carvekit/web/other/removebg.py

import io
import time
import zipfile

import requests
from PIL import Image, ImageColor

from carvekit.utils.image_utils import transparency_paste, add_margin
from carvekit.utils.mask_utils import extract_alpha_channel
from carvekit.web.responses.api import error_dict
from carvekit.api.interface import Interface


def process_remove_bg(
    interface: Interface, params, image, bg, is_json_or_www_encoded=False
):
    """
    Handles a request to the removebg api method

    Args:
        interface: CarveKit interface
        bg: background pil image
        is_json_or_www_encoded: is "json" or "x-www-form-urlencoded" content-type
        image: foreground pil image
        params: parameters
    """
    h, w = image.size
    if h < 2 or w < 2:
        return error_dict("Image is too small. Minimum size 2x2"), 400

    if "size" in params.keys():
        value = params["size"]
        if value == "preview" or value == "small" or value == "regular":
            image.thumbnail((625, 400), resample=3)  # 0.25 mp
        elif value == "medium":
            image.thumbnail((1504, 1000), resample=3)  # 1.5 mp
        elif value == "hd":
            image.thumbnail((2000, 2000), resample=3)  # 2.5 mp
        else:
            image.thumbnail((6250, 4000), resample=3)  # 25 mp

    roi_box = [0, 0, image.size[0], image.size[1]]
    if "type" in params.keys():
        value = params["type"]
        pass

    if "roi" in params.keys():
        value = params["roi"].split(" ")
        if len(value) == 4:
            for i, coord in enumerate(value):
                if "px" in coord:
                    coord = coord.replace("px", "")
                    try:
                        coord = int(coord)
                    except BaseException:
                        return (
                            error_dict(
                                "Error converting roi coordinate string to number!"
                            ),
                            400,
                        )
                    if coord < 0:
                        error_dict("Bad roi coordinate."), 400
                    if (i == 0 or i == 2) and coord > image.size[0]:
                        return (
                            error_dict(
                                "The roi coordinate cannot be larger than the image size."
                            ),
                            400,
                        )
                    elif (i == 1 or i == 3) and coord > image.size[1]:
                        return (
                            error_dict(
                                "The roi coordinate cannot be larger than the image size."
                            ),
                            400,
                        )
                    roi_box[i] = int(coord)
                elif "%" in coord:
                    coord = coord.replace("%", "")
                    try:
                        coord = int(coord)
                    except BaseException:
                        return (
                            error_dict(
                                "Error converting roi coordinate string to number!"
                            ),
                            400,
                        )
                    if coord > 100:
                        return (
                            error_dict("The coordinate cannot be more than 100%"),
                            400,
                        )
                    elif coord < 0:
                        return error_dict("Coordinate cannot be less than 0%"), 400
                    if i == 0 or i == 2:
                        coord = int(image.size[0] * coord / 100)
                    elif i == 1 or i == 3:
                        coord = int(image.size[1] * coord / 100)
                    roi_box[i] = coord
                else:
                    return error_dict("Something wrong with roi coordinates!"), 400

    new_image = image.copy()
    new_image = new_image.crop(roi_box)
    h, w = new_image.size
    if h < 2 or w < 2:
        return error_dict("Image is too small. Minimum size 2x2"), 400
    new_image = interface([new_image])[0]

    scaled = False
    if "scale" in params.keys() and params["scale"] != 100:
        value = params["scale"]
        new_image.thumbnail(
            (int(image.size[0] * value / 100), int(image.size[1] * value / 100)),
            resample=3,
        )
        scaled = True
    if "crop" in params.keys():
        value = params["crop"]
        if value:
            new_image = new_image.crop(new_image.getbbox())
            if "crop_margin" in params.keys():
                crop_margin = params["crop_margin"]
                if "px" in crop_margin:
                    crop_margin = crop_margin.replace("px", "")
                    crop_margin = abs(int(crop_margin))
                    if crop_margin > 500:
                        return (
                            error_dict(
                                "The crop_margin cannot be larger than the original image size."
                            ),
                            400,
                        )
                    new_image = add_margin(
                        new_image,
                        crop_margin,
                        crop_margin,
                        crop_margin,
                        crop_margin,
                        (0, 0, 0, 0),
                    )
                elif "%" in crop_margin:
                    crop_margin = crop_margin.replace("%", "")
                    crop_margin = int(crop_margin)
                    new_image = add_margin(
                        new_image,
                        int(new_image.size[1] * crop_margin / 100),
                        int(new_image.size[0] * crop_margin / 100),
                        int(new_image.size[1] * crop_margin / 100),
                        int(new_image.size[0] * crop_margin / 100),
                        (0, 0, 0, 0),
                    )
        else:
            if "position" in params.keys() and scaled is False:
                value = params["position"]
                if len(value) == 2:
                    new_image = transparency_paste(
                        Image.new("RGBA", image.size),
                        new_image,
                        (
                            int(image.size[0] * value[0] / 100),
                            int(image.size[1] * value[1] / 100),
                        ),
                    )
                else:
                    new_image = transparency_paste(
                        Image.new("RGBA", image.size), new_image, roi_box
                    )
            elif scaled is False:
                new_image = transparency_paste(
                    Image.new("RGBA", image.size), new_image, roi_box
                )

    if "channels" in params.keys():
        value = params["channels"]
        if value == "alpha":
            new_image = extract_alpha_channel(new_image)
        else:
            bg_changed = False
            if "bg_color" in params.keys():
                value = params["bg_color"]
                if len(value) > 0:
                    color = ImageColor.getcolor(value, "RGB")
                    bg = Image.new("RGBA", new_image.size, color)
                    bg = transparency_paste(bg, new_image, (0, 0))
                    new_image = bg.copy()
                    bg_changed = True
            if "bg_image_url" in params.keys() and bg_changed is False:
                value = params["bg_image_url"]
                if len(value) > 0:
                    try:
                        bg = Image.open(io.BytesIO(requests.get(value).content))
                    except BaseException:
                        return error_dict("Error download background image!"), 400
                    bg = bg.resize(new_image.size)
                    bg = bg.convert("RGBA")
                    bg = transparency_paste(bg, new_image, (0, 0))
                    new_image = bg.copy()
                    bg_changed = True
            if not is_json_or_www_encoded:
                if bg and bg_changed is False:
                    bg = bg.resize(new_image.size)
                    bg = bg.convert("RGBA")
                    bg = transparency_paste(bg, new_image, (0, 0))
                    new_image = bg.copy()
    if "format" in params.keys():
        value = params["format"]
        if value == "jpg":
            new_image = new_image.convert("RGB")
            img_io = io.BytesIO()
            new_image.save(img_io, "JPEG", quality=100)
            img_io.seek(0)
            return {"type": "jpg", "data": [img_io, new_image.size]}
        elif value == "zip":
            mask = extract_alpha_channel(new_image)
            mask_buff = io.BytesIO()
            mask.save(mask_buff, "PNG")
            mask_buff.seek(0)
            image_buff = io.BytesIO()
            image.save(image_buff, "JPEG")
            image_buff.seek(0)
            fileobj = io.BytesIO()
            with zipfile.ZipFile(fileobj, "w") as zip_file:
                zip_info = zipfile.ZipInfo(filename="color.jpg")
                zip_info.date_time = time.localtime(time.time())[:6]
                zip_info.compress_type = zipfile.ZIP_DEFLATED
                zip_file.writestr(zip_info, image_buff.getvalue())
                zip_info = zipfile.ZipInfo(filename="alpha.png")
                zip_info.date_time = time.localtime(time.time())[:6]
                zip_info.compress_type = zipfile.ZIP_DEFLATED
                zip_file.writestr(zip_info, mask_buff.getvalue())
            fileobj.seek(0)
            return {"type": "zip", "data": [fileobj.read(), new_image.size]}
        else:
            buff = io.BytesIO()
            new_image.save(buff, "PNG")
            buff.seek(0)
            return {"type": "png", "data": [buff, new_image.size]}
    return (
        error_dict(
            "Something wrong with request or http api. Please, open new issue on Github! This is error in "
            "code."
        ),
        400,
    )