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Add test pattern

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kijai 2023-11-05 15:19:19 +02:00
parent 179c462e9b
commit b4d2ea1350
1 changed files with 66 additions and 2 deletions
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68
nodes.py
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@ -1109,6 +1109,8 @@ class ImageConcanate:
"direction": (
[ 'right',
'down',
'left',
'up',
],
{
"default": 'right'
@ -1124,6 +1126,10 @@ class ImageConcanate:
row = torch.cat((image1, image2), dim=2)
elif direction == 'down':
row = torch.cat((image1, image2), dim=1)
elif direction == 'left':
row = torch.cat((image2, image1), dim=2)
elif direction == 'up':
row = torch.cat((image2, image1), dim=1)
return (row,)
class ImageGridComposite2x2:
@ -1172,6 +1178,62 @@ class ImageGridComposite3x3:
grid = torch.cat((top_row, mid_row, bottom_row), dim=1)
return (grid,)
import random
class ImageBatchTestPattern:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"batch_size": ("INT", {"default": 1,"min": 1, "max": 255, "step": 1}),
"start_from": ("INT", {"default": 1,"min": 1, "max": 255, "step": 1}),
"width": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
"height": ("INT", {"default": 512,"min": 16, "max": 4096, "step": 1}),
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "generatetestpattern"
CATEGORY = "KJNodes"
def generatetestpattern(self, batch_size, start_from, width, height):
out = []
# Generate the sequential numbers for each image
numbers = np.arange(batch_size)
# Create an image for each number
for i, number in enumerate(numbers):
# Create a black image with the number as a random color text
image = Image.new("RGB", (width, height), color=0)
draw = ImageDraw.Draw(image)
# Draw a border around the image
border_width = 10
border_color = (255, 255, 255) # white color
border_box = [(border_width, border_width), (width - border_width, height - border_width)]
draw.rectangle(border_box, fill=None, outline=border_color)
font_size = 255 # Choose the desired font size
font_path = "fonts\\TTNorms-Black.otf" #I don't know why relative path won't work otherwise...
font_path = os.path.join(script_dir, font_path)
# Generate a random color for the text
color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
font = ImageFont.truetype(font_path, font_size) # Replace "path_to_font_file.ttf" with the path to your font file
text_width = font_size
text_height = font_size
text_x = (width - text_width / 2) // 2
text_y = (height - text_height) // 2
draw.text((text_x, text_y), str(number + start_from), font=font, fill=color)
# Convert the image to a numpy array and normalize the pixel values
image = np.array(image).astype(np.float32) / 255.0
image = torch.from_numpy(image)[None,]
out.append(image)
return (torch.cat(out, dim=0),)
NODE_CLASS_MAPPINGS = {
"INTConstant": INTConstant,
"FloatConstant": FloatConstant,
@ -1197,7 +1259,8 @@ NODE_CLASS_MAPPINGS = {
"ReverseImageBatch": ReverseImageBatch,
"ImageGridComposite2x2": ImageGridComposite2x2,
"ImageGridComposite3x3": ImageGridComposite3x3,
"ImageConcanate": ImageConcanate
"ImageConcanate": ImageConcanate,
"ImageBatchTestPattern": ImageBatchTestPattern,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"INTConstant": "INT Constant",
@ -1223,5 +1286,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"ReverseImageBatch": "ReverseImageBatch",
"ImageGridComposite2x2": "ImageGridComposite2x2",
"ImageGridComposite3x3": "ImageGridComposite3x3",
"ImageConcanate": "ImageConcanate"
"ImageConcanate": "ImageConcanate",
"ImageBatchTestPattern": "ImageBatchTestPattern"
}