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Merge pull request #1 from mekinney/XYPlot-Footer

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Add core XYPlot Footer
This commit is contained in:
Mike Kinney
2025-05-13 06:51:23 -07:00
committed by GitHub
parent 4f31641da3 ce62fc73da
commit 419b7c985c
2 changed files with 89 additions and 11 deletions
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py/libs/xyplot.py
+88 -10
View File
@@ -8,6 +8,7 @@ from .log import log_node_warn
from ..modules.layer_diffuse import LayerDiffuse
from ..config import RESOURCES_DIR
from nodes import CLIPTextEncode
import pprint
try:
from comfy_extras.nodes_flux import FluxGuidance
except:
@@ -118,24 +119,32 @@ class easyXYPlot():
def calculate_background_dimensions(self):
border_size = int((self.max_width // 8) * 1.5) if self.y_type != "None" or self.x_type != "None" else 0
bg_width = self.num_cols * (self.max_width + self.grid_spacing) - self.grid_spacing + border_size * (
self.y_type != "None")
bg_height = self.num_rows * (self.max_height + self.grid_spacing) - self.grid_spacing + border_size * (
self.x_type != "None")
# Add space at the bottom of the image for common informaiton about the image
bg_height = bg_height + (border_size*2)
# print(f"Grid Size: width = {bg_width} height = {bg_height} border_size = {border_size}")
x_offset_initial = border_size if self.y_type != "None" else 0
y_offset = border_size if self.x_type != "None" else 0
return bg_width, bg_height, x_offset_initial, y_offset
def adjust_font_size(self, text, initial_font_size, label_width):
font = self.get_font(initial_font_size, self.custom_font)
text_width = font.getbbox(text)
# pprint.pp(f"Initial font size: {initial_font_size}, text: {text}, text_width: {text_width}")
if text_width and text_width[2]:
text_width = text_width[2]
scaling_factor = 0.9
if text_width > (label_width * scaling_factor):
# print(f"Adjusting font size from {initial_font_size} to fit text width {text_width} into label width {label_width} scaling_factor {scaling_factor}")
return int(initial_font_size * (label_width / text_width) * scaling_factor)
else:
return initial_font_size
@@ -144,15 +153,22 @@ class easyXYPlot():
_, _, width, height = d.textbbox((0, 0), text=text, font=font)
return width, height
def create_label(self, img, text, initial_font_size, is_x_label=True, max_font_size=70, min_font_size=10):
label_width = img.width if is_x_label else img.height
def create_label(self, img, text, initial_font_size, is_x_label=True, max_font_size=70, min_font_size=10, label_width=0, label_height=0):
# if the label_width is specified, leave it along. Otherwise do the old logic.
if label_width == 0:
label_width = img.width if is_x_label else img.height
text_lines = text.split('\n')
longest_line = max(text_lines, key=len)
# Adjust font size
font_size = self.adjust_font_size(text, initial_font_size, label_width)
font_size = self.adjust_font_size(longest_line, initial_font_size, label_width)
font_size = min(max_font_size, font_size) # Ensure font isn't too large
font_size = max(min_font_size, font_size) # Ensure font isn't too small
label_height = int(font_size * 1.5) if is_x_label else font_size
if label_height == 0:
label_height = int(font_size * 1.5) if is_x_label else font_size
label_bg = Image.new('RGBA', (label_width, label_height), color=(255, 255, 255, 0))
d = ImageDraw.Draw(label_bg)
@@ -166,7 +182,7 @@ class easyXYPlot():
text = text + '...'
# Compute text width and height for multi-line text
text_lines = text.split('\n')
text_widths, text_heights = zip(*[self.textsize(d, line, font=font) for line in text_lines])
max_text_width = max(text_widths)
total_text_height = sum(text_heights)
@@ -197,6 +213,9 @@ class easyXYPlot():
sd_version = get_sd_version(plot_image_vars['model'])
# print(f"sample_plot_image x_type: {self.x_type} y_type: {self.y_type} x_value: {x_value} y_value: {y_value}")
# 高级用法
if plot_image_vars["x_node_type"] == "advanced" or plot_image_vars["y_node_type"] == "advanced":
if self.x_type == "Seeds++ Batch" or self.y_type == "Seeds++ Batch":
@@ -347,15 +366,26 @@ class easyXYPlot():
# Lora
if self.x_type == "Lora" or self.y_type == "Lora":
# print(f"Lora: {x_value} {y_value}")
model = model if model is not None else plot_image_vars["model"]
clip = clip if clip is not None else plot_image_vars["clip"]
xy_values = x_value if self.x_type == "Lora" else y_value
lora_name, lora_model_strength, lora_clip_strength, _ = xy_values.split(",")
lora_stack = [{"lora_name": lora_name, "model": model, "clip" :clip, "model_strength": float(lora_model_strength), "clip_strength": float(lora_clip_strength)}]
# print(f"new_lora_stack: {new_lora_stack}")
# optional_lora_stack = plot_image_vars['lora_stack']
# print(f"optional_lora_stack: {optional_lora_stack}")
# if optional_lora_stack is not None and optional_lora_stack != []:
# for lora in optional_lora_stack:
# print(f"Lora: {lora}")
if 'lora_stack' in plot_image_vars:
lora_stack = lora_stack + plot_image_vars['lora_stack']
# print(f"new_lora_stack: {new_lora_stack}")
if lora_stack is not None and lora_stack != []:
for lora in lora_stack:
model, clip = self.easyCache.load_lora(lora)
@@ -464,6 +494,10 @@ class easyXYPlot():
plot_image_vars['negative_weight_interpretation'], w_max=1.0,
apply_to_pooled="enable", a1111_prompt_style=a1111_prompt_style, steps=steps)
# print(f"plotting image")
# if model is not None:
# pprint.pp(f"Model: {model}")
model = model if model is not None else plot_image_vars["model"]
vae = vae if vae is not None else plot_image_vars["vae"]
positive = positive if positive is not None else plot_image_vars["positive_cond"]
@@ -582,11 +616,10 @@ class easyXYPlot():
return self.latents_plot
def plot_images_and_labels(self):
# Calculate the background dimensions
def plot_images_and_labels(self, plot_image_vars):
bg_width, bg_height, x_offset_initial, y_offset = self.calculate_background_dimensions()
# Create the white background image
background = Image.new('RGBA', (int(bg_width), int(bg_height)), color=(255, 255, 255, 255))
output_image = []
@@ -618,4 +651,49 @@ class easyXYPlot():
y_offset += img.height + self.grid_spacing
return (self.sampler.pil2tensor(background), output_image)
# lookup used models in the image
common_label = ""
# Update to add a function to do the heavy lifting. Parameters are plot_image_vars name, label to use, names of the axis,
# pprint.pp(plot_image_vars)
labels = [
{"id": "ckpt_name", "id_desc": "ckpt"},
{"id": "vae_name", "id_desc": ''},
{"id": "sampler_name", "id_desc": "sampler"},
{"id": "scheduler", "id_desc": ''},
{"id": "steps", "id_desc": ''},
{"id": "seed", "id_desc": ''}
]
for item in labels:
common_label += self.add_common_label(item['id'], plot_image_vars, item['id_desc'])
common_label += f"\n"
if plot_image_vars['lora_stack'] is not None and plot_image_vars['lora_stack'] != []:
# print(f"lora_stack: {plot_image_vars['lora_stack']}")
for lora in plot_image_vars['lora_stack']:
# pprint.pp(lora)
lora_name = lora['lora_name']
lora_weight = lora['model_strength']
if lora_name is not None and len(lora_name) > 0 and lora_weight > 0:
common_label += f"LORA: {lora_name} weight: {lora_weight:.2f} \n"
common_label = common_label.strip()
if len(common_label) > 0:
label_height = background.height - y_offset
label_bg = self.create_label(background, common_label, int(48 * background.width / 512), label_width=background.width, label_height=label_height)
label_x = (background.width - label_bg.width) // 2
label_y = y_offset
# print(f"Adding common label: {common_label} x = {label_x} y = {label_y}")
background.alpha_composite(label_bg, (label_x, label_y))
return (self.sampler.pil2tensor(background), output_image)
def add_common_label(self, tag, plot_image_vars, description = ''):
label = ''
if description == '': description = tag
if plot_image_vars[tag] is not None and plot_image_vars[tag] != 'None':
label += f"{description}: {plot_image_vars[tag]} "
return label
py/nodes/samplers.py
+1 -1
View File
@@ -513,7 +513,7 @@ class samplerFull:
samp_samples = {"samples": latents_plot}
images, image_list = sampleXYplot.plot_images_and_labels()
images, image_list = sampleXYplot.plot_images_and_labels(plot_image_vars)
# Generate output_images
output_images = torch.stack([tensor.squeeze() for tensor in image_list])