Руководство по масковому inpainting

original image
+ mask image
+ edit prompt
= fully edited image

┌──────────────────────────┐
│      Opaque region        │
│   keep original intact    │
│                          │
│      ┌──────────┐        │
│      │transparent│       │
│      │→ flowers  │       │
│      └──────────┘        │
└──────────────────────────┘

Replace the cup in the transparent region with a bouquet of white tulips.
Keep everything else unchanged, preserving the original lighting,
camera angle, and photographic style.

Only modify the transparent region of the mask. Replace the person's top
with a plain red crew-neck cotton T-shirt. Keep the face, hair, body pose,
arms, background, composition, camera angle, lighting direction, and image
dimensions unchanged. The new shirt must fit the body naturally and
preserve the original photographic realism.

image[0]  = the main editing canvas
image[1…] = reference images
mask      = applies only to image[0]

import base64
from pathlib import Path
from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.apiyi.com/v1"
)

with open("input.png", "rb") as image_file, \
     open("mask.png", "rb") as mask_file:

    result = client.images.edit(
        model="gpt-image-2",
        image=image_file,
        mask=mask_file,
        prompt=(
            "Only modify the transparent region of the mask. "
            "Replace the white cup on the table with a bouquet of white tulips. "
            "Keep the table, background, camera angle, composition, and lighting unchanged. "
            "The bouquet should sit naturally where the cup was, casting shadows "
            "consistent with the original lighting."
        ),
        size="1536x1024",
        quality="high",
        output_format="png",
        n=1,
    )

image_bytes = base64.b64decode(result.data[0].b64_json)
Path("edited.png").write_bytes(image_bytes)
print("Saved: edited.png")

curl -s \
  -X POST "https://api.apiyi.com/v1/images/edits" \
  -H "Authorization: Bearer sk-your-api-key" \
  -F "model=gpt-image-2" \
  -F "image[][email protected];type=image/png" \
  -F "[email protected];type=image/png" \
  -F "prompt=Only modify the transparent region of the mask. Replace the cup on the table with a bouquet of white tulips. Keep everything else unchanged, preserving the original composition, lighting, and photographic realism." \
  -F "size=1536x1024" \
  -F "quality=high" \
  -F "output_format=png" \
  | jq -r '.data[0].b64_json' \
  | base64 --decode > edited.png

import fs from "fs";
import OpenAI, { toFile } from "openai";

const client = new OpenAI({
  apiKey: "sk-your-api-key",
  baseURL: "https://api.apiyi.com/v1",
});

const image = await toFile(
  fs.createReadStream("input.png"),
  "input.png",
  { type: "image/png" }
);

const mask = await toFile(
  fs.createReadStream("mask.png"),
  "mask.png",
  { type: "image/png" }
);

const result = await client.images.edit({
  model: "gpt-image-2",
  image,
  mask,
  prompt:
    "Only modify the transparent region of the mask. Replace the white cup " +
    "on the table with a bouquet of white tulips. Keep the background, " +
    "composition, camera angle, and lighting unchanged.",
  size: "1536x1024",
  quality: "high",
  output_format: "png",
});

const imageBuffer = Buffer.from(result.data[0].b64_json, "base64");
fs.writeFileSync("edited.png", imageBuffer);
console.log("Saved: edited.png");

from PIL import Image, ImageDraw

original = Image.open("input.png").convert("RGBA")

# Fully opaque by default: preserve everything
mask = Image.new("RGBA", original.size, (255, 255, 255, 255))

draw = ImageDraw.Draw(mask)

# Make the target region fully transparent: editable
# Coordinates: (left, top, right, bottom)
draw.rectangle((300, 250, 750, 800), fill=(0, 0, 0, 0))

mask.save("mask.png")
print("Mask size:", mask.size)

from PIL import Image

bw_mask = Image.open("mask_bw.png").convert("L")

rgba_mask = Image.new("RGBA", bw_mask.size, (255, 255, 255, 255))

# Black (0)   → alpha 0   → transparent → edit
# White (255) → alpha 255 → opaque      → keep
rgba_mask.putalpha(bw_mask)

rgba_mask.save("mask.png")

from PIL import Image

image = Image.open("input.png")
mask = Image.open("mask.png")

print("Mask format:", mask.format)
print("Mask mode:", mask.mode)
print("Mask size:", mask.size)

assert mask.format == "PNG", "Mask must be a PNG"
assert mask.mode in ("RGBA", "LA"), "Mask must contain an alpha channel"
assert image.size == mask.size, "Image and mask dimensions must match exactly"

alpha = mask.getchannel("A")
assert alpha.getextrema()[0] == 0, "Mask has no fully transparent editable region"

print("Mask check passed")

Bottom <img>     shows the original (visual reference only, not exported)
Top <canvas>     same pixel dimensions as the original, initially fully opaque
                 wherever the brush passes → pixels become transparent
Export canvas    → a valid alpha-mask PNG

const canvas = document.getElementById("mask-canvas");
const ctx = canvas.getContext("2d");

// 1. Canvas size = the image's natural pixel size (not its CSS display size);
//    matching dimensions come for free
canvas.width = image.naturalWidth;
canvas.height = image.naturalHeight;

// 2. Start fully opaque = preserve everything
ctx.fillStyle = "rgba(255, 255, 255, 1)";
ctx.fillRect(0, 0, canvas.width, canvas.height);

// 3. The key line: switch the brush to "erase" mode — strokes become transparent
ctx.globalCompositeOperation = "destination-out";
ctx.lineWidth = 40;          // brush size
ctx.lineCap = "round";
ctx.strokeStyle = "rgba(0, 0, 0, 1)";

// 4. Draw on pointer events (convert display coordinates back to natural pixels)
canvas.addEventListener("pointermove", (event) => {
  if (!drawing) return;
  const scaleX = canvas.width / canvas.clientWidth;
  const scaleY = canvas.height / canvas.clientHeight;
  ctx.lineTo(event.offsetX * scaleX, event.offsetY * scaleY);
  ctx.stroke();
});

// 5. Export: a PNG mask with an alpha channel, ready to upload
canvas.toBlob((blob) => {
  const formData = new FormData();
  formData.append("mask", blob, "mask.png");
  // POST to /v1/images/edits together with the image and prompt
}, "image/png");

User clicks an object            → SAM returns a pixel-accurate outline mask
User types "the cup on the left" → SAM 3 finds all instances matching the concept
Program dilates + feathers       → submit to /v1/images/edits

import base64
from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.apiyi.com/v1"
)

with open("person.png", "rb") as person, \
     open("clothes_reference.png", "rb") as clothes, \
     open("fabric_reference.png", "rb") as fabric, \
     open("mask.png", "rb") as mask:

    result = client.images.edit(
        model="gpt-image-2",
        image=[person, clothes, fabric],
        mask=mask,
        prompt=(
            "The first image is the subject to edit. "
            "Only modify the clothing inside the transparent mask region "
            "of the first image. Use the garment style from the second image "
            "and the fabric texture from the third image. Keep the face, "
            "hairstyle, pose, body proportions, background, and lighting "
            "of the first image unchanged."
        ),
        quality="high",
        size="1024x1536",
        output_format="png",
    )

with open("result.png", "wb") as output:
    output.write(base64.b64decode(result.data[0].b64_json))

from PIL import Image, ImageFilter

original = Image.open("input.png").convert("RGBA")
edited = Image.open("edited.png").convert("RGBA")
mask = Image.open("mask.png").convert("RGBA")

if edited.size != original.size:
    edited = edited.resize(original.size, Image.Resampling.LANCZOS)

# Original mask alpha: 0 = edit region, 255 = preserved region
alpha = mask.getchannel("A")

# Inverted: 255 = use edited result, 0 = use original
edit_area = alpha.point(lambda value: 255 - value)

# Slight feathering to avoid hard edges
edit_area = edit_area.filter(ImageFilter.GaussianBlur(radius=3))

final = Image.composite(edited, original, edit_area)
final.save("final.png")

Width and height must both be multiples of 16
Longest side no more than 3840px
Aspect ratio no more than 3:1
Total pixels at least 655,360
Total pixels no more than 8,294,400

result = client.images.edit(
    model="gpt-image-2",
    image=open("input.png", "rb"),
    mask=open("mask.png", "rb"),
    prompt="""
Only edit the transparent region of the mask.

Edit task:
Replace the white mug inside the transparent region with a bouquet
of white tulips.

Must preserve:
- Original composition
- Camera position and lens perspective
- Table surface and background
- Lighting direction and color temperature
- All people and objects outside the mask
- Realistic photographic style

Blending requirements:
The bouquet should sit naturally where the mug was, with shadows,
reflections, and contact points consistent with the scene lighting.
Do not add any other objects.
""",
    size="1536x1024",
    quality="high",
    output_format="png",
)