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import os, io, re, random, string, tempfile
import spaces
import gradio as gr
from PIL import Image
# --- CONSTANTS ---
POTRACE_BIN = 'potrace'
UPM = 1000
CROP = 8
SIDEBEARING = 20
GLYPH_SCALE = 0.112
PRECISION = 1
HF_TOKEN = os.environ.get("HF_TOKEN", "")
DEFAULT_IMG_PROMPT = "Design a custom typeface that takes direct inspiration on the attached control image. The font should faithfully replicate the unique style of the reference."
# --- 6x6 MAPPINGS ---
MAP_UC = [['A','B','C','D','E','F'],['G','H','I','J','K','L'],['M','N','O','P','Q','R'],['S','T','U','V','W','X'],['Y','Z','Æ','Œ','Ø','ß'],['Ç','.',',',';','?','!']]
MAP_LC = [['a','b','c','d','e','f'],['g','h','i','j','k','l'],['m','n','o','p','q','r'],['s','t','u','v','w','x'],['y','z','æ','œ','ø','Ð'],['ç',':',"'",'"','«','<']]
MAP_PUNC = [['1','2','3','4','5','6'],['7','8','9','0','#','%'],['(','[','{','$','€','£'],['&','@','_','+','-','='],['*','/','^','°','→','—'],['`','´','ˆ','¨','˜','•']]
# --- PER-GRID BASELINE REFERENCES ---
BASELINE_REFS = {
0: ['H', 'I', 'E', 'A', 'B', 'D', 'F', 'L', 'M', 'N', 'P', 'R', 'T', 'U', 'V', 'X', 'Y', 'Z'],
1: ['n', 'm', 'u', 'x', 'h', 'i', 'l', 'k', 'r', 'v', 'w', 'z', 'a', 'e', 'o'],
2: ['1', '0', '2', '4', '7', '8', '9', '#', '%', '$', '£', '&', '@', '+', '='],
}
# --- SVG PROCESSING ---
def simplify_svg_path(d):
from fontTools.pens.recordingPen import RecordingPen
from fontTools.pens.svgPathPen import SVGPathPen
from fontTools.svgLib.path import parse_path
rec = RecordingPen()
parse_path(d, rec)
svg = SVGPathPen(None)
rec.replay(svg)
return re.sub(r"(\d+\.\d+)", lambda m: f"{float(m.group(1)):.{PRECISION}f}", svg.getCommands())
def get_char_path_rdp(pil_img, upscale=2):
import tempfile, subprocess
import cv2, numpy as np
rgb = np.array(pil_img.convert("RGB"))
black_mask = (
(rgb[:,:,0] < 80) &
(rgb[:,:,1] < 80) &
(rgb[:,:,2] < 80)
).astype(np.uint8) * 255
h, w = black_mask.shape
up = cv2.resize(black_mask, (w*upscale, h*upscale), interpolation=cv2.INTER_NEAREST)
with tempfile.NamedTemporaryFile(suffix='.pbm', delete=False) as f:
pbm = f.name
with tempfile.NamedTemporaryFile(suffix='.svg', delete=False) as f:
svg = f.name
Image.fromarray(cv2.flip(255-up, 0)).convert('1').save(pbm)
try:
subprocess.run([POTRACE_BIN, pbm, '-s', '-o', svg, '--alphamax', '0.9', '--opttolerance', '0.5', '--turdsize', '30'], check=True, capture_output=True)
except:
return ""
finally:
if os.path.exists(pbm):
os.unlink(pbm)
if not os.path.exists(svg):
return ""
with open(svg) as f:
content = f.read()
os.unlink(svg)
paths = re.findall(r'd="([^"]+)"', content)
return ' '.join(simplify_svg_path(p) for p in paths).strip() if paths else ""
# --- OTF CONSTRUCTION ---
MIRROR_MAP = {')': '(', ']': '[', '}': '{'}
ACCENT_MAP = {
'à':('a','`'),'è':('e','`'),'ì':('i','`'),'ò':('o','`'),'ù':('u','`'),
'À':('A','`'),'È':('E','`'),'Ì':('I','`'),'Ò':('O','`'),'Ù':('U','`'),
'á':('a','´'),'é':('e','´'),'í':('i','´'),'ó':('o','´'),'ú':('u','´'),
'Á':('A','´'),'É':('E','´'),'Í':('I','´'),'Ó':('O','´'),'Ú':('U','´'),
'â':('a','ˆ'),'ê':('e','ˆ'),'î':('i','ˆ'),'ô':('o','ˆ'),'û':('u','ˆ'),
'Â':('A','ˆ'),'Ê':('E','ˆ'),'Î':('I','ˆ'),'Ô':('O','ˆ'),'Û':('U','ˆ'),
'ä':('a','¨'),'ë':('e','¨'),'ï':('i','¨'),'ö':('o','¨'),'ü':('u','¨'),
'Ä':('A','¨'),'Ë':('E','¨'),'Ï':('I','¨'),'Ö':('O','¨'),'Ü':('U','¨'),
'ã':('a','˜'),'õ':('o','˜'),'ñ':('n','˜'),
'Ã':('A','˜'),'Õ':('O','˜'),'Ñ':('N','˜'),
}
def build_otf(images, font_name):
from fontTools.fontBuilder import FontBuilder
from fontTools.pens.t2CharStringPen import T2CharStringPen
from fontTools.pens.boundsPen import BoundsPen
from fontTools.pens.transformPen import TransformPen
from fontTools.pens.recordingPen import RecordingPen
from fontTools.misc.transform import Identity
from fontTools.svgLib.path import parse_path
from fontTools.cffLib import PrivateDict
from fontTools.ttLib import newTable
from fontTools.ttLib.tables import _k_e_r_n as _kern
import tempfile, subprocess, cv2, numpy as np
from PIL import Image, ImageDraw
all_maps = [MAP_UC, MAP_LC, MAP_PUNC]
glyph_data = {}
for idx, img in enumerate(images):
w, h = img.size
arr = np.array(img.convert("RGB"))
arr_up = cv2.resize(arr, (w*2, h*2), interpolation=cv2.INTER_CUBIC)
img_up = Image.fromarray(arr_up)
w2, h2 = img_up.size
cw, ch = w2//6, h2//6
scale = 800/ch
current_map = all_maps[idx]
for r in range(6):
for c in range(6):
char = current_map[r][c]
box = (c*cw, r*ch, (c+1)*cw, (r+1)*ch)
d = get_char_path_rdp(img_up.crop(box), upscale=1)
if not d:
continue
bp = BoundsPen(None)
try:
parse_path(d, bp)
except:
continue
if bp.bounds:
glyph_data[char] = {'d': d, 'b': bp.bounds, 'scale': scale, 'grid': idx}
# Computed baseline
baseline_per_grid = {}
for grid_idx in range(len(all_maps)):
chosen_ref = None
for ref_char in BASELINE_REFS.get(grid_idx, []):
if ref_char in glyph_data and glyph_data[ref_char].get('grid') == grid_idx:
gd = glyph_data[ref_char]
baseline_per_grid[grid_idx] = gd['b'][3] * gd['scale'] * GLYPH_SCALE
chosen_ref = ref_char
break
if chosen_ref is None:
baseline_per_grid[grid_idx] = baseline_per_grid.get(0, 0)
print(f"⚠️ Grid {grid_idx}: no reference glyph found, fallback = {baseline_per_grid[grid_idx]:.1f}")
else:
print(f"📐 Grid {grid_idx}: baseline = {baseline_per_grid[grid_idx]:.1f} (ref '{chosen_ref}')")
def get_baseline(char):
if char in glyph_data:
return baseline_per_grid.get(glyph_data[char]['grid'], baseline_per_grid.get(0, 0))
return baseline_per_grid.get(0, 0)
dummy = PrivateDict()
dummy.nominalWidthX = 0
cs = {".notdef": T2CharStringPen(600, None).getCharString(private=dummy)}
metrics = {".notdef": (600, 0)}
cmap, order = {}, [".notdef"]
cs["space"] = T2CharStringPen(300, None).getCharString(private=dummy)
metrics["space"] = (300, 0)
order.append("space")
cmap[32] = "space"
font_recordings = {}
font_bounds = {}
font_widths = {}
font_centers = {}
for char, data in glyph_data.items():
if len(char) != 1:
continue
b, s = data['b'], data['scale']
width = round((b[2]-b[0]) * s * GLYPH_SCALE + SIDEBEARING * 2)
tx = SIDEBEARING - b[0] * s * GLYPH_SCALE
ty = get_baseline(char)
transform = Identity.translate(tx, ty).scale(s * GLYPH_SCALE, -s * GLYPH_SCALE)
rec = RecordingPen()
parse_path(data['d'], TransformPen(rec, transform))
font_recordings[char] = rec.value
font_widths[char] = width
bp2 = BoundsPen(None)
rec2 = RecordingPen()
rec2.value = rec.value
rec2.replay(bp2)
bounds = bp2.bounds or (0, 0, width, 800)
font_bounds[char] = bounds
font_centers[char] = ((bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2)
pen = T2CharStringPen(width, None)
rec3 = RecordingPen()
rec3.value = rec.value
rec3.replay(pen)
glyph_name = f"glyph{ord(char)}"
cs[glyph_name] = pen.getCharString(private=dummy)
order.append(glyph_name)
cmap[ord(char)] = glyph_name
metrics[glyph_name] = (width, 0)
# Mirrors
for dst_char, src_char in MIRROR_MAP.items():
if src_char not in font_recordings:
continue
w = font_widths[src_char]
pen = T2CharStringPen(w, None)
flip = TransformPen(pen, (-1, 0, 0, 1, w, 0))
rec = RecordingPen()
rec.value = font_recordings[src_char]
rec.replay(flip)
gn = f"glyph{ord(dst_char)}"
cs[gn] = pen.getCharString(private=dummy)
order.append(gn)
cmap[ord(dst_char)] = gn
metrics[gn] = (w, 0)
if src_char in font_centers:
cx, cy = font_centers[src_char]
font_centers[dst_char] = (w - cx, cy)
# Accented
for dst_char, (base_char, accent_char) in ACCENT_MAP.items():
if base_char not in font_recordings or accent_char not in font_recordings:
continue
w = font_widths[base_char]
bb = font_bounds[base_char]
ab = font_bounds[accent_char]
dx = ((bb[0]+bb[2]) - (ab[0]+ab[2])) / 2
dy = bb[3] - ab[1] + 40
pen = T2CharStringPen(w, None)
rec1 = RecordingPen()
rec1.value = font_recordings[base_char]
rec1.replay(pen)
rec2 = RecordingPen()
rec2.value = font_recordings[accent_char]
rec2.replay(TransformPen(pen, (1, 0, 0, 1, dx, dy)))
gn = f"glyph{ord(dst_char)}"
cs[gn] = pen.getCharString(private=dummy)
order.append(gn)
cmap[ord(dst_char)] = gn
metrics[gn] = (w, 0)
if base_char in font_centers and accent_char in font_centers:
bx, by = font_centers[base_char]
ax, ay = font_centers[accent_char]
font_centers[dst_char] = (bx + dx, by + dy)
# Bracket mirrors
MIRROR_PAIRS = {'(': ')', '[': ']', '{': '}'}
for src_char, dst_char in MIRROR_PAIRS.items():
if src_char not in glyph_data:
continue
data = glyph_data[src_char]
b, s = data['b'], data['scale']
width = round((b[2]-b[0]) * s * GLYPH_SCALE + SIDEBEARING * 2)
pen = T2CharStringPen(width, None)
tx = SIDEBEARING + b[2] * s * GLYPH_SCALE
ty = get_baseline(src_char)
transform = Identity.translate(tx, ty).scale(-s * GLYPH_SCALE, -s * GLYPH_SCALE)
parse_path(data['d'], TransformPen(pen, transform))
glyph_name = f"glyph{ord(dst_char)}"
if glyph_name not in cs:
cs[glyph_name] = pen.getCharString(private=dummy)
order.append(glyph_name)
cmap[ord(dst_char)] = glyph_name
metrics[glyph_name] = (width, 0)
if src_char in font_centers:
cx, cy = font_centers[src_char]
font_centers[dst_char] = (width - cx, cy)
# Combining-accent aliases
ACCENT_ALIASES = {
'`': [0x0060, 0x0300], '´': [0x00B4, 0x0301],
'ˆ': [0x02C6, 0x0302], '¨': [0x00A8, 0x0308], '˜': [0x02DC, 0x0303],
}
for base_char, codepoints in ACCENT_ALIASES.items():
if base_char not in glyph_data:
continue
existing_glyph_name = f"glyph{ord(base_char)}"
if existing_glyph_name in cs:
for cp in codepoints[1:]:
if cp not in cmap:
cmap[cp] = existing_glyph_name
fb = FontBuilder(UPM, isTTF=False)
fb.setupGlyphOrder(order)
fb.setupCharacterMap(cmap)
fb.setupCFF(
font_name,
{"FullName": font_name, "FamilyName": font_name, "Weight": "Regular"},
cs,
{font_name: dummy}
)
fb.setupHorizontalMetrics(metrics)
fb.setupHorizontalHeader(ascent=REF["asc"], descent=REF["dsc"])
fb.setupNameTable({
"familyName": font_name,
"styleName": "Regular",
"uniqueFontIdentifier": f"{font_name}:Version 1.000",
"fullName": font_name,
"version": "Version 1.000",
"psName": font_name
})
fb.setupOS2(
sTypoAscender=REF["tAsc"],
sTypoDescender=REF["tDsc"],
sTypoLineGap=REF["tGap"],
usWinAscent=REF["wAsc"],
usWinDescent=REF["wDsc"],
sxHeight=REF["xH"],
sCapHeight=REF["cH"],
fsType=4,
fsSelection=64
)
fb.setupPost(italicAngle=0, underlinePosition=REF["ulP"], underlineThickness=REF["ulT"])
# -------------------------------------------------------------------------
# BUBBLE KERNING — pure vector, written to GPOS (no pair-count limit)
# -------------------------------------------------------------------------
try:
import numpy as np
from fontTools.otlLib.builder import buildValue, buildPairPosGlyphs
from fontTools.ttLib import newTable
from fontTools.ttLib.tables import otTables
# --- Parameters ---
BUBBLE_RADIUS = 10 # bubble radius in UPM, must be < SIDEBEARING (20)
N_SAMPLES = 300 # sampled points per contour
KERN_THRESHOLD = -2 # pairs with kern >= threshold are skipped (sub-UPM noise)
KERN_CAP = -280 # anti-collision floor
def sample_contour(recording, n=N_SAMPLES):
pts = []
def add_line(p0, p1):
d = ((p1[0]-p0[0])**2 + (p1[1]-p0[1])**2) ** 0.5
steps = max(1, int(d / 8))
for i in range(steps + 1):
t = i / steps
pts.append((p0[0] + t*(p1[0]-p0[0]),
p0[1] + t*(p1[1]-p0[1])))
def add_cubic(p0, p1, p2, p3):
d = ((p3[0]-p0[0])**2 + (p3[1]-p0[1])**2) ** 0.5
steps = max(4, int(d * 1.5 / 8))
for i in range(steps + 1):
t = i / steps
mt = 1.0 - t
bx = mt**3*p0[0] + 3*mt**2*t*p1[0] + 3*mt*t**2*p2[0] + t**3*p3[0]
by = mt**3*p0[1] + 3*mt**2*t*p1[1] + 3*mt*t**2*p2[1] + t**3*p3[1]
pts.append((bx, by))
cur = (0.0, 0.0)
start = (0.0, 0.0)
for op, args in recording:
if op == 'moveTo':
cur = args[0]; start = cur
elif op == 'lineTo':
add_line(cur, args[0]); cur = args[0]
elif op == 'curveTo':
add_cubic(cur, args[0], args[1], args[2]); cur = args[2]
elif op in ('endPath', 'closePath'):
if cur != start:
add_line(cur, start)
cur = start
if not pts:
return None
arr = np.array(pts, dtype=np.float32)
if len(arr) > n:
idx = np.round(np.linspace(0, len(arr)-1, n)).astype(int)
arr = arr[idx]
return arr
# Sampling
chars_available = [c for c in font_recordings if len(c) == 1]
contour_points = {}
for char in chars_available:
pts = sample_contour(font_recordings[char])
if pts is not None and len(pts) >= 2:
contour_points[char] = pts
print(f"📐 Contours sampled: {len(contour_points)} glyphs")
# All-to-all computation
diameter = BUBBLE_RADIUS * 2.0
gpos_pairs = {} # (glyph_name_L, glyph_name_R) -> kern_upm
for l_char in contour_points:
pts_L = contour_points[l_char]
adv_L = float(font_widths[l_char])
lg = f"glyph{ord(l_char)}"
if lg not in metrics:
continue
for r_char in contour_points:
rg = f"glyph{ord(r_char)}"
if rg not in metrics:
continue
pts_R_shifted = contour_points[r_char] + np.array([adv_L, 0.0], dtype=np.float32)
diff = pts_L[:, np.newaxis, :] - pts_R_shifted[np.newaxis, :, :]
min_dist = float(np.sqrt((diff**2).sum(axis=2)).min())
kern_upm = int(round(diameter - min_dist))
if l_char in ('A','V','W') and r_char in ('A','V','W'):
print(f" {l_char}->{r_char} : min_dist={min_dist:.1f} kern={kern_upm}")
if kern_upm < KERN_THRESHOLD:
gpos_pairs[(lg, rg)] = max(kern_upm, KERN_CAP)
print(f"✅ Bubble Kerning (vector): {len(gpos_pairs)} pairs")
if gpos_pairs:
val0 = buildValue({})
pairs_for_builder = {
(lg, rg): (buildValue({"XAdvance": kern}), val0)
for (lg, rg), kern in gpos_pairs.items()
}
glyph_map = fb.font.getReverseGlyphMap()
subtables = buildPairPosGlyphs(pairs_for_builder, glyph_map)
lookup = otTables.Lookup()
lookup.LookupType = 2
lookup.LookupFlag = 0
lookup.SubTableCount = len(subtables)
lookup.SubTable = subtables
lookup_list = otTables.LookupList()
lookup_list.Lookup = [lookup]
lookup_list.LookupCount = 1
feature_record = otTables.FeatureRecord()
feature_record.FeatureTag = "kern"
feature = otTables.Feature()
feature.LookupListIndex = [0]
feature.LookupCount = 1
feature_record.Feature = feature
lang_sys = otTables.DefaultLangSys()
lang_sys.ReqFeatureIndex = 0xFFFF
lang_sys.FeatureIndex = [0]
lang_sys.FeatureCount = 1
lang_sys.LookupOrderOffset = 0
script = otTables.Script()
script.DefaultLangSys = lang_sys
script.LangSysCount = 0
script.LangSysRecord = []
script_record = otTables.ScriptRecord()
script_record.ScriptTag = "DFLT"
script_record.Script = script
script_list = otTables.ScriptList()
script_list.ScriptRecord = [script_record]
script_list.ScriptCount = 1
feature_list = otTables.FeatureList()
feature_list.FeatureRecord = [feature_record]
feature_list.FeatureCount = 1
gpos_table = otTables.GPOS()
gpos_table.Version = 0x00010000
gpos_table.ScriptList = script_list
gpos_table.FeatureList = feature_list
gpos_table.LookupList = lookup_list
gpos = newTable("GPOS")
gpos.table = gpos_table
fb.font["GPOS"] = gpos
print(f"✅ GPOS written: {len(gpos_pairs)} kern pairs")
except Exception as e:
print(f"⚠️ Bubble Kerning failed: {e}")
import traceback
traceback.print_exc()
# --- Final OTF save ---
tmp_otf = f"/tmp/{font_name}.otf"
fb.save(tmp_otf)
with open(tmp_otf, "rb") as f:
data = f.read()
os.remove(tmp_otf)
return data
# --- REFERENCE METRICS (Helvetica LT Std Regular) ---
REF = {
"asc": 718, "dsc": -282, "tAsc": 718, "tDsc": -282, "tGap": 200,
"wAsc": 931, "wDsc": 225, "xH": 524, "cH": 718, "ulP": -75, "ulT": 50
}
# =============================================================================
# MODEL LOADING (module scope, once at Space startup)
# ZeroGPU: .to("cuda") here is fine, the real CUDA init is deferred by `spaces`.
# =============================================================================
import torch
from diffusers import Flux2KleinPipeline
from huggingface_hub import login
if HF_TOKEN:
login(token=HF_TOKEN)
print("🚀 Loading Flux.2-klein + LoRAs ...")
pipe = Flux2KleinPipeline.from_pretrained(
"black-forest-labs/FLUX.2-klein-base-4B",
torch_dtype=torch.bfloat16,
)
pipe.load_lora_weights("ChevalierJoseph/TYPOTOPIA_APP", weight_name="typotopiaMAJ.safetensors", adapter_name="uc")
pipe.load_lora_weights("ChevalierJoseph/TYPOTOPIA_APP", weight_name="typotopiaMIN.safetensors", adapter_name="lc")
pipe.load_lora_weights("ChevalierJoseph/TYPOTOPIA_APP", weight_name="typotopiaPONCT.safetensors", adapter_name="punc")
pipe.to("cuda")
print("✅ Model ready!")
# =============================================================================
# GPU INFERENCE — only the 3 FLUX passes run under @spaces.GPU
# duration = max GPU allocation per request (counts against the ZeroGPU quota).
# =============================================================================
@spaces.GPU(duration=180)
def run_pipeline(enhanced, input_img, seed):
gen = torch.Generator("cuda").manual_seed(int(seed))
pipe.set_adapters("uc")
img1 = pipe(
prompt=f"[typotopiaMAJ], {enhanced}",
image=input_img,
num_inference_steps=5,
guidance_scale=7 if input_img else 3.5,
height=1536, width=1536,
generator=gen,
).images[0]
pipe.set_adapters("lc")
img2 = pipe(
prompt="[typotopiaMIN], Design a custom lowercase typeface inspired by the attached control image.",
image=img1,
num_inference_steps=5,
guidance_scale=7,
height=1536, width=1536,
generator=gen,
).images[0]
pipe.set_adapters("punc")
img3 = pipe(
prompt="[typotopiaPONCT], Design a custom punctuation typeface inspired by the attached control image.",
image=img1,
num_inference_steps=5,
guidance_scale=7,
height=1536, width=1536,
generator=gen,
).images[0]
return img1, img2, img3
# =============================================================================
# ORCHESTRATOR + GRADIO UI
# =============================================================================
def _render_preview(otf_path, font_name):
try:
from PIL import Image, ImageDraw, ImageFont
sample = f"{font_name}\nAa Bb Cc 123\nThe quick brown fox"
img = Image.new("RGB", (1700, 620), "white")
draw = ImageDraw.Draw(img)
font = ImageFont.truetype(otf_path, 150)
draw.multiline_text((40, 30), sample, font=font, fill="black", spacing=30)
return img
except Exception as e:
print(f"⚠️ Preview failed: {e}")
return None
def generate(prompt, control_image, progress=gr.Progress(track_tqdm=True)):
seed = random.randint(0, 2**32 - 1)
input_img = None
prefixes = ["Vex","Aur","Kyr","Lux","Nox","Arc","Sol","Vel","Fen","Zor","Cal","Dex","Ora","Pax","Rux"]
suffixes = ["ra","is","on","us","ia","el","an","ix","em","or","al","en","ax","um","yr"]
font_name = random.choice(prefixes) + random.choice(suffixes)
if control_image is not None:
input_img = control_image.convert("RGB").resize((1536, 1536))
enhanced = DEFAULT_IMG_PROMPT
else:
if not (prompt and prompt.strip()):
raise gr.Error("Provide a prompt OR a control image.")
enhanced = prompt # raw user input, no refinement
# --- GPU: 3 FLUX passes ---
img1, img2, img3 = run_pipeline(enhanced, input_img, seed)
if not font_name:
font_name = "Font" + "".join(random.choices(string.ascii_uppercase, k=3))
# --- CPU: potrace vectorization + OTF build ---
otf_bytes = build_otf([img1, img2, img3], font_name)
out_dir = tempfile.mkdtemp()
otf_path = os.path.join(out_dir, f"{font_name}.otf")
with open(otf_path, "wb") as f:
f.write(otf_bytes)
gallery = [(img1, "Uppercase"), (img2, "Lowercase"), (img3, "Punctuation")]
preview = _render_preview(otf_path, font_name)
return gallery, preview, otf_path
# =============================================================================
# OPTIONAL CUSTOM TITLE FONT
# Drop your own font in the repo as one of these names and the hero title will
# use it (otherwise it falls back to the Helvetica/Archivo grotesque stack):
# title.otf / title.ttf / title.woff2 / title.woff (or under assets/)
# =============================================================================
def _load_title_font():
import base64
fmt = {"otf": "opentype", "ttf": "truetype", "woff": "woff", "woff2": "woff2"}
mime = {"otf": "font/otf", "ttf": "font/ttf", "woff": "font/woff", "woff2": "font/woff2"}
candidates = [
"title.otf", "title.ttf", "title.woff2", "title.woff",
"assets/title.otf", "assets/title.ttf", "assets/title.woff2", "assets/title.woff",
]
for path in candidates:
if os.path.exists(path):
ext = path.rsplit(".", 1)[-1].lower()
with open(path, "rb") as fh:
b64 = base64.b64encode(fh.read()).decode()
print(f"🔤 Title font: {path}")
face = (
"@font-face {"
"font-family: 'TitleFont';"
f"src: url(data:{mime[ext]};base64,{b64}) format('{fmt[ext]}');"
"font-weight: 100 900; font-style: normal; font-display: swap;}"
)
return face, "'TitleFont', 'Helvetica Neue', Helvetica, 'Archivo', Arial, sans-serif"
return "", "'Helvetica Neue', Helvetica, 'Archivo', Arial, sans-serif"
TITLE_FONT_FACE, TITLE_FAMILY = _load_title_font()
# =============================================================================
# THEME — International Typographic Style (light grey / black / violet)
# =============================================================================
THEME = gr.themes.Base(
primary_hue=gr.themes.colors.violet,
neutral_hue=gr.themes.colors.gray,
radius_size=gr.themes.sizes.radius_none,
font=["Helvetica Neue", "Helvetica", gr.themes.GoogleFont("Archivo"), "Arial", "sans-serif"],
font_mono=[gr.themes.GoogleFont("JetBrains Mono"), "ui-monospace", "monospace"],
).set(
body_background_fill="#ECECEC",
body_background_fill_dark="#ECECEC",
body_text_color="#000000",
body_text_color_dark="#000000",
body_text_color_subdued="#6B6B6B",
body_text_color_subdued_dark="#6B6B6B",
background_fill_primary="#FFFFFF",
background_fill_primary_dark="#FFFFFF",
background_fill_secondary="#F4F4F4",
background_fill_secondary_dark="#F4F4F4",
block_background_fill="#FFFFFF",
block_background_fill_dark="#FFFFFF",
block_border_color="#D8D8D8",
block_border_color_dark="#D8D8D8",
block_border_width="1px",
block_label_text_color="#000000",
block_label_text_color_dark="#000000",
block_label_background_fill="#FFFFFF",
block_label_background_fill_dark="#FFFFFF",
block_title_text_color="#000000",
block_title_text_color_dark="#000000",
block_radius="0px",
block_shadow="none",
block_shadow_dark="none",
input_background_fill="#FFFFFF",
input_background_fill_dark="#FFFFFF",
input_border_color="#000000",
input_border_color_dark="#000000",
input_border_color_focus="#5F2EEA",
input_border_color_focus_dark="#5F2EEA",
input_shadow="none",
input_shadow_dark="none",
input_shadow_focus="none",
input_shadow_focus_dark="none",
shadow_drop="none",
shadow_drop_lg="none",
button_primary_background_fill="#5F2EEA",
button_primary_background_fill_dark="#5F2EEA",
button_primary_background_fill_hover="#000000",
button_primary_background_fill_hover_dark="#000000",
button_primary_text_color="#FFFFFF",
button_primary_text_color_dark="#FFFFFF",
button_primary_border_color="#5F2EEA",
button_primary_border_color_dark="#5F2EEA",
button_secondary_background_fill="#FFFFFF",
button_secondary_background_fill_dark="#FFFFFF",
button_secondary_text_color="#000000",
button_secondary_text_color_dark="#000000",
button_secondary_border_color="#000000",
button_secondary_border_color_dark="#000000",
)
CSS = """
@import url('https://fonts.googleapis.com/css2?family=Archivo:wght@400;500;700;800&family=JetBrains+Mono:wght@400;500&display=swap');
:root {
--ink: #000000;
--paper: #FFFFFF;
--bg: #ECECEC;
--accent: #5F2EEA;
--grey: #6B6B6B;
--hairline: #D8D8D8;
--grotesk: 'Helvetica Neue', Helvetica, 'Archivo', Arial, sans-serif;
--mono: 'JetBrains Mono', ui-monospace, monospace;
}
.gradio-container {
max-width: 100% !important;
width: 100% !important;
margin: 0 !important;
padding-left: clamp(20px, 5vw, 72px) !important;
padding-right: clamp(20px, 5vw, 72px) !important;
background: var(--bg) !important;
}
/* Kill every radius and shadow — flat ink on paper */
.gradio-container *,
.gradio-container *::before,
.gradio-container *::after {
border-radius: 0 !important;
box-shadow: none !important;
text-shadow: none !important;
}
/* =========================================================================
MASTHEAD — wordmark left, tabular meta right, heavy rule below
========================================================================= */
#hero { padding: 22px 0 0; margin-bottom: 18px; }
#hero .masthead {
display: flex;
justify-content: space-between;
align-items: flex-end;
gap: 32px;
flex-wrap: wrap;
padding-bottom: 8px;
}
#hero h1 {
font-family: __TITLE_FAMILY__;
font-weight: 700;
font-size: clamp(44px, 8.5vw, 108px);
line-height: 0.82;
letter-spacing: -0.05em;
margin: 0;
color: var(--ink);
}
#hero h1 .stop { color: var(--accent); }
#hero .meta {
font-family: var(--grotesk);
font-size: 11px;
font-weight: 500;
text-transform: uppercase;
letter-spacing: 0.14em;
line-height: 1;
color: var(--ink);
min-width: 280px;
flex: 0 1 340px;
}
#hero .meta .row {
display: flex;
justify-content: space-between;
gap: 24px;
padding: 7px 0;
border-top: 1px solid var(--ink);
}
#hero .meta .row:first-child { border-top: none; }
#hero .meta .k { color: var(--grey); }
#hero .meta .v { text-align: right; }
/* Component labels */
.gradio-container label span,
.gradio-container .gr-check-radio label span {
font-family: var(--grotesk) !important;
text-transform: uppercase;
letter-spacing: 0.12em;
font-size: 10px !important;
font-weight: 500 !important;
color: var(--ink) !important;
}
/* Inputs: ink rules on paper */
.gradio-container textarea,
.gradio-container input[type='text'],
.gradio-container input[type='number'] {
font-family: var(--grotesk) !important;
font-size: 14px !important;
border: 1px solid var(--ink) !important;
background: var(--paper) !important;
}
.gradio-container textarea:focus,
.gradio-container input:focus {
border-color: var(--accent) !important;
outline: 2px solid var(--accent) !important;
outline-offset: -1px;
}
/* Primary CTA — violet plate, uppercase, no ornament */
.go-btn {
text-transform: uppercase !important;
letter-spacing: 0.22em !important;
font-family: var(--grotesk) !important;
font-weight: 700 !important;
font-size: 12px !important;
min-height: 48px !important;
border: none !important;
transition: background-color .12s ease !important;
}
.go-btn:hover { background: var(--ink) !important; }
.go-btn:focus-visible { outline: 2px solid var(--ink) !important; outline-offset: 2px; }
/* Compaction — single-screen fit */
#hero ~ .row, .gradio-container .gap { gap: 12px !important; }
.gradio-container .padded, .gradio-container .block { padding: 10px !important; }
.gradio-container .block { border-color: var(--hairline) !important; }
/* Control image dropzone — icon only, no instruction text */
#control-image .wrap {
font-size: 0 !important;
line-height: 0 !important;
gap: 0 !important;
}
#control-image .wrap .or { display: none !important; }
#control-image .wrap svg { width: 28px !important; height: 28px !important; }
/* Compact output blocks (download + preview) */
#otf-file { max-height: 84px !important; overflow: hidden; }
#otf-file .unpadded_box, #otf-file .empty { min-height: 56px !important; height: 56px !important; }
#preview-img .unpadded_box, #preview-img .empty { min-height: 96px !important; }
/* Progress — single violet gauge inside the grids block */
.gradio-container .progress-bar { background: var(--accent) !important; }
#grids { min-height: 240px; }
#grids .progress-text, #grids .progress-level-inner, #grids .meta-text, #grids .meta-text-center {
font-family: var(--mono) !important;
font-size: 12px !important;
color: var(--ink) !important;
}
@media (prefers-reduced-motion: reduce) {
.gradio-container * { transition: none !important; animation: none !important; }
}
footer { display: none !important; }
"""
# Inject the chosen title font-family + (optional) embedded @font-face.
CSS = CSS.replace("__TITLE_FAMILY__", TITLE_FAMILY) + TITLE_FONT_FACE
with gr.Blocks(title="Typotopia", theme=THEME, css=CSS) as demo:
gr.HTML(
"""
<div id="hero">
<div class="masthead">
<h1>Typotopia<span class="stop">.</span></h1>
<div class="meta">
<div class="row"><span class="k">Input</span><span class="v">Prompt / Control image</span></div>
<div class="row"><span class="k">Model</span><span class="v">FLUX.2-klein + LoRA</span></div>
<div class="row"><span class="k">Output</span><span class="v">OpenType · GPOS kerning</span></div>
</div>
</div>
</div>
"""
)
with gr.Row(equal_height=False):
with gr.Column(scale=1):
prompt = gr.Textbox(
label="Prompt",
placeholder="e.g. a bold geometric sans inspired by brutalist concrete signage",
lines=2,
)
control_image = gr.Image(label="Control image (optional)", type="pil", height=140, elem_id="control-image")
btn = gr.Button("Generate font", variant="primary", elem_classes=["go-btn"])
with gr.Column(scale=1):
otf_file = gr.File(label="Download .otf", height=56, elem_id="otf-file")
preview = gr.Image(label="Preview", type="pil", height=150, elem_id="preview-img")
gallery = gr.Gallery(label="Generated grids", columns=3, height=150, object_fit="contain", elem_id="grids")
btn.click(
generate,
inputs=[prompt, control_image],
outputs=[gallery, preview, otf_file],
show_progress="full",
show_progress_on=gallery,
)
if __name__ == "__main__":
demo.queue().launch() |