Image Editing và Inpainting

1from openai import OpenAI
2
3client = OpenAI()
4
5# Edit with DALL-E
6response = client.images.edit(
7    model="dall-e-2",
8    image=open("original.png", "rb"),
9    mask=open("mask.png", "rb"),  # White = area to edit
10    prompt="A beautiful garden with flowers",
11    n=1,
12    size="1024x1024"
13)
14
15edited_url = response.data[0].url

1from diffusers import StableDiffusionXLInpaintPipeline
2from PIL import Image
3import torch
4
5pipe = StableDiffusionXLInpaintPipeline.from_pretrained(
6    "stabilityai/stable-diffusion-xl-base-1.0",
7    torch_dtype=torch.float16
8)
9pipe = pipe.to("cuda")
10
11image = Image.open("photo.png").resize((1024, 1024))
12mask = Image.open("mask.png").resize((1024, 1024))
13
14result = pipe(
15    prompt="modern furniture, clean design",
16    image=image,
17    mask_image=mask,
18    guidance_scale=7.5,
19    num_inference_steps=30,
20    strength=0.9
21).images[0]
22
23result.save("edited.png")

1from PIL import Image, ImageDraw
2
3# Tao mask trang (area can edit)
4mask = Image.new("RGB", (1024, 1024), "black")
5draw = ImageDraw.Draw(mask)
6# Ve vung can edit mau trang
7draw.rectangle([200, 200, 800, 800], fill="white")
8mask.save("mask.png")

1# Segment Anything Model
2from segment_anything import SamPredictor, sam_model_registry
3
4sam = sam_model_registry["vit_h"](checkpoint="sam_vit_h.pth")
5predictor = SamPredictor(sam)
6
7predictor.set_image(image_array)
8
9# Click point to select object
10masks, scores, logits = predictor.predict(
11    point_coords=[[500, 500]],
12    point_labels=[1],  # 1 = foreground
13    multimask_output=True
14)

1from rembg import remove
2from PIL import Image
3
4# Remove background
5input_image = Image.open("photo.png")
6output = remove(input_image)
7output.save("no_background.png")
8
9# Replace background
10background = Image.open("new_bg.png").resize(output.size)
11background.paste(output, mask=output.split()[3])  # Use alpha channel
12background.save("new_photo.png")

1from diffusers import StableDiffusionUpscalePipeline
2
3upscaler = StableDiffusionUpscalePipeline.from_pretrained(
4    "stabilityai/stable-diffusion-x4-upscaler",
5    torch_dtype=torch.float16
6)
7upscaler = upscaler.to("cuda")
8
9low_res = Image.open("small_image.png")
10
11upscaled = upscaler(
12    prompt="high quality, detailed, sharp",
13    image=low_res
14).images[0]
15
16upscaled.save("upscaled_4x.png")

1# Mo rong hinh anh ra ngoai boundaries
2from PIL import Image
3
4original = Image.open("photo.png")
5w, h = original.size
6
7# Tao canvas lon hon
8canvas = Image.new("RGB", (w * 2, h), "white")
9canvas.paste(original, (w // 2, 0))
10
11# Tao mask cho phan can generate
12mask = Image.new("RGB", (w * 2, h), "white")
13mask.paste(Image.new("RGB", (w, h), "black"), (w // 2, 0))
14
15# Inpaint phan trang
16result = pipe(
17    prompt="seamless landscape extension, same style and lighting",
18    image=canvas,
19    mask_image=mask,
20    guidance_scale=7.5
21).images[0]

1import os
2from pathlib import Path
3
4def batch_edit(input_dir, output_dir, edit_fn):
5    Path(output_dir).mkdir(exist_ok=True)
6    
7    for img_path in Path(input_dir).glob("*.png"):
8        image = Image.open(img_path)
9        edited = edit_fn(image)
10        edited.save(f"{output_dir}/{img_path.name}")
11        print(f"Processed: {img_path.name}")
12
13# Batch background removal
14batch_edit("photos/", "no_bg/", lambda img: remove(img))