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Midjourney Imagine API 申请流程与使用详解 | 极客日志
Python Node.js AI
Midjourney Imagine API 申请流程与使用详解 本文档介绍 Midjourney Imagine API 的申请步骤及核心功能。涵盖文本生成图像、图像放大变换、垫图改写、多图融合、局部重绘及异步回调等场景。提供 Python 和 Node.js 代码示例，并说明流式输出配置方法，帮助开发者快速集成 AI 绘图能力。
SqlMaster 发布于 2026/4/7 更新于 2026/5/23 Midjourney Imagine API 申请及使用
Midjourney 是一款强大的 AI 绘图工具，只需输入关键词，就能在短短一两分钟内生成精美的图像。如今，它已在各个行业广泛应用。本文档主要介绍 Midjourney Imagine API 中 Imagine 操作的使用流程，利用它我们可以轻松通过文本生成所需的图像。
申请流程
要使用 Midjourney Imagine API，首先访问平台页面点击「Acquire」按钮，获取请求所需的凭证：
如果你尚未登录或注册，系统会自动跳转到登录页面。登录注册后会自动返回当前页面。首次申请时会有免费额度赠送，可以免费使用该 API。
基本使用
接下来就可以在界面上填写对应的内容：
第一次使用时，至少需要填写两个内容：一个是 authorization，直接在下拉列表中选择；另一个是 prompt，即图片描述内容。建议用英文描述，生成的图会更准确效果更好。这里我们用了示例内容 Lamborghini speeds inside a volcano，代表要画一个兰博基尼在火山飞驰。
右侧有对应的调用代码生成，你可以复制代码直接运行，也可以直接点击「Try」按钮进行测试。
主要请求参数说明：
prompt：图片描述词（支持自动翻译）。mode：生成模式，可选 fast/relax/turbo，默认 fast。timeout：超时时间（秒），超时会直接返回。translation：是否自动翻译非英文 prompt。split_images：是否将 2x2 结果拆分返回单张。action/image_id：对历史图片继续操作时需指定。callback_url：异步回调地址。
调用之后，返回结果如下：
{
"image_url" : "https://midjourney.cdn.acedata.cloud/attachments/..." ,
"image_width" : 1024 ,
"image_height" : 1024 ,
"image_id" : "1234197197067915365" ,
"raw_image_url"
:
"https://midjourney.cdn.acedata.cloud/attachments/..."
,
"raw_image_width"
:
2048
,
"raw_image_height"
:
2048
,
"progress"
:
100
,
"actions"
:
[
"upscale1"
,
"upscale2"
,
"upscale3"
,
"upscale4"
,
"reroll"
,
"variation1"
,
"variation2"
,
"variation3"
,
"variation4"
]
,
"task_id"
:
"1bae3bec-3ac4-4180-a148-74ee6cb68b98"
,
"success"
:
true
}
task_id：生成此图像任务的 ID，用于唯一标识此次任务。image_id：图片的唯一标识，下次需要对图片进行变换操作时需要传此参数。image_url：缩略图的 URL，直接打开即可查看生成的效果。image_width / image_height：缩略图的像素尺寸。raw_image_url：原图的 URL，比缩略图更高清，但加载速度稍慢。raw_image_width / raw_image_height：原图的像素尺寸。actions：可以对生成的图片进行的进一步操作列表。其中 upscale 代表放大，variation 代表变换。例如 upscale1 是对左上角第一张图片进行放大，variation3 是根据左下角第三张图片进行变换。 打开 image_url 或 raw_image_url 对应的链接，可以看到生成的 2x2 预览图。至此，第一次 API 调用完成。
图像放大与变换 接下来尝试针对当前生成的照片进行进一步操作。比如觉得右上角第二张的图片还不错，想进行微调，就可以将 action 填写为 variation2，同时传递 image_id：
{
"image_url" : "https://midjourney.cdn.acedata.cloud/attachments/..." ,
"image_id" : "1234201336543969401" ,
"actions" : [ "upscale1" , "upscale2" , "upscale3" , "upscale4" , "reroll" , "variation1" , "variation2" , "variation3" , "variation4" ] ,
"task_id" : "f4961620-1104-409f-9dc1-ba3ed15c2f4d" ,
"success" : true }
可以看到，针对上一张右上角的图片，再次得到了四张类似的照片。此时可以挑选其中一张进行精细化放大操作，比如选第四张，传入 action 为 upscale4，并通过 image_id 再次传入当前图像的 ID 即可。
注意：upscale 操作相比 variation 来说，Midjourney 的耗时通常会更短一些。
{
"image_url" : "https://midjourney.cdn.acedata.cloud/attachments/..." ,
"image_width" : 512 ,
"image_height" : 512 ,
"image_id" : "1234202545208033400" ,
"raw_image_url" : "https://midjourney.cdn.acedata.cloud/attachments/..." ,
"raw_image_width" : 1024 ,
"raw_image_height" : 1024 ,
"progress" : 100 ,
"actions" : [ "upscale_2x" , "upscale_4x" , "zoom_out_2x" , "zoom_out_1_5x" , "pan_left" , "pan_right" , "pan_up" , "pan_down" ] ,
"task_id" : "03f62b17-a6f1-4c8e-9b4d-1fc7bd5b1180" ,
"success" : true }
这样我们就成功得到了一张兰博基尼的照片。同时注意到 actions 里面又包含了几个可进行的操作：
upscale_2x：对画面放大 2 倍，得到 2 倍高清图。upscale_4x：对画面放大 4 倍，得到 4 倍高清图。zoom_out_2x：对画面进行缩小两倍操作（周围区域填充）。zoom_out_1_5x：对画面进行缩小 1.5 倍操作（周围区域填充）。pan_left/right/up/down：对画面进行左/右/上/下偏移操作。 可以继续按照上述流程传入对应的变换指令进行连续生图操作。
图像改写（垫图） 该 API 也支持图像改写，俗称垫图。我们可以输入一张图片 URL 以及需要改写的描述文字，API 就会返回改写后的图片。
注意：输入的图片 URL 需要是一张纯图片，不能是一个网页里展示一张图片，否则无法进行图像改写。建议使用图床来上传获取图片的 URL。
例如，这里有一张公路落日的图片，公路旁边有一些树木和楼房：
现在想在它的基础上改写成海滩旁边，同时放一辆汽车停在路边。构造如下的 prompt：
可以看到，prompt 的最开头是一个 HTTPS 开头的图片链接，然后接着加一个空格，后面跟上 prompt 文字的内容。这里还用了额外的一些高级参数，如 --iw 2 来调整图片的权重。
将如上内容作为一个整体，传递给 prompt 字段：
{
"image_url" : "https://midjourney.cdn.acedata.cloud/attachments/..." ,
"image_id" : "1234539663515975690" ,
"actions" : [ "upscale1" , "upscale2" , "upscale3" , "upscale4" , "reroll" , "variation1" , "variation2" , "variation3" , "variation4" ] ,
"task_id" : "24a79e8b-a79d-471a-aef7-089dc0627ee8" ,
"success" : true }
可以看到，在原来的图片整体风格和构图不变的前提下，整个场景变成了海滩旁边，同时公路上还出现了汽车，这就是 Prompt with Image。
图像融合 该 API 也支持图像融合，我们可以传入多张图片，以实现不同的图片融合效果。
比如说这里一共有两张图片，一张是一只玩具熊，另一张是一个电锯：
想把二者融合起来，让这只熊拿着这个电锯，怎么做呢？
https://i-blog.ZEEKLOGimg.cn/img_convert/c97448ef51e6b36bd026d72092abe548.png https://i-blog.ZEEKLOGimg.cn/img_convert/1d81aa82612a1f16e8f3ad41354af74f.png The bear is holding the chainsaw --iw2
可以发现，和 Image with Prompt 类似，将多张图片 URL 放在了 prompt 开头，并以空格分隔，最后再加上文字 prompt，将如上内容作为一个整体传递给 prompt 参数，运行效果如下：
{
"image_url" : "https://midjourney.cdn.acedata.cloud/attachments/..." ,
"image_id" : "1234547236830973972" ,
"actions" : [ "upscale1" , "upscale2" , "upscale3" , "upscale4" , "reroll" , "variation1" , "variation2" , "variation3" , "variation4" ] ,
"task_id" : "891f2645-ee15-4c7b-ac24-d98163c8e57e" ,
"success" : true }
注意：图片融合最多可以支持 5 个图片 URL 作为输入，也就是最多支持 5 张图片融合，输入格式同上。
局部变换 该 API 也支持图像的局部绘图功能，但只支持在上文内容下生成的图片。我们可以传入一张生成图片的唯一 ID，局部重绘的行为参数 action 以及需要重绘区域的掩码 mask，以实现在该掩码区域进行重绘。
首先需要获取该区域的掩码 mask，此 mask 是通过灰度图片进行 Base64 编码得来的。下面提供一些获取掩码的工具代码：
import sys
import os
from PySide6.QtWidgets import *
from PySide6.QtGui import QPainter, QMouseEvent, QPen, QColor, QImage
from PySide6.QtCore import Qt, QPoint
class DrawingWidget (QWidget ):
def __init__ (self, imagePath ):
super ().__init__()
self .setAttribute(Qt.WA_StaticContents)
self .background_image = QImage(imagePath)
imageSize = self .background_image.size() * 0.8
self .setFixedSize(imageSize)
self .foreground_image = QImage(self .size(), QImage.Format_ARGB32)
self .foreground_image.fill(Qt.transparent)
self .drawing = False
self .lastPoint = QPoint()
self .pen_color = QColor(255 , 255 , 255 , 255 )
self .pen_size = 50
def set_pen_size (self, size ):
self .pen_size = size
def mousePressEvent (self, event: QMouseEvent ):
if event.button() == Qt.LeftButton:
self .drawing = True
self .lastPoint = event.pos()
def mouseMoveEvent (self, event: QMouseEvent ):
if event.buttons() & Qt.LeftButton and self .drawing:
painter = QPainter(self .foreground_image)
painter.setRenderHint(QPainter.Antialiasing, True )
pen = QPen(self .pen_color, self .pen_size, Qt.SolidLine, Qt.RoundCap, Qt.RoundJoin)
painter.setPen(pen)
painter.drawLine(self .lastPoint, event.pos())
self .lastPoint = event.pos()
self .update()
def mouseReleaseEvent (self, event: QMouseEvent ):
if event.button() == Qt.LeftButton and self .drawing:
self .drawing = False
def paintEvent (self, event ):
canvasPainter = QPainter(self )
canvasPainter.drawImage(self .rect(), self .background_image, self .background_image.rect())
canvasPainter.drawImage(self .rect(), self .foreground_image, self .foreground_image.rect())
def save_image (self, path ):
self .foreground_image.save(path)
class MainWindow (QDialog ):
def __init__ (self, imagePath ):
super ().__init__()
self .setWindowTitle("mask tool" )
self .drawing_widget = DrawingWidget(imagePath)
self .currentPath = os.getcwd().replace("\\" , "/" )
self .tempPath = self .currentPath + "/temp.jpg"
self .projectPath = ""
self .setDone = False
def init_ui (self ):
layout = QVBoxLayout()
layout.addWidget(self .drawing_widget)
controls_layout = QHBoxLayout()
size_label = QLabel("pen size:" )
controls_layout.addWidget(size_label)
self .size_slider = QSlider(Qt.Horizontal)
self .size_slider.setMinimum(100 )
self .size_slider.setMaximum(400 )
self .size_slider.setValue(400 )
self .size_slider.valueChanged.connect(self .update_pen_size)
controls_layout.addWidget(self .size_slider)
self .lineEdit_addPromp = QLineEdit()
layout.addWidget(self .lineEdit_addPromp)
save_button = QPushButton("Start partial redrawing" )
save_button.clicked.connect(self .save_image)
controls_layout.addWidget(save_button)
dont_button = QPushButton("Cancel partial redraw" )
dont_button.clicked.connect(self .dont_image)
controls_layout.addWidget(dont_button)
layout.addLayout(controls_layout)
self .setLayout(layout)
def update_pen_size (self ):
size = self .size_slider.value()
self .drawing_widget.set_pen_size(size)
def save_image (self ):
tempImage = self .currentPath + "/temp.jpg"
self .drawing_widget.save_image(self .tempPath)
self .prompt = self .lineEdit_addPromp.text()
self .setDone = True
self .close()
def dont_image (self ):
self .setDone = False
self .close()
def closeEvent (self, event ):
if self .setDone:
pass
else :
self .setDone = False
event.accept()
if __name__ == '__main__' :
imagePath = "test.png"
app = QApplication(sys.argv)
mainWindow = MainWindow(imagePath)
mainWindow.init_ui()
mainWindow.exec ()
通过以上代码可以获得掩码图片。在这个过程中需要注意掩码图片必须与原图片一样的尺寸，然后掩码图片中白色的区域就是需要重绘的区域。下面展示猫图片需要重绘的掩码图片与原图的对比：
最后还需要将掩码图片转换为基于 Base64 的编码，接下来提供转换 Base64 编码的代码：
import cv2
import base64
image_path = 'temp.jpg'
gray_image = cv2.imread(image_path)
_, buffer = cv2.imencode('.jpg' , gray_image)
base64_encoded = base64.b64encode(buffer).decode('utf-8' )
with open ('grayscale_image_base64.txt' , 'w' ) as f:
f.write(base64_encoded)
print ("success!" )
注意：上述 Python 代码描述了 mask 的生成过程，如果您要将其对接到您的产品中，请根据其原理编写对应语言的代码。
通过以上代码，我们获得了需要重绘的掩码 mask。下面我们还需要将参数 action 设置为 variation_region，生成图片的 ID image_id（获取该参数参考上文的内容），以及传入对应的掩码 mask，其它参数信息如下：
action：对图片进行操作的行为，此处为 variation_region，表示对图片进行局部重绘。prompt：对图像进行局部重绘的描述词（可选参数）。image_id：图片的唯一标识，方便对图像进行局部重绘。mask：图片对应的掩码区域的 base64 编码（图片是上面 image_id 指定的）。 因此根据以上规则我们需要设置正确的参数，参数 prompt 是一个非必填参数，这里为了方便对比将掩码区域的 prompt 设置为 A cute cat，具体的参数设置如下图所示：
代码示例 可以发现，在页面右侧已经自动生成了各种语言的代码。部分代码示例如下：
CURL curl -X POST 'https://api.acedata.cloud/midjourney/imagine' \
-H 'accept: application/json' \
-H 'authorization: Bearer {token}' \
-H 'content-type: application/json' \
-d '{ "prompt": "A cute cat ", "action": "variation_region", "image_id": "1265875488702726144", "mask": "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}
Python import requests
url = "https://api.acedata.cloud/midjourney/imagine"
headers = {
"accept" : "application/json" ,
"authorization" : "Bearer {token}" ,
"content-type" : "application/json"
}
payload = {
"prompt" : "A cute cat " ,
"action" : "variation_region" ,
"image_id" : "1265875488702726144" ,
"mask" : 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}
Node.js const axios = require ("axios" );
const url = "https://api.acedata.cloud/midjourney/imagine" ;
const headers = {
"content-type" : "application/json" ,
accept : "application/x-ndjson" ,
authorization : "Bearer {token}" ,
};
const body = {
prompt : "a beautiful cat --v 6" ,
action : "generate" ,
};
axios.post (url, body, { headers : headers, responseType : "stream" })
.then ((response ) => {
console .log (response.status );
response.data .on ("data" , (chunk ) => {
console .log (chunk.toString ());
});
})
.catch ((error ) => {
console .error (error);
});
这些示例运行的结果都是相似的。请注意，流式输出结果中有一个称为 progress 的字段，表示生成进度，范围从 0 到 100。如果需要，您可以在页面上显示这些信息。
注意：当生成未完全完成时，actions 字段为空，表示无法对中间图像执行进一步处理操作。生成完成后，在生成过程中生成的 image_url 将被销毁。
此外，您可以通过指定 accept=application/x-ndjson 的请求头和 callback_url 的请求体，将流式结果与异步回调结合起来，然后 callback_url 可以接收到多个流式结果的 POST 请求。
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