompt: str
    negative_prompt: str


def is_json(data: str) -> bool:
    try:
        loaded_json = json.loads(data)
        assert isinstance(loaded_json, dict)
    except (ValueError, AssertionError):
        return False
    return True

def ordinal_suffix(number: int) -> str:
    return 'th' if 10 <= number % 100 <= 20 else {1: 'st', 2: 'nd', 3: 'rd'}.get(number % 10, 'th')