xinyun/ComfyUI-KJNodes
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Fix add overlay label

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kijai 2024-05-09 15:41:22 +03:00
parent 26fbf1f03d
commit 916241840a
1 changed files with 28 additions and 28 deletions
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56
nodes/image_nodes.py
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@ -422,36 +422,36 @@ ComfyUI/custom_nodes/ComfyUI-KJNodes/fonts
label_image = Image.new("RGB", (width, height), label_color) label_image = Image.new("RGB", (width, height), label_color)
pil_image = label_image pil_image = label_image
draw = ImageDraw.Draw(pil_image) draw = ImageDraw.Draw(pil_image)
font = ImageFont.truetype(font_path, font_size) font = ImageFont.truetype(font_path, font_size)
words = caption_text.split() words = caption_text.split()
lines = [] lines = []
current_line = [] current_line = []
current_line_width = 0 current_line_width = 0
for word in words: for word in words:
word_width = font.getbbox(word)[2] word_width = font.getbbox(word)[2]
if current_line_width + word_width <= width - 2 * text_x: if current_line_width + word_width <= width - 2 * text_x:
current_line.append(word) current_line.append(word)
current_line_width += word_width + font.getbbox(" ")[2] # Add space width current_line_width += word_width + font.getbbox(" ")[2] # Add space width
else: else:
lines.append(" ".join(current_line))
current_line = [word]
current_line_width = word_width
if current_line:
lines.append(" ".join(current_line)) lines.append(" ".join(current_line))
current_line = [word]
current_line_width = word_width
if current_line:
lines.append(" ".join(current_line))
y_offset = text_y
for line in lines:
try:
draw.text((text_x, y_offset), line, font=font, fill=font_color, features=['-liga'])
except:
draw.text((text_x, y_offset), line, font=font, fill=font_color)
y_offset += font_size # Move to the next line
y_offset = text_y processed_image = torch.from_numpy(np.array(pil_image).astype(np.float32) / 255.0).unsqueeze(0)
for line in lines:
try:
draw.text((text_x, y_offset), line, font=font, fill=font_color, features=['-liga'])
except:
draw.text((text_x, y_offset), line, font=font, fill=font_color)
y_offset += font_size # Move to the next line
processed_image = torch.from_numpy(np.array(pil_image).astype(np.float32) / 255.0).unsqueeze(0)
return processed_image return processed_image
if caption == "": if caption == "":