diff --git a/backend/app/routers/ai_tools.py b/backend/app/routers/ai_tools.py
index b99be59..29b7668 100644
--- a/backend/app/routers/ai_tools.py
+++ b/backend/app/routers/ai_tools.py
@@ -408,3 +408,154 @@ async def segment_install():
from app.services.sam_service import ensure_sam_installed, get_install_status
asyncio.create_task(ensure_sam_installed())
return get_install_status()
+
+
+# ─── Enhance ─────────────────────────────────────────────────────────────────
+
+import io as _io
+import numpy as _np
+import cv2 as _cv2
+from PIL import Image as _Image
+
+class EnhanceRequest(BaseModel):
+ image: str # base64
+ strength: float = 1.0
+
+
+def _enhance_image(image_bytes: bytes, strength: float) -> bytes:
+ """
+ Apply a chain of non-AI image enhancements, each blended with `strength` (0–1).
+
+ Steps:
+ 1. Auto white balance (gray-world)
+ 2. CLAHE on L channel of LAB colorspace
+ 3. Auto saturation boost in HSV (×1.15, clamped)
+ 4. Mild unsharp mask (gaussian sigma=1.0, delta weight=0.3)
+ """
+ strength = max(0.0, min(1.0, float(strength)))
+
+ # Decode to RGB numpy array
+ pil = _Image.open(_io.BytesIO(image_bytes)).convert("RGB")
+ orig = _np.array(pil, dtype=_np.float32) # H×W×3, float [0,255]
+
+ img = orig.copy()
+
+ # ── Step 1: Auto white balance (gray-world) ──────────────────────────────
+ mean_r = img[:, :, 0].mean()
+ mean_g = img[:, :, 1].mean()
+ mean_b = img[:, :, 2].mean()
+ overall_mean = (mean_r + mean_g + mean_b) / 3.0
+
+ def _scale(channel, channel_mean):
+ if channel_mean == 0:
+ return channel
+ return channel * (overall_mean / channel_mean)
+
+ wb = img.copy()
+ wb[:, :, 0] = _np.clip(_scale(img[:, :, 0], mean_r), 0, 255)
+ wb[:, :, 1] = _np.clip(_scale(img[:, :, 1], mean_g), 0, 255)
+ wb[:, :, 2] = _np.clip(_scale(img[:, :, 2], mean_b), 0, 255)
+
+ img = (orig + strength * (wb - orig)).clip(0, 255)
+
+ # ── Step 2: CLAHE on L channel (LAB) ────────────────────────────────────
+ img_u8 = img.astype(_np.uint8)
+ lab = _cv2.cvtColor(img_u8, _cv2.COLOR_RGB2LAB)
+ clahe = _cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
+ l_orig = lab[:, :, 0].copy()
+ lab[:, :, 0] = clahe.apply(l_orig)
+ # Blend L channel back using strength
+ lab_blended = lab.copy()
+ lab_blended[:, :, 0] = (l_orig + strength * (lab[:, :, 0].astype(_np.float32) - l_orig.astype(_np.float32))).clip(0, 255).astype(_np.uint8)
+ img = _cv2.cvtColor(lab_blended, _cv2.COLOR_LAB2RGB).astype(_np.float32)
+
+ # ── Step 3: Auto saturation boost (HSV, ×1.15) ──────────────────────────
+ img_u8 = img.astype(_np.uint8)
+ hsv = _cv2.cvtColor(img_u8, _cv2.COLOR_RGB2HSV).astype(_np.float32)
+ s_orig = hsv[:, :, 1].copy()
+ s_boosted = _np.clip(s_orig * 1.15, 0, 255)
+ hsv[:, :, 1] = s_orig + strength * (s_boosted - s_orig)
+ hsv = hsv.clip(0, 255).astype(_np.uint8)
+ img = _cv2.cvtColor(hsv, _cv2.COLOR_HSV2RGB).astype(_np.float32)
+
+ # ── Step 4: Mild unsharp mask (sigma=1.0, delta weight=0.3) ─────────────
+ img_u8 = img.astype(_np.uint8)
+ blurred = _cv2.GaussianBlur(img_u8, (0, 0), sigmaX=1.0)
+ sharpness_delta = img_u8.astype(_np.float32) - blurred.astype(_np.float32)
+ sharpened = img_u8.astype(_np.float32) + 0.3 * sharpness_delta * strength
+ img = sharpened.clip(0, 255)
+
+ # Encode result as PNG
+ result_pil = _Image.fromarray(img.astype(_np.uint8), mode="RGB")
+ buf = _io.BytesIO()
+ result_pil.save(buf, format="PNG")
+ return buf.getvalue()
+
+
+@router.post("/enhance")
+async def enhance(req: EnhanceRequest):
+ """
+ Non-AI image enhancement: auto white balance, CLAHE, saturation boost,
+ and unsharp mask. Each step is blended proportionally to `strength` (0–1).
+ """
+ try:
+ image_bytes = _decode(req.image)
+ result = await asyncio.get_event_loop().run_in_executor(
+ None, _enhance_image, image_bytes, req.strength
+ )
+ return {"result": _encode(result)}
+ except Exception as e:
+ import traceback; traceback.print_exc()
+ raise HTTPException(status_code=500, detail=str(e))
+
+
+# ─── Extract colors ───────────────────────────────────────────────────────────
+
+from sklearn.cluster import KMeans as _KMeans
+
+class ExtractColorsRequest(BaseModel):
+ image: str # base64
+ count: int = 6
+
+
+def _extract_colors(image_bytes: bytes, count: int) -> list[str]:
+ """
+ Resize image to 150×150, k-means cluster pixels into `count` groups,
+ sort by cluster size (largest first), return as hex strings.
+ """
+ count = max(1, min(count, 32))
+
+ pil = _Image.open(_io.BytesIO(image_bytes)).convert("RGB").resize((150, 150))
+ pixels = _np.array(pil, dtype=_np.float32).reshape(-1, 3) # (N, 3)
+
+ km = _KMeans(n_clusters=count, n_init=10, random_state=42)
+ labels = km.fit_predict(pixels)
+ centers = km.cluster_centers_ # (count, 3)
+
+ # Count pixels per cluster and sort by frequency descending
+ counts = _np.bincount(labels, minlength=count)
+ order = _np.argsort(-counts) # descending
+
+ hex_colors = []
+ for idx in order:
+ r, g, b = centers[idx].astype(int).clip(0, 255)
+ hex_colors.append(f"#{r:02x}{g:02x}{b:02x}")
+
+ return hex_colors
+
+
+@router.post("/extract-colors")
+async def extract_colors(req: ExtractColorsRequest):
+ """
+ Extract dominant colors from an image using k-means clustering.
+ Returns hex color strings sorted by frequency (most dominant first).
+ """
+ try:
+ image_bytes = _decode(req.image)
+ colors = await asyncio.get_event_loop().run_in_executor(
+ None, _extract_colors, image_bytes, req.count
+ )
+ return {"colors": colors}
+ except Exception as e:
+ import traceback; traceback.print_exc()
+ raise HTTPException(status_code=500, detail=str(e))
diff --git a/frontend/src/js/config-menu.js b/frontend/src/js/config-menu.js
index b19e667..9f592ed 100644
--- a/frontend/src/js/config-menu.js
+++ b/frontend/src/js/config-menu.js
@@ -140,6 +140,11 @@ const menuDefinition = [
shortcut: 'Ctrl+Y',
target: 'edit/redo.redo'
},
+ {
+ name: 'History Panel',
+ shortcut: 'Ctrl+H',
+ target: 'edit/history_panel.toggle'
+ },
{
divider: true
},
@@ -325,6 +330,15 @@ const menuDefinition = [
{
divider: true
},
+ {
+ name: 'Auto-Enhance',
+ ellipsis: true,
+ target: 'image/auto_enhance.auto_enhance'
+ },
+ {
+ name: 'Extract Color Palette',
+ target: 'image/color_palette.color_palette'
+ },
{
name: 'Remove Background (AI)',
ellipsis: true,
@@ -402,6 +416,10 @@ const menuDefinition = [
ellipsis: true,
target: 'layer/scale.scale'
},
+ {
+ name: 'Align to Canvas',
+ target: 'layer/align.align'
+ },
{
divider: true
},
@@ -840,6 +858,14 @@ const menuDefinition = [
{
name: 'Generate',
children: [
+ {
+ name: 'Add Text',
+ ellipsis: true,
+ target: 'text/text_presets.add_preset'
+ },
+ {
+ divider: true
+ },
{
name: 'Text → Image',
ellipsis: true,
diff --git a/frontend/src/js/modules/edit/history_panel.js b/frontend/src/js/modules/edit/history_panel.js
new file mode 100644
index 0000000..310d829
--- /dev/null
+++ b/frontend/src/js/modules/edit/history_panel.js
@@ -0,0 +1,145 @@
+/**
+ * History Panel — visual undo history timeline.
+ * Shows the last N actions as a clickable list. Click any item to undo/redo to that point.
+ * Docks as a floating panel on the right side of the screen.
+ *
+ * Menu target: edit/history_panel.toggle
+ */
+
+import app from './../../app.js';
+import alertify from './../../../../node_modules/alertifyjs/build/alertify.min.js';
+
+var instance = null;
+
+class Edit_history_panel_class {
+ constructor() {
+ if (instance) return instance;
+ instance = this;
+ this._panel = null;
+ this._interval = null;
+ }
+
+ toggle() {
+ if (this._panel) {
+ this._stop();
+ } else {
+ this._start();
+ }
+ }
+
+ _start() {
+ this._buildPanel();
+ this._render();
+ // Refresh whenever the history changes (poll lightly)
+ this._interval = setInterval(() => this._render(), 800);
+ }
+
+ _stop() {
+ if (this._interval) { clearInterval(this._interval); this._interval = null; }
+ if (this._panel) { this._panel.remove(); this._panel = null; }
+ }
+
+ _buildPanel() {
+ const panel = document.createElement('div');
+ panel.id = 'history_panel';
+ Object.assign(panel.style, {
+ position: 'fixed',
+ top: '60px',
+ right: '0',
+ width: '200px',
+ maxHeight: 'calc(100vh - 80px)',
+ overflowY: 'auto',
+ background: '#1a1a1a',
+ borderLeft: '1px solid #333',
+ borderBottom: '1px solid #333',
+ borderRadius: '0 0 0 10px',
+ zIndex: '8888',
+ fontFamily: 'sans-serif',
+ fontSize: '12px',
+ color: '#ccc',
+ boxShadow: '-4px 4px 16px rgba(0,0,0,0.4)',
+ userSelect: 'none',
+ });
+ panel.innerHTML = `
+
+ History
+ ×
+
+ `;
+ document.body.appendChild(panel);
+ this._panel = panel;
+ panel.querySelector('#hist-close').addEventListener('click', () => this._stop());
+ }
+
+ _render() {
+ if (!this._panel) return;
+ const list = this._panel.querySelector('#hist-list');
+ if (!list) return;
+
+ const history = app.State.action_history || [];
+ const idx = app.State.action_history_index ?? history.length;
+
+ if (history.length === 0) {
+ list.innerHTML = `No actions yet.
`;
+ return;
+ }
+
+ // Build rows newest-first
+ const rows = [];
+ // "Current state" row at top
+ const atTop = idx >= history.length;
+ rows.push(`
+ ${atTop ? '▶' : '○'}Current state
+
`);
+
+ for (let i = history.length - 1; i >= 0; i--) {
+ const action = history[i];
+ const isCurrent = (i === idx - 1);
+ const isFuture = (i >= idx);
+ const label = action.action_description || action.action_id || `Step ${i + 1}`;
+ rows.push(`
+ ${isCurrent ? '▶' : isFuture ? '○' : '·'}${_escHtml(label)}
+
`);
+ }
+ list.innerHTML = rows.join('');
+
+ // Wire clicks
+ list.querySelectorAll('[data-idx]').forEach(el => {
+ el.addEventListener('click', () => {
+ const target = parseInt(el.dataset.idx, 10);
+ this._jumpTo(target);
+ });
+ });
+ }
+
+ _jumpTo(targetIdx) {
+ const history = app.State.action_history || [];
+ const current = app.State.action_history_index ?? history.length;
+
+ if (targetIdx === current) return;
+
+ const steps = targetIdx - current;
+ if (steps > 0) {
+ for (let i = 0; i < steps; i++) app.State.redo_action();
+ } else {
+ for (let i = 0; i < Math.abs(steps); i++) app.State.undo_action();
+ }
+ this._render();
+ }
+}
+
+function _escHtml(s) {
+ return String(s).replace(/&/g,'&').replace(//g,'>');
+}
+
+export default Edit_history_panel_class;
diff --git a/frontend/src/js/modules/image/auto_enhance.js b/frontend/src/js/modules/image/auto_enhance.js
new file mode 100644
index 0000000..e8bd64d
--- /dev/null
+++ b/frontend/src/js/modules/image/auto_enhance.js
@@ -0,0 +1,124 @@
+/**
+ * Auto-Enhance — one-click smart photo improvement.
+ * Applies auto white balance, CLAHE contrast, saturation boost, and mild sharpening.
+ * Strength slider lets the user dial in how strong the effect is.
+ *
+ * Menu target: image/auto_enhance.auto_enhance
+ */
+
+import app from './../../app.js';
+import config from './../../config.js';
+import Dialog_class from './../../libs/popup.js';
+import alertify from './../../../../node_modules/alertifyjs/build/alertify.min.js';
+
+var instance = null;
+
+class Image_auto_enhance_class {
+ constructor() {
+ if (instance) return instance;
+ instance = this;
+ this.Dialog = new Dialog_class();
+ this.isProcessing = false;
+ }
+
+ async auto_enhance() {
+ if (!config.layer || config.layer.type !== 'image') {
+ alertify.error('Select an image layer first.');
+ return;
+ }
+ var _this = this;
+ this.Dialog.show({
+ title: 'Auto-Enhance',
+ params: [
+ {
+ title: '',
+ html: `
+ Automatically improves white balance, contrast, saturation, and sharpness.
+
`,
+ },
+ {
+ name: 'strength',
+ title: 'Strength:',
+ value: '100',
+ values: ['25', '50', '75', '100'],
+ type: 'select',
+ },
+ {
+ name: 'new_layer',
+ title: 'Keep original as separate layer:',
+ value: false,
+ },
+ ],
+ on_finish: async function (params) {
+ await _this._run(parseFloat(params.strength) / 100, params.new_layer);
+ },
+ });
+ }
+
+ async _run(strength, newLayer) {
+ if (this.isProcessing) return;
+ this.isProcessing = true;
+ alertify.message('Enhancing…', 0);
+
+ try {
+ const layer = config.layer;
+ const c = document.createElement('canvas');
+ c.width = layer.width_original; c.height = layer.height_original;
+ c.getContext('2d').drawImage(layer.link, 0, 0);
+ const imageB64 = c.toDataURL('image/png').split(',')[1];
+
+ const base = window.API_BASE_URL || '';
+ const r = await fetch(`${base}/api/enhance`, {
+ method: 'POST',
+ headers: { 'Content-Type': 'application/json' },
+ body: JSON.stringify({ image: imageB64, strength }),
+ });
+ if (!r.ok) throw new Error((await r.json().catch(() => ({}))).detail || 'Failed');
+ const data = await r.json();
+
+ const img = new Image();
+ img.onload = () => {
+ const rc = document.createElement('canvas');
+ rc.width = img.naturalWidth; rc.height = img.naturalHeight;
+ rc.getContext('2d').drawImage(img, 0, 0);
+
+ if (newLayer) {
+ app.State.do_action(
+ new app.Actions.Bundle_action('auto_enhance', 'Auto-Enhance', [
+ new app.Actions.Insert_layer_action({
+ name: layer.name + ' (Enhanced)',
+ type: 'image',
+ data: img.src,
+ x: layer.x, y: layer.y,
+ width: img.naturalWidth, height: img.naturalHeight,
+ width_original: img.naturalWidth, height_original: img.naturalHeight,
+ })
+ ])
+ );
+ } else {
+ app.State.do_action(
+ new app.Actions.Bundle_action('auto_enhance', 'Auto-Enhance', [
+ new app.Actions.Update_layer_image_action(rc)
+ ])
+ );
+ }
+ alertify.dismissAll();
+ alertify.success('Enhancement applied.');
+ this.isProcessing = false;
+ };
+ img.onerror = () => {
+ alertify.dismissAll();
+ alertify.error('Failed to load result.');
+ this.isProcessing = false;
+ };
+ img.src = 'data:image/png;base64,' + data.result;
+
+ } catch (err) {
+ alertify.dismissAll();
+ alertify.error('Auto-enhance failed: ' + (err.message || err));
+ this.isProcessing = false;
+ }
+ }
+}
+
+export default Image_auto_enhance_class;
diff --git a/frontend/src/js/modules/image/color_palette.js b/frontend/src/js/modules/image/color_palette.js
new file mode 100644
index 0000000..34b13d1
--- /dev/null
+++ b/frontend/src/js/modules/image/color_palette.js
@@ -0,0 +1,114 @@
+/**
+ * Color Palette Extractor — pull dominant colors from the current image layer.
+ * Shows a floating swatch panel; click a swatch to copy the hex or set as active color.
+ *
+ * Menu target: image/color_palette.color_palette
+ */
+
+import config from './../../config.js';
+import alertify from './../../../../node_modules/alertifyjs/build/alertify.min.js';
+
+var instance = null;
+
+class Image_color_palette_class {
+ constructor() {
+ if (instance) return instance;
+ instance = this;
+ this._panel = null;
+ }
+
+ async color_palette() {
+ if (!config.layer || config.layer.type !== 'image') {
+ alertify.error('Select an image layer first.');
+ return;
+ }
+ // Toggle: if panel already showing, close it
+ if (this._panel) { this._removePanel(); return; }
+
+ alertify.message('Extracting colors…', 0);
+ try {
+ const layer = config.layer;
+ const c = document.createElement('canvas');
+ c.width = layer.width_original; c.height = layer.height_original;
+ c.getContext('2d').drawImage(layer.link, 0, 0);
+ const imageB64 = c.toDataURL('image/png').split(',')[1];
+
+ const base = window.API_BASE_URL || '';
+ const r = await fetch(`${base}/api/extract-colors`, {
+ method: 'POST',
+ headers: { 'Content-Type': 'application/json' },
+ body: JSON.stringify({ image: imageB64, count: 8 }),
+ });
+ if (!r.ok) throw new Error((await r.json().catch(() => ({}))).detail || 'Failed');
+ const data = await r.json();
+
+ alertify.dismissAll();
+ this._showPanel(data.colors);
+ } catch (err) {
+ alertify.dismissAll();
+ alertify.error('Color extraction failed: ' + (err.message || err));
+ }
+ }
+
+ _showPanel(colors) {
+ this._removePanel();
+ const panel = document.createElement('div');
+ panel.id = 'color_palette_panel';
+ Object.assign(panel.style, {
+ position: 'fixed', bottom: '72px', right: '24px',
+ background: '#1a1a1a', border: '1px solid #3a3a3a',
+ borderRadius: '12px', padding: '12px 14px',
+ zIndex: '9998', boxShadow: '0 6px 24px rgba(0,0,0,0.6)',
+ fontFamily: 'sans-serif', fontSize: '12px', color: '#bbb',
+ userSelect: 'none', minWidth: '180px',
+ });
+
+ const swatchesHtml = colors.map(hex => `
+
+
`).join('');
+
+ panel.innerHTML = `
+
+ Image Palette
+ ×
+
+ ${swatchesHtml}
+
+ Click: copy hex · Shift+click: set color
`;
+
+ document.body.appendChild(panel);
+ this._panel = panel;
+
+ // Close button
+ panel.querySelector('#cp-close').addEventListener('click', () => this._removePanel());
+
+ // Swatch clicks
+ panel.querySelectorAll('[data-hex]').forEach(el => {
+ el.addEventListener('click', e => {
+ const hex = el.dataset.hex;
+ if (e.shiftKey) {
+ // Set as active color in miniPaint
+ config.COLOR = hex;
+ const copiedEl = panel.querySelector('#cp-copied');
+ if (copiedEl) copiedEl.textContent = `Active color set to ${hex}`;
+ } else {
+ navigator.clipboard.writeText(hex).catch(() => {});
+ const copiedEl = panel.querySelector('#cp-copied');
+ if (copiedEl) { copiedEl.textContent = `Copied ${hex}`; }
+ }
+ });
+ });
+ }
+
+ _removePanel() {
+ if (this._panel) { this._panel.remove(); this._panel = null; }
+ }
+}
+
+export default Image_color_palette_class;
diff --git a/frontend/src/js/modules/layer/align.js b/frontend/src/js/modules/layer/align.js
new file mode 100644
index 0000000..9e22fc2
--- /dev/null
+++ b/frontend/src/js/modules/layer/align.js
@@ -0,0 +1,114 @@
+/**
+ * Layer Alignment — align the active layer (or multiple selected layers) to the canvas.
+ * Operations: center H, center V, center both, align left/right/top/bottom, distribute.
+ * Shows as a compact floating toolbar.
+ *
+ * Menu target: layer/align.align
+ */
+
+import app from './../../app.js';
+import config from './../../config.js';
+import alertify from './../../../../node_modules/alertifyjs/build/alertify.min.js';
+
+var instance = null;
+
+const BUTTONS = [
+ { id: 'ch', label: '⬌', title: 'Center horizontally on canvas' },
+ { id: 'cv', label: '⬍', title: 'Center vertically on canvas' },
+ { id: 'cc', label: '⊕', title: 'Center on canvas' },
+ { id: 'sep', label: '|', title: '', sep: true },
+ { id: 'al', label: '⇤', title: 'Align left edge to canvas' },
+ { id: 'ar', label: '⇥', title: 'Align right edge to canvas' },
+ { id: 'at', label: '⇡', title: 'Align top edge to canvas' },
+ { id: 'ab', label: '⇣', title: 'Align bottom edge to canvas' },
+];
+
+class Layer_align_class {
+ constructor() {
+ if (instance) return instance;
+ instance = this;
+ this._panel = null;
+ }
+
+ align() {
+ if (this._panel) { this._removePanel(); return; }
+ this._mountPanel();
+ }
+
+ _mountPanel() {
+ this._removePanel();
+ const panel = document.createElement('div');
+ panel.id = 'align_panel';
+ Object.assign(panel.style, {
+ position: 'fixed',
+ top: '60px',
+ left: '50%',
+ transform: 'translateX(-50%)',
+ background: '#1a1a1a',
+ border: '1px solid #3a3a3a',
+ borderRadius: '10px',
+ padding: '7px 10px',
+ display: 'flex',
+ alignItems: 'center',
+ gap: '4px',
+ zIndex: '8889',
+ boxShadow: '0 4px 16px rgba(0,0,0,0.5)',
+ fontFamily: 'sans-serif',
+ userSelect: 'none',
+ });
+
+ const btnHtml = BUTTONS.map(b => {
+ if (b.sep) return `│`;
+ return ``;
+ }).join('');
+
+ panel.innerHTML = `
+ Align:
+ ${btnHtml}
+ ×`;
+
+ document.body.appendChild(panel);
+ this._panel = panel;
+
+ panel.querySelector('#align-close').addEventListener('click', () => this._removePanel());
+ panel.querySelectorAll('[data-align]').forEach(btn => {
+ btn.addEventListener('click', () => this._doAlign(btn.dataset.align));
+ });
+ }
+
+ _doAlign(op) {
+ const layer = config.layer;
+ if (!layer) { alertify.error('Select a layer first.'); return; }
+
+ const cw = config.WIDTH;
+ const ch = config.HEIGHT;
+ const lw = layer.width;
+ const lh = layer.height;
+
+ let newX = layer.x;
+ let newY = layer.y;
+
+ if (op === 'ch' || op === 'cc') newX = Math.round((cw - lw) / 2);
+ if (op === 'cv' || op === 'cc') newY = Math.round((ch - lh) / 2);
+ if (op === 'al') newX = 0;
+ if (op === 'ar') newX = cw - lw;
+ if (op === 'at') newY = 0;
+ if (op === 'ab') newY = ch - lh;
+
+ app.State.do_action(
+ new app.Actions.Update_layer_action(layer.id, { x: newX, y: newY })
+ );
+ }
+
+ _removePanel() {
+ if (this._panel) { this._panel.remove(); this._panel = null; }
+ }
+}
+
+export default Layer_align_class;
diff --git a/frontend/src/js/modules/text/text_presets.js b/frontend/src/js/modules/text/text_presets.js
new file mode 100644
index 0000000..c3c08a3
--- /dev/null
+++ b/frontend/src/js/modules/text/text_presets.js
@@ -0,0 +1,153 @@
+/**
+ * Text Presets — insert a styled text layer with one click.
+ * Presets: Heading, Subheading, Body, Caption, Quote, Bold Label.
+ * Each preset sets font, size, weight, color, and positions on canvas center.
+ *
+ * Menu target: text/text_presets.add_preset
+ */
+
+import app from './../../app.js';
+import config from './../../config.js';
+import Dialog_class from './../../libs/popup.js';
+import alertify from './../../../../node_modules/alertifyjs/build/alertify.min.js';
+
+var instance = null;
+
+const PRESETS = [
+ {
+ label: 'Heading',
+ sample: 'Add a heading',
+ family: 'Montserrat', size: 72, bold: true, italic: false,
+ fill_color: '#ffffff', stroke_size: 0,
+ },
+ {
+ label: 'Subheading',
+ sample: 'Add a subheading',
+ family: 'Montserrat', size: 44, bold: false, italic: false,
+ fill_color: '#e2e8f0', stroke_size: 0,
+ },
+ {
+ label: 'Body',
+ sample: 'Add body text',
+ family: 'Lato', size: 28, bold: false, italic: false,
+ fill_color: '#cbd5e1', stroke_size: 0,
+ },
+ {
+ label: 'Caption',
+ sample: 'Add a caption',
+ family: 'Lato', size: 20, bold: false, italic: true,
+ fill_color: '#94a3b8', stroke_size: 0,
+ },
+ {
+ label: 'Quote',
+ sample: '"Add a quote"',
+ family: 'Playfair Display', size: 36, bold: false, italic: true,
+ fill_color: '#f1f5f9', stroke_size: 0,
+ },
+ {
+ label: 'Bold Label',
+ sample: 'LABEL',
+ family: 'Oswald', size: 32, bold: true, italic: false,
+ fill_color: '#ffffff', stroke_size: 2, stroke_color: '#000000',
+ },
+];
+
+class Text_presets_class {
+ constructor() {
+ if (instance) return instance;
+ instance = this;
+ this.Dialog = new Dialog_class();
+ }
+
+ add_preset() {
+ var _this = this;
+ const labels = PRESETS.map(p => p.label);
+
+ this.Dialog.show({
+ title: 'Add Text',
+ params: [
+ {
+ title: '',
+ html: `
+ ${PRESETS.map((p, i) => `
+
+ ${p.sample}
+ ${p.family} · ${p.size}px
+
`).join('')}
+