sync with original main Fooocus repo

modules/util.py

@@ -0,0 +1,177 @@
+import numpy as np
+import datetime
+import random
+import math
+import os
+import cv2
+
+from PIL import Image
+
+
+LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
+
+
+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(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)