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fix: 🐛 font fallback

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since I scoped the location for fonts the fallback
was not being used.. This commit fixes that.

Closes #152
This commit is contained in:
Mel Massadian
2024-03-07 06:12:04 +01:00
parent af2175a1fc
commit 9fccdee82d
4 changed files with 68 additions and 33 deletions
Download Patch File Download Diff File Expand all files Collapse all files
font.ttf → data/font.ttf
View File
nodes/generate.py
+4 -10
View File
@@ -2,7 +2,7 @@ import qrcode
from PIL import Image
from ..log import log
from ..utils import comfy_dir, pil2tensor
from ..utils import comfy_dir, font_path, pil2tensor
# class MtbExamples:
# """MTB Example Images"""
@@ -202,13 +202,14 @@ class TextToImage:
fonts = {}
def __init__(self):
# - This is executed when the graph is executed, we could conditionaly reload fonts there
# - This is executed when the graph is executed,
# - we could conditionaly reload fonts there
pass
@classmethod
def CACHE_FONTS(cls):
font_extensions = ["*.ttf", "*.otf", "*.woff", "*.woff2", "*.eot"]
fonts = []
fonts = [font_path]
for extension in font_extensions:
try:
@@ -219,13 +220,6 @@ class TextToImage:
except Exception as e:
log.error(f"Error during font caching: {e}")
if not fonts:
log.warn(
"> No fonts found in the comfy folder, place at least one font file somewhere in ComfyUI's hierarchy"
)
else:
log.debug(f"> Found {len(fonts)} fonts")
for font in fonts:
log.debug(f"Adding font {font}")
TextToImage.fonts[font.stem] = font.as_posix()
utils.py
+62 -23
View File
@@ -1,4 +1,13 @@
import contextlib, functools, math, os, shlex, shutil, socket, subprocess, sys, uuid
import contextlib
import functools
import math
import os
import shlex
import shutil
import socket
import subprocess
import sys
import uuid
from pathlib import Path
from typing import List, Optional, Union
@@ -77,7 +86,9 @@ def get_server_info():
base_url = args.listen
if base_url == "0.0.0.0":
log.debug("Server set to 0.0.0.0, we will try to resolve the host IP")
base_url = ip_checker.get_working_ip(f"http://{{}}:{args.port}/history")
base_url = ip_checker.get_working_ip(
f"http://{{}}:{args.port}/history"
)
log.debug(f"Setting ip to {base_url}")
return (base_url, args.port)
@@ -157,7 +168,9 @@ def run_command(cmd, ignored_lines_start=None):
try:
_run_command(shell_cmd, ignored_lines_start)
except subprocess.CalledProcessError as e:
print(f"Command failed with return code: {e.returncode}", file=sys.stderr)
print(
f"Command failed with return code: {e.returncode}", file=sys.stderr
)
print(e.stderr.strip(), file=sys.stderr)
except KeyboardInterrupt:
@@ -205,7 +218,13 @@ def import_install(package_name):
except Exception: # (ImportError, ModuleNotFoundError):
run_command(
[Path(sys.executable).as_posix(), "-m", "pip", "install", package_spec]
[
Path(sys.executable).as_posix(),
"-m",
"pip",
"install",
package_spec,
]
)
importlib.import_module(package_name)
@@ -233,7 +252,7 @@ output_dir = Path(folder_paths.output_directory)
styles_dir = comfy_dir / "styles"
session_id = str(uuid.uuid4())
# - Construct the path to the font file
font_path = here / "font.ttf"
font_path = here / "data" / "font.ttf"
# - Add extern folder to path
extern_root = here / "extern"
@@ -244,7 +263,7 @@ for pth in extern_root.iterdir():
# - Add the ComfyUI directory and custom nodes path to the sys.path list
add_path(comfy_dir)
add_path((comfy_dir / "custom_nodes"))
add_path(comfy_dir / "custom_nodes")
PIL_FILTER_MAP = {
"nearest": Image.Resampling.NEAREST,
@@ -268,7 +287,9 @@ def tensor2pil(image: torch.Tensor) -> List[Image.Image]:
return [
Image.fromarray(
np.clip(255.0 * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8)
np.clip(255.0 * image.cpu().numpy().squeeze(), 0, 255).astype(
np.uint8
)
)
]
@@ -277,7 +298,9 @@ def pil2tensor(image: Union[Image.Image, List[Image.Image]]) -> torch.Tensor:
if isinstance(image, list):
return torch.cat([pil2tensor(img) for img in image], dim=0)
return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
return torch.from_numpy(
np.array(image).astype(np.float32) / 255.0
).unsqueeze(0)
def np2tensor(img_np: Union[np.ndarray, List[np.ndarray]]) -> torch.Tensor:
@@ -295,23 +318,31 @@ def tensor2np(tensor: torch.Tensor) -> List[np.ndarray]:
out.extend(tensor2np(tensor[i]))
return out
return [np.clip(255.0 * tensor.cpu().numpy().squeeze(), 0, 255).astype(np.uint8)]
return [
np.clip(255.0 * tensor.cpu().numpy().squeeze(), 0, 255).astype(
np.uint8
)
]
def pad(img, left, right, top, bottom):
pad_width = np.array(((0, 0), (top, bottom), (left, right)))
print(f"pad_width: {pad_width}, shape: {pad_width.shape}") # Debugging line
print(
f"pad_width: {pad_width}, shape: {pad_width.shape}"
) # Debugging line
return np.pad(img, pad_width, mode="wrap")
def tiles_infer(tiles, ort_session, progress_callback=None):
"""Infer each tile with the given model. progress_callback will be called with
arguments : current tile idx and total tiles amount (used to show progress on
cursor in Blender)."""
cursor in Blender).
"""
out_channels = 3 # normal map RGB channels
tiles_nb = tiles.shape[0]
pred_tiles = np.empty((tiles_nb, out_channels, tiles.shape[2], tiles.shape[3]))
pred_tiles = np.empty(
(tiles_nb, out_channels, tiles.shape[2], tiles.shape[3])
)
for i in range(tiles_nb):
if progress_callback != None:
@@ -325,7 +356,6 @@ def tiles_infer(tiles, ort_session, progress_callback=None):
def generate_mask(tile_size, stride_size):
"""Generates a pyramidal-like mask. Used for mixing overlapping predicted tiles."""
tile_h, tile_w = tile_size
stride_h, stride_w = stride_size
ramp_h = tile_h - stride_h
@@ -364,8 +394,8 @@ def generate_mask(tile_size, stride_size):
def corner_mask(side_length):
"""Generates the corner part of the pyramidal-like mask.
Currently, only for square shapes."""
Currently, only for square shapes.
"""
corner = np.zeros([side_length, side_length])
for h in range(0, side_length):
@@ -401,8 +431,8 @@ def scaling_mask(side_length):
def tiles_merge(tiles, stride_size, img_size, paddings):
"""Merges the list of tiles into one image. img_size is the original size, before
padding."""
padding.
"""
_, tile_h, tile_w = tiles[0].shape
pad_left, pad_right, pad_top, pad_bottom = paddings
height = img_size[1] + pad_top + pad_bottom
@@ -435,7 +465,8 @@ def tiles_merge(tiles, stride_size, img_size, paddings):
def tiles_split(img, tile_size, stride_size):
"""Returns list of tiles from the given image and the padding used to fit the tiles
in it. Input image must have dimension C,H,W."""
in it. Input image must have dimension C,H,W.
"""
log.debug(f"Splitting img: tile {tile_size}, stride {stride_size} ")
tile_h, tile_w = tile_size
stride_h, stride_w = stride_size
@@ -492,7 +523,9 @@ def tiles_split(img, tile_size, stride_size):
# region MODEL Utilities
def download_antelopev2():
antelopev2_url = "https://drive.google.com/uc?id=18wEUfMNohBJ4K3Ly5wpTejPfDzp-8fI8"
antelopev2_url = (
"https://drive.google.com/uc?id=18wEUfMNohBJ4K3Ly5wpTejPfDzp-8fI8"
)
try:
import gdown
@@ -603,7 +636,10 @@ def apply_easing(value, easing_type):
return 1
p = 0.3
s = p / 4
return -(math.pow(2, 10 * (t - 1)) * math.sin((t - 1 - s) * (2 * math.pi) / p))
return -(
math.pow(2, 10 * (t - 1))
* math.sin((t - 1 - s) * (2 * math.pi) / p)
)
def easeOutElastic(t):
if t == 0:
@@ -624,10 +660,13 @@ def apply_easing(value, easing_type):
t = t * 2
if t < 1:
return -0.5 * (
math.pow(2, 10 * (t - 1)) * math.sin((t - 1 - s) * (2 * math.pi) / p)
math.pow(2, 10 * (t - 1))
* math.sin((t - 1 - s) * (2 * math.pi) / p)
)
return (
0.5 * math.pow(2, -10 * (t - 1)) * math.sin((t - 1 - s) * (2 * math.pi) / p)
0.5
* math.pow(2, -10 * (t - 1))
* math.sin((t - 1 - s) * (2 * math.pi) / p)
+ 1
)
web/mtb_widgets.js
+2
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@@ -20,6 +20,8 @@ import { log } from './comfy_shared.js'
const newTypes = [, /*'BOOL'*/ 'COLOR', 'BBOX']
const deprecated_nodes = {
// 'Animation Builder':
// 'Kept to avoid breaking older script but replaced by TimeEngine',
}
const withFont = (ctx, font, cb) => {