python生成psd文件实例

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gen_psd.py from PIL import Image from psd_tools import PSDImage from psd_tools.api.layers import PixelLayer def image_to_psd(image_obj: Image, save_path): # 确保图像模式为 RGBA if image_obj.mode != “RGBA”: image_obj = image_obj.convert(“RGBA”) # 将PIL图像转换为PSD格式 psd = PSDImage.frompil(image_obj) # 创建一个新图层 pixel_layer = PixelLayer.frompil(image_obj, psd) pixel_layer.visible = True # 设置图层为可见 psd.append(pixel_layer) # 将图层添加到PSD中 psd.save(save_path) # 保存为PSD文件 if __name__ == “__main__”: image_obj = Image.open(r”D:project_2025live2dtalking-head-anime-4-demo-maindemocharacter_modelcharacter.png”) save_path = ‘demo.psd’ image_to_psd(image_obj, save_path)
from PIL import Image from psd_tools import PSDImage from psd_tools.api.layers import PixelLayer def image_to_psd(image_paths, save_path): # 读取第一张图，作为 PSD 画布 base_img = Image.open(image_paths[0]).convert(“RGBA”) psd = PSDImage.frompil(base_img) # 第一个图层 layer0 = PixelLayer.frompil(base_img, psd) layer0.name = “Base” layer0.visible = True psd.append(layer0) # 后续图片作为新图层 for i, img_path in enumerate(image_paths[1:], start=1): img = Image.open(img_path).convert(“RGBA”) layer = PixelLayer.frompil(img, psd) layer.name = f”Layer_{i}” layer.visible = True psd.append(layer) # 保存 PSD psd.save(save_path) if __name__ == “__main__”: image_paths = [ r”D:project_2025live2dtalking-head-anime-4-demo-maindemodataimageslambda_02_face_mask.png”, r”D:project_2025live2dtalking-head-anime-4-demo-maindemodataimageslambda_02.png”, ] image_to_psd(image_paths, “demo.psd”)

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from PIL import Image

from psd_tools import PSDImage
from psd_tools.api.layers import PixelLayer

def image_to_psd(image_obj: Image, save_path):
    # 确保图像模式为 RGBA
    if image_obj.mode != "RGBA":
        image_obj = image_obj.convert("RGBA")

    # 将PIL图像转换为PSD格式
    psd = PSDImage.frompil(image_obj)

    # 创建一个新图层
    pixel_layer = PixelLayer.frompil(image_obj, psd)
    pixel_layer.visible = True  # 设置图层为可见

    psd.append(pixel_layer)  # 将图层添加到PSD中
    psd.save(save_path)  # 保存为PSD文件

if __name__ == "__main__":
    image_obj = Image.open(r"D:project_2025live2dtalking-head-anime-4-demo-maindemocharacter_modelcharacter.png")
    save_path = 'demo.psd'
    image_to_psd(image_obj, save_path)

from PIL import Image
from psd_tools import PSDImage
from psd_tools.api.layers import PixelLayer


def image_to_psd(image_paths, save_path):
    # 读取第一张图，作为 PSD 画布
    base_img = Image.open(image_paths[0]).convert("RGBA")
    psd = PSDImage.frompil(base_img)

    # 第一个图层
    layer0 = PixelLayer.frompil(base_img, psd)
    layer0.name = "Base"
    layer0.visible = True
    psd.append(layer0)

    # 后续图片作为新图层
    for i, img_path in enumerate(image_paths[1:], start=1):
        img = Image.open(img_path).convert("RGBA")
        layer = PixelLayer.frompil(img, psd)
        layer.name = f"Layer_{i}"
        layer.visible = True
        psd.append(layer)

    # 保存 PSD
    psd.save(save_path)


if __name__ == "__main__":
    image_paths = [
        r"D:project_2025live2dtalking-head-anime-4-demo-maindemodataimageslambda_02_face_mask.png",
        r"D:project_2025live2dtalking-head-anime-4-demo-maindemodataimageslambda_02.png",
    ]

    image_to_psd(image_paths, "demo.psd")

import os
from PIL import Image
from psd_tools import PSDImage

import cv2
import numpy as np
import os

from psd_tools.api.layers import PixelLayer

from Skps import FaceAna

def generate_eye_ellipse_mask(image_shape, landmarks, indices, scale_x=2, scale_y=1.25):
    """
    使用最小外接椭圆生成眼睛 mask
    """
    mask = np.zeros(image_shape[:2], dtype=np.uint8)
    pts = landmarks[indices].astype(np.int32)

    if pts.shape[0] < 5:
        return mask

    ellipse = cv2.fitEllipse(pts)
    (cx, cy), (w, h), angle = ellipse

    w *= scale_x
    h *= scale_y

    cv2.ellipse(
        mask,
        ((int(cx), int(cy)), (int(w), int(h)), angle),
        255,
        -1
    )
    return mask

def generate_part_mask(image_shape, landmarks, indices):
    """
    根据关键点索引生成对应部位的二进制遮罩。
    Args:
        image_shape: 原图尺寸 (H, W)
        landmarks: 人脸关键点坐标数组
        indices: 特定部位的关键点索引列表
    Returns:
        mask: 二值化遮罩 (0/255)
    """
    mask = np.zeros(image_shape[:2], dtype=np.uint8)
    pts = landmarks[indices].astype(np.int32)
    # 使用凸包或最小矩形来定义区域
    if len(indices) > 2:  # 对于眼睛、嘴巴等轮廓点
        hull = cv2.convexHull(pts)
        cv2.fillConvexPoly(mask, hull, 255)
    else:  # 对于可能需要矩形定义的部位
        x, y, w, h = cv2.boundingRect(pts)
        cv2.rectangle(mask, (x, y), (x + w, y + h), 255, -1)
    return mask


def masks_to_psd(base_image_path, masks_dict, output_psd_path):

    # 1. 读取基础图像作为背景层
    base_img = Image.open(base_image_path).convert("RGBA")
    # 2. 创建一个以基础图像为画布的PSD对象[citation:4][citation:9]
    psd = PSDImage.frompil(base_img)

    # 3. 为每个部位创建图层[citation:4][citation:9]
    for layer_name, mask in masks_dict.items():
        # 将二值mask (0/255) 转换为RGBA图像

        rgba_array = np.array(base_img).copy()  # 形状为 (H, W, 4)
        rgba_array[mask == 0, 3] = 0  # 索引3代表RGBA中的A（Alpha）通道

        part_img = Image.fromarray(rgba_array, mode='RGBA')
        # 第一个图层
        layer0 = PixelLayer.frompil(part_img, psd)
        layer0.name = layer_name
        layer0.visible = True
        psd.append(layer0)

    # 4. 保存PSD文件[citation:4]
    psd.save(output_psd_path)
    print(f"PSD文件已生成: {output_psd_path}")

def generate_face_outer_mask(image_shape, landmarks, indices):
    """
    生成头部轮廓以外的 mask
    """
    h, w = image_shape[:2]
    mask_face = np.zeros((h, w), np.uint8)

    pts = landmarks[indices].astype(np.int32)
    hull = cv2.convexHull(pts)
    cv2.fillConvexPoly(mask_face, hull, 255)

    # 反转：脸外 = 255
    mask_outer = cv2.bitwise_not(mask_face)
    return mask_outer

def generate_brow_mask(image_shape, landmarks, indices, scale_x=1.2, scale_y=1.5):
    """
    生成眉毛 mask（扁椭圆 / 拉长）
    """
    mask = np.zeros(image_shape[:2], dtype=np.uint8)
    pts = landmarks[indices].astype(np.int32)

    if pts.shape[0] < 3:
        return mask

    hull = cv2.convexHull(pts)

    # 计算中心
    cx = np.mean(hull[:, 0, 0])
    cy = np.mean(hull[:, 0, 1])

    # 缩放 hull（手动仿射）
    scaled = []
    for p in hull[:, 0, :]:
        x = cx + (p[0] - cx) * scale_x
        y = cy + (p[1] - cy) * scale_y
        scaled.append([int(x), int(y)])

    scaled = np.array(scaled, np.int32)
    cv2.fillConvexPoly(mask, scaled, 255)
    return mask

def process_single_image(image_path, facer, output_dir="output"):
    """
    处理单张图片的主流程。
    """
    # 1. 读取图片并运行关键点检测
    image = cv2.imread(image_path)
    result = facer.run(image)
    # 假设只处理检测到的第一张脸
    if len(result) == 0:
        print(f"未检测到人脸: {image_path}")
        return
    landmarks = result[0]['kps']  # 形状应为 (98, 2)

    # 2. 定义各部位的关键点索引 (需根据你的98点模型调整)
    # 以下索引为示例，请务必根据你的模型定义进行核对和修改
    PARTS_INDEX = {
        "Face_Outline": list(range(0, 32)),  # 脸部轮廓示例索引
        "Left_Eye": list(range(60, 68)),  # 左眼
        "Right_Eye": list(range(68, 76)),  # 右眼
        "Nose": list(range(51, 60)),  # 鼻子
        "Mouth": list(range(76, 96)),  # 嘴巴
        "Left_Brow" : list(range(33, 41)),
        "Right_Brow" : list(range(42, 50))
        # 你可以根据需要添加更多部位，如眉毛: list(range(33, 51))
    }

    # 3. 为每个部位生成遮罩
    masks = {}
    for part_name, indices in PARTS_INDEX.items():

        if part_name == "Face_Outline":
            mask = generate_face_outer_mask(image.shape, landmarks, indices)

        elif part_name in ["Left_Eye", "Right_Eye"]:
            mask = generate_eye_ellipse_mask(image.shape, landmarks, indices)
        elif part_name in ["Left_Brow", "Right_Brow"]:
            mask = generate_brow_mask(image.shape, landmarks, indices)
        else:
            mask = generate_part_mask(image.shape, landmarks, indices)

        masks[part_name] = mask
        # 可选：保存每个部位的遮罩为PNG以供检查
        # cv2.imwrite(os.path.join(output_dir, f"{part_name}.png"), mask)

    # 4. 生成PSD
    os.makedirs(output_dir, exist_ok=True)
    base_name = os.path.splitext(os.path.basename(image_path))[0]
    psd_path = os.path.join(output_dir, f"{base_name}_layers.psd")
    masks_to_psd(image_path, masks, psd_path)


if __name__ == "__main__":
    # 初始化你的关键点检测器
    facer = FaceAna()

    image_path = r"D:project_2025live2dtalking-head-anime-4-demo-maindemodataimageslambda_02.png"
    process_single_image(image_path, facer, output_dir="psd_output")

以上为个人经验，希望能给大家一个参考，也希望大家多多支持风君子博客。

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python生成psd文件实例

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以上为个人经验，希望能给大家一个参考，也希望大家多多支持风君子博客。 您可能感兴趣的文章: Python通过psd-tools解析PSD文件的实现 Python通过psd-tools解析PSD文件

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以上为个人经验，希望能给大家一个参考，也希望大家多多支持风君子博客。

您可能感兴趣的文章:

Python通过psd-tools解析PSD文件的实现

Python通过psd-tools解析PSD文件