ImageDrawLine¶
Documentation¶
- Class name:
ImageDrawLine
- Category:
image/draw
- Output node:
False
The ImageDrawLine node is designed to draw lines on images. It leverages the dimensions and color specifications provided to render a line between two points on an image, supporting customization through parameters like line thickness, color, and anti-aliasing settings.
Input types¶
Required¶
width
- Specifies the width of the image canvas, essential for determining the drawing area for the line.
- Comfy dtype:
INT
- Python dtype:
int
height
- Specifies the height of the image canvas, essential for determining the drawing area for the line.
- Comfy dtype:
INT
- Python dtype:
int
size
- Specifies the thickness of the line to be drawn, playing a significant role in the visual impact of the line on the image.
- Comfy dtype:
INT
- Python dtype:
int
start_x
- The starting x-coordinate for the line, marking one end of the line on the image.
- Comfy dtype:
FLOAT
- Python dtype:
float
start_y
- The starting y-coordinate for the line, working together with start_x to define the initial point of the line.
- Comfy dtype:
FLOAT
- Python dtype:
float
end_x
- The ending x-coordinate for the line, marking the other end of the line on the image.
- Comfy dtype:
FLOAT
- Python dtype:
float
end_y
- The ending y-coordinate for the line, working together with end_x to define the terminal point of the line.
- Comfy dtype:
FLOAT
- Python dtype:
float
red
- The red color component of the line, contributing to the final color of the line drawn on the image.
- Comfy dtype:
INT
- Python dtype:
int
green
- The green color component of the line, contributing to the final color of the line drawn on the image.
- Comfy dtype:
INT
- Python dtype:
int
blue
- The blue color component of the line, contributing to the final color of the line drawn on the image.
- Comfy dtype:
INT
- Python dtype:
int
alpha
- The alpha (transparency) component of the line's color, allowing for transparency effects in the line drawn on the image.
- Comfy dtype:
FLOAT
- Python dtype:
float
SSAA
- Super Sampling Anti-Aliasing factor for the line, enhancing the visual quality of the line by reducing jagged edges.
- Comfy dtype:
INT
- Python dtype:
int
method
- The method used for resizing the image after drawing the line, affecting the final appearance of the line.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
str
Output types¶
image
- Comfy dtype:
IMAGE
- The modified image with the line drawn on it, returned as a tensor.
- Python dtype:
torch.Tensor
- Comfy dtype:
Usage tips¶
- Infra type:
GPU
- Common nodes: unknown
Source code¶
class ImageDrawLine:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"width": ("INT", {
"default": 256,
"min": 1,
"step": 1
}),
"height": ("INT", {
"default": 256,
"min": 1,
"step": 1
}),
"size": ("INT", {
"default": 1,
"min": 1,
"step": 1
}),
"start_x": ("FLOAT", {
"default": 0.0,
"max": 1.0,
"step": 0.01
}),
"start_y": ("FLOAT", {
"default": 0.0,
"max": 1.0,
"step": 0.01
}),
"end_x": ("FLOAT", {
"default": 1.0,
"max": 1.0,
"step": 0.01
}),
"end_y": ("FLOAT", {
"default": 1.0,
"max": 1.0,
"step": 0.01
}),
"red": ("INT", {
"default": 255,
"max": 255,
"step": 1
}),
"green": ("INT", {
"default": 255,
"max": 255,
"step": 1
}),
"blue": ("INT", {
"default": 255,
"max": 255,
"step": 1
}),
"alpha": ("FLOAT", {
"default": 1.0,
"max": 1.0,
"step": 0.01
}),
"SSAA": ("INT", {
"default": 4,
"min": 1,
"max": 16,
"step": 1
}),
"method": (["lanczos", "bicubic", "hamming", "bilinear", "box", "nearest"],),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "node"
CATEGORY = "image/draw"
# noinspection PyPep8Naming, PyUnresolvedReferences
def node(self, width, height, size, start_x, start_y, end_x, end_y, red, green, blue, alpha, SSAA, method):
canvas = Image.new("RGBA", (width * SSAA, height * SSAA), (0, 0, 0, 0))
draw = ImageDraw.Draw(canvas)
draw.line(
[
(width * start_x * SSAA, height * start_y * SSAA),
(width * end_x * SSAA, height * end_y * SSAA)
],
(red, green, blue, int(alpha * 255)), size * SSAA
)
canvas = canvas.resize((width, height), get_sampler_by_name(method))
return (canvas.image_to_tensor().unsqueeze(0),)