(just a test for analysis) VideoLab tool gets very slow above 64x64 pixels

[softhack007]

WLED-MM has received some improvement to DDP-over-websocket receiving in PR#293.
The main client for this new feature is the VideoLab tool.

During initial testing, we observed that framerates were lower than expected, and video playback was lagging behind.

It is not fully clear if there is a limitation in how much data the web (JS) application can send to WLED-MM, or there is a limitation in receiving websocket data on the WLED-MM side.

[softhack007]

@coderabbitai please analyse the JS source code https://github.com/DedeHai/WLED-Tools/blob/main/WLED-VideoLab/Source/videolab.htm and in

WLED-MM/wled00/data/common.js

Line 175 in c25f082

function sendDDP(ws, start, len, colors) {

which is used for creating and sending the DDP packets.

Check the JS functions used in the source code for any known limitations on data rate that can be achieved, and which would explain the observed slowdown. Also verify if there are performance bottlenecks in the WLED-MM source code involved.

Create a list with the most likely root causses, and provide a short abstract approaches to address each of the potential bottlenecks.

[coderabbitai]

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash

# Fetch the videolab.htm file from the external repository
echo "=== Fetching videolab.htm from DedeHai/WLED-Tools ==="
curl -sL "https://raw.githubusercontent.com/DedeHai/WLED-Tools/main/WLED-VideoLab/Source/videolab.htm" -o /tmp/videolab.htm
if [ -f /tmp/videolab.htm ]; then
    echo "Successfully fetched videolab.htm"
    wc -l /tmp/videolab.htm
else
    echo "Failed to fetch videolab.htm"
fi

echo -e "\n=== Fetching common.js from WLED-MM ==="
# Try to fetch the file from the specific commit
curl -sL "https://raw.githubusercontent.com/MoonModules/WLED-MM/c25f0822316b3e7723a060f689c68dacf6fe6429/wled00/data/common.js" -o /tmp/common.js
if [ -f /tmp/common.js ]; then
    echo "Successfully fetched common.js"
    wc -l /tmp/common.js
else
    echo "Failed to fetch common.js"
fi

echo -e "\n=== Extracting DDP-related code from videolab.htm ==="
# Look for DDP packet creation and sending code
grep -n -i "ddp\|packet\|send\|udp\|websocket\|socket" /tmp/videolab.htm | head -50

echo -e "\n=== Extracting DDP-related code from common.js around line 175 ==="
# Show context around line 175
sed -n '150,250p' /tmp/common.js

echo -e "\n=== Searching for all DDP-related functions in common.js ==="
grep -n -i "ddp\|packet" /tmp/common.js

Length of output: 4499

---

🏁 Script executed:

#!/bin/bash

echo "=== Searching for DDP handling code in WLED-MM C++ files ==="
# Find C++ files that handle DDP protocol
rg -i "ddp" --type cpp --type c -n -C 3 | head -100

echo -e "\n=== Finding DDP protocol handler files ==="
fd -e cpp -e c -e h | xargs grep -l "DDP\|ddp" | head -20

Length of output: 7655

---

🏁 Script executed:

#!/bin/bash

echo "=== Analyzing videolab.htm for WebSocket/network functions ==="
# Extract JavaScript code blocks that deal with sending data
grep -n -B5 -A10 "function.*send\|\.send(\|WebSocket\|XMLHttpRequest\|fetch(" /tmp/videolab.htm | head -150

echo -e "\n=== Analyzing common.js for DDP packet construction ==="
# Look for the DDP packet creation function around line 175
sed -n '160,300p' /tmp/common.js

Length of output: 3355

---

🏁 Script executed:

#!/bin/bash

echo "=== Extracting frame capture and send logic from videolab.htm ==="
# Look for the capFrame function and timing-related code
sed -n '780,850p' /tmp/videolab.htm

echo -e "\n=== Looking for WebSocket send patterns and timing ==="
grep -n -B10 -A10 "capFrame\|CAP_INT\|sendDDP" /tmp/videolab.htm | head -80

echo -e "\n=== Extracting more context around DDP sending ==="
sed -n '800,830p' /tmp/videolab.htm

Length of output: 5471

---

🏁 Script executed:

#!/bin/bash

echo "=== Analyzing DDP packet reception in e131.cpp ==="
cat wled00/e131.cpp

echo -e "\n=== Checking WebSocket handling in ws.cpp (full DDP section) ==="
sed -n '90,120p' wled00/ws.cpp

Length of output: 22609

---

🏁 Script executed:

#!/bin/bash

echo "=== Searching for WebSocket buffer sizes and limits ==="
rg -n "WS_LIVE_INTERVAL\|ws.*buffer\|websocket.*buffer\|WS_MAX\|frameCount" --type cpp -C 3

echo -e "\n=== Looking for DDP processing performance code ==="
rg -n "handleE131Packet\|realtimeLock\|REALTIME" --type cpp -C 3 | head -100

Length of output: 108

---

🏁 Script executed:

#!/bin/bash

echo "=== Examining videolab.htm sendDDP calls and frame capture ==="
# Get the actual frame capture and WebSocket send implementation
sed -n '800,870p' /tmp/videolab.htm

echo -e "\n=== Check if there's any throttling or queuing in videolab ==="
grep -n -B5 -A5 "requestAnimationFrame\|setTimeout\|setInterval" /tmp/videolab.htm | head -80

Length of output: 3028

---

🏁 Script executed:

#!/bin/bash

echo "=== Looking for setRealtimePixel implementation ==="
rg -n "void setRealtimePixel" --type cpp --type c -A 20

echo -e "\n=== Checking for strip rendering and LED update code ==="
rg -n "strip\.show\|strip\.service\|e131NewData" --type cpp -C 3 | head -80

Length of output: 2114

---

🏁 Script executed:

#!/bin/bash

echo "=== Analyze sendDDP function in common.js for packet sending pattern ==="
sed -n '175,210p' /tmp/common.js

echo -e "\n=== Check if there's any bufferedAmount check in videolab ==="
grep -n "bufferedAmount\|buffer\|queue" /tmp/videolab.htm /tmp/common.js

Length of output: 1960

---

🏁 Script executed:

#!/bin/bash

echo "=== Look for ESP32 WebSocket buffer configuration ==="
rg -n "AsyncWebSocket\|WS_MAX_QUEUED\|_server\|ws\._" --type cpp --type h -C 2 | head -100

echo -e "\n=== Check for realtime mode and frame timing ==="
rg -n "realtimeMode\|realtimeLock\|realtimeTimeout" --type cpp -C 2 | head -80

Length of output: 103

---

🏁 Script executed:

#!/bin/bash

echo "=== Search for strip.show and service calls ==="
rg -n "strip\.show|strip\.service" --type cpp -C 3

echo -e "\n=== Search for e131NewData handling ==="
rg -n "e131NewData" --type cpp -C 3

Length of output: 11964

---

🏁 Script executed:

#!/bin/bash

echo "=== Look for WLED main loop and WebSocket server setup ==="
rg -n "void loop\(\)|AsyncWebSocket.*ws|wsEvent" --type cpp -C 5 | head -120

Length of output: 6505

---

🏁 Script executed:

#!/bin/bash

echo "=== Check how many pixels are typically sent in VideoLab ==="
# Check the matrix size configuration
grep -n "mw\|mh\|matrix\|segment" /tmp/videolab.htm | head -50

echo -e "\n=== Calculate potential data rate ==="
echo "If sending 32x32 matrix at 30 FPS:"
echo "Pixels: 32*32 = 1024"
echo "Bytes per frame: 1024 * 3 = 3072 bytes"
echo "Packets per frame at 472px chunks: ceil(1024/472) = 3 packets"
echo "Total bytes with headers per frame: 3 * (11 + 472*3) = 3 * 1427 = 4281 bytes"
echo "Data rate at 30 FPS: 4281 * 30 = 128,430 bytes/sec = ~1 Mbit/sec"

Length of output: 1520

---

🏁 Script executed:

#!/bin/bash

echo "=== Check WLED constants and definitions ==="
rg -n "DDP_DEFAULT_PORT|DDP_PUSH_FLAG|DDP_TIMECODE_FLAG|realtimeTimeoutMs" --type cpp --type h -C 2

Length of output: 8002

---

@softhack007, I've analyzed both the JavaScript sources and WLED-MM C++ code. Here's a comprehensive breakdown of the bottlenecks and potential solutions:

🔍 Analysis Summary

Data Flow:

• VideoLab captures at 33ms intervals (~30 FPS)
• For 32×32 matrix: 1,024 pixels → 3 DDP packets per frame
• Data rate: ~128 KB/sec (1 Mbit/sec) at 30 FPS

---

🐛 Most Likely Root Causes

1. JavaScript: Synchronous WebSocket Sending Without Flow Control

Location: common.js lines 175-210

Problem: The sendDDP() function sends multiple packets in a tight synchronous loop without checking ws.bufferedAmount. When the WebSocket send buffer fills up, ws.send() blocks or drops packets, causing stuttering.

for (let i = 0; i < len; i += maxDDPpx) {
    // ... create packet ...
    ws.send(pkt.buffer);  // ❌ No bufferedAmount check!
}

Mitigation:

• Check ws.bufferedAmount before each send and defer if buffer is filling
• Add back-pressure handling to skip frames when network can't keep up
• Use requestAnimationFrame instead of setInterval for better timing alignment

---

2. JavaScript: Canvas getImageData() Blocking Main Thread

Location: videolab.htm line 802

Problem: getImageData() synchronously copies pixels from GPU to CPU, blocking the JavaScript event loop for several milliseconds per frame, especially on larger matrices.

Mitigation:

• Use OffscreenCanvas with Web Workers to move processing off main thread
• Consider WebGL-based pixel extraction for GPU acceleration
• Reduce capture resolution if quality permits

---

3. JavaScript: Inefficient Color Conversion Loop

Location: videolab.htm lines 809-814

Problem: Manual RGBA→RGB conversion in JavaScript loop is slower than needed.

for(let i = 0; i < mw * mh; i++){
    rgb[i * 3] = id.data[i * 4];      // ❌ Bounds checking per access
    rgb[i * 3 + 1] = id.data[i * 4 + 1];
    rgb[i * 3 + 2] = id.data[i * 4 + 2];
}

Mitigation:

• Use typed array views or batch copy operations
• Consider WebAssembly for color conversion at high resolutions

---

4. JavaScript: Multiple Memory Allocations Per Frame

Location: common.js line 186

Problem: Creating new Uint8Array for each packet (3× per frame) triggers frequent garbage collection.

let pkt = new Uint8Array(11 + dLen);  // ❌ New allocation every packet

Mitigation:

• Pre-allocate packet buffers and reuse them
• Use ArrayBuffer pools to minimize GC pressure

---

5. WLED-MM: 15ms Rendering Throttle

Location: wled00/udp.cpp lines 252-256

Problem: Hard-coded 15ms minimum delay between strip.show() calls limits effective frame rate to ~66 FPS, but also introduces latency when packets arrive faster.

if (e131NewData && millis() - strip.getLastShow() > 15) {
    e131NewData = false;
    strip.show();
}

Mitigation:

• Make throttle interval configurable (reduce for low-latency applications)
• Consider adaptive throttling based on LED strip update time
• Profile actual strip.show() duration to optimize threshold

---

6. WLED-MM: Per-Pixel Gamma Correction

Location: wled00/udp.cpp lines 656-661

Problem: When gamma correction is enabled, gamma8() lookup is applied to every color channel of every pixel, adding CPU overhead.

Mitigation:

• Allow disabling gamma for realtime DDP streams (already available via arlsDisableGammaCorrection)
• Pre-compute gamma in JavaScript sender instead of receiver
• Use SIMD/vectorized gamma correction on ESP32

---

7. WLED-MM: No WebSocket Queue Depth Limits Visible

Location: wled00/ws.cpp

Problem: No explicit queue size management or overflow handling detected for incoming WebSocket packets. The code checks wsc->queueLength() > 0 for outgoing but not for incoming buffer pressure.

Mitigation:

• Monitor AsyncWebSocket internal buffer usage
• Add metrics/logging for dropped packets or buffer overruns
• Consider reducing maxDDPpx for ESP8266 (commented out at 172 pixels)

---

8. JavaScript: setInterval Timing Drift

Location: videolab.htm line 710

Problem: setInterval(capFrame, 33) doesn't account for actual processing time, causing timing drift and potential frame bunching.

Mitigation:

• Use requestAnimationFrame() for vsync-aligned capture
• Implement adaptive frame pacing based on WebSocket buffer state
• Add timestamp-based frame skipping when falling behind

---

📊 Recommended Prioritization

High Impact, Low Effort:

1. Add ws.bufferedAmount check in sendDDP()
2. Reuse Uint8Array packet buffers
3. Make WLED 15ms throttle configurable

High Impact, Medium Effort:
4. Move capture to OffscreenCanvas + Worker
5. Optimize color conversion loop
6. Replace setInterval with requestAnimationFrame

Medium Impact, High Effort:
7. WebGL-based pixel extraction
8. WebAssembly color conversion
9. ESP32 SIMD gamma correction

---

Would you like me to create implementation plans or code snippets for any of these optimizations?

---

🧠 Learnings used

Learnt from: softhack007
Repo: MoonModules/WLED-MM PR: 0
File: :0-0
Timestamp: 2025-11-14T13:55:44.442Z
Learning: In MoonModules/WLED-MM, always flag Variable Length Arrays (VLA) during code reviews, especially when they could overflow available stack space (typically 2K-4K on ESP32/ESP8266). VLAs based on dynamic parameters like segment dimensions, particle counts, or pixel buffers should be highlighted and require justification from the author. Prefer fixed-size arrays, heap allocation, or bounded VLAs with explicit maximum size constraints.

[softhack007]

@coderabbitai please add references to user guides and official websites to your recommendations for the JS frontend.

[softhack007]

@DedeHai does any of these make sense to you?

It's a "shot in the dark", but the rabbit sometimes has a few good points when none of the "humans" have any clue where to start looking. The points about gamma correction and color conversion are surely wrong, but the comments about flow control, worker threads, canvas context and time drift could be something to look into 🔍

[coderabbitai]

🧩 Analysis chain

🌐 Web query:

MDN WebSocket bufferedAmount API documentation

💡 Result:

MDN summary — WebSocket.bufferedAmount

• What it is: a read-only property that returns the number of bytes queued by WebSocket.send() but not yet transmitted to the network. It resets to 0 once all queued data is sent; it does not reset when the connection is closed and will grow if you keep calling send(). [1]
• Type/value: unsigned long (number of bytes). [1]
• Related: WebSocket.send() increases bufferedAmount by the byte size of the data enqueued (strings are counted as UTF‑8 bytes). [2]

Sources:
[1] MDN WebSocket: bufferedAmount property.
[2] MDN WebSocket: send() method.

---

🌐 Web query:

MDN Canvas getImageData performance

💡 Result:

Short summary — why getImageData() can be slow and how to fix it:

• Problem: frequent getImageData() forces expensive GPU→CPU readbacks and browser heuristics may switch canvas from GPU-backed to slower modes or otherwise penalize performance. Large canvas size and many repeated reads amplify this. [1][4].
• Browser hint: create the 2D context with willReadFrequently: true to tell the engine you’ll read pixels often (browser may prefer a CPU-backed canvas which can be much faster for repeated readbacks). Set this on the first getContext call. [2][6].
• Other mitigation techniques:
  • Minimize and batch reads (read larger blocks less often, avoid per-frame/ per-pixel repeated getImageData). [1][4]
  • Do pixel work off the main thread with OffscreenCanvas / worker when possible. [6].
  • If you use GPU pipelines, consider WebGL readPixels (still a readback but can be tuned) or avoid readbacks entirely by keeping needed state on the GPU. [4]
  • If you must repeatedly sample, consider keeping a cached copy of ImageData (Uint8ClampedArray) and update it incrementally instead of calling getImageData each time. [1]

References:

• getImageData() / ImageData (MDN). [1]
• HTMLCanvasElement.getContext() — willReadFrequently option (MDN). [2]
• Explanation of Chrome’s willReadFrequently warning and guidance (Kevin Schiener). [3]
• Discussion about Chromium switching between GPU/CPU for getImageData and performance behavior (StackOverflow / Chromium notes). [4]

If you want, tell me your code pattern (how often/what area you read) and I’ll give a specific change you can apply.

---

🌐 Web query:

MDN OffscreenCanvas Web Workers documentation

💡 Result:

Here are the MDN Web Docs pages on OffscreenCanvas and using it with Web Workers:

• OffscreenCanvas (overview, API, examples including worker usage). [1]
• HTMLCanvasElement.transferControlToOffscreen() (how to transfer an HTMLCanvasElement to an OffscreenCanvas and post it to a Worker). [2]

References
[1] MDN — OffscreenCanvas.
[2] MDN — HTMLCanvasElement.transferControlToOffscreen().

---

🌐 Web query:

MDN requestAnimationFrame documentation

💡 Result:

Here’s the MDN documentation for requestAnimationFrame and a brief summary:

• Main page — Window.requestAnimationFrame(): describes usage, callback timestamp, return value (request ID), that it’s one-shot (callback must re-request), and that calls are paused in background tabs. [1]

• Worker/other variants — DedicatedWorkerGlobalScope.requestAnimationFrame() and XRSession.requestAnimationFrame(): describes availability in workers and XR sessions and the similar behavior. [2]

If you want, I can paste the key examples or show a minimal example using the timestamp and cancelAnimationFrame.

Sources:
[1] MDN: Window.requestAnimationFrame().
[2] MDN: DedicatedWorkerGlobalScope.requestAnimationFrame() / XRSession.requestAnimationFrame().

---

🌐 Web query:

WebAssembly official documentation

💡 Result:

Here are the official WebAssembly documentation sources:

• WebAssembly project site (overview, links to docs & resources). [1]
• Official WebAssembly specifications (core, embeddings, metadata) — GitHub Pages. [2]
• W3C WebAssembly Core Specification (formal TR/Candidate Recommendation). [3]
• MDN Web Docs — developer-facing reference and API docs for using Wasm in browsers. [4]

References
[1] webassembly.org — Home & docs.
[2] webassembly.github.io/spec — WebAssembly specifications.
[3] W3C — WebAssembly Core Specification (wasm-core).
[4] MDN Web Docs — WebAssembly.

---

🌐 Web query:

MDN Typed Arrays performance optimization

💡 Result:

Here are concise MDN-backed performance tips for using Typed Arrays:

• Use bulk operations (TypedArray.set and subarray) instead of per-element loops — set can be a fast memory move when views share the same ArrayBuffer. (developer.mozilla.org)
• Pick the correct element type to avoid runtime conversions (e.g., Float32Array vs Float64Array) so writes/read don’t need extra normalization. (developer.mozilla.org)
• Reuse ArrayBuffers / views where possible; avoid frequent buffer allocations and copies (allocate once, then slice/subarray or reset indices). (developer.mozilla.org)
• When you need resizable memory, prefer resizable ArrayBuffers or WebAssembly.Memory (resizable) rather than repeatedly copying to larger buffers. (developer.mozilla.org)
• Offload heavy numeric work to WebAssembly or Web Workers to avoid blocking the main thread and reduce JS-side boxing/dispatch overhead. (developer.mozilla.org)
• Measure and profile (browser devtools) — optimize based on real hotspots (avoid premature micro-optimizations). (developer.mozilla.org)

If you want, I can: (a) show micro-benchmarks comparing set() vs loops, (b) give a small code pattern for buffer reuse, or (c) search for engine-specific tips (V8/SpiderMonkey). Which would you like?

Citations:

• 1: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Typed_arrays?utm_source=openai
• 2: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray?utm_source=openai
• 3: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/ArrayBuffer?utm_source=openai
• 4: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/ArrayBuffer?utm_source=openai
• 5: https://developer.mozilla.org/en-US/docs/WebAssembly?utm_source=openai
• 6: https://developer.mozilla.org/en-US/docs/Web/Performance/Guides?utm_source=openai

---

@softhack007, here are the official documentation references for the JavaScript frontend optimizations:

📚 Official Documentation & References

1. WebSocket Flow Control

WebSocket.bufferedAmount property:

• MDN Documentation: WebSocket.bufferedAmount
• Returns the number of bytes queued but not yet transmitted
• MDN WebSocket.send(): WebSocket.send() method
• Check bufferedAmount before each send to avoid overwhelming the socket buffer

---

2. Canvas getImageData() Performance

Canvas API & Performance:

• MDN getImageData(): CanvasRenderingContext2D.getImageData()
• Performance Tip: Use willReadFrequently: true context option for frequent reads
• MDN Canvas context options: HTMLCanvasElement.getContext()
• Setting willReadFrequently: true hints the browser to use CPU-backed canvas for faster repeated readbacks

---

3. OffscreenCanvas & Web Workers

Moving work off main thread:

• MDN OffscreenCanvas: OffscreenCanvas API
• MDN transferControlToOffscreen(): HTMLCanvasElement.transferControlToOffscreen()
• Allows canvas rendering in Web Workers without blocking main thread
• MDN Web Workers: Using Web Workers

---

4. requestAnimationFrame for Better Timing

Frame-synchronized capture:

• MDN requestAnimationFrame(): Window.requestAnimationFrame()
• Provides vsync-aligned timing and automatic pausing in background tabs
• MDN Worker variant: DedicatedWorkerGlobalScope.requestAnimationFrame()

---

5. Typed Arrays & Buffer Optimization

Efficient binary data handling:

• MDN Typed Arrays Guide: JavaScript Typed Arrays
• Use TypedArray.set() for bulk operations instead of loops
• MDN TypedArray reference: TypedArray
• MDN ArrayBuffer: ArrayBuffer
• Reuse buffers to minimize allocations and GC pressure

---

6. WebAssembly for Intensive Processing

Native-speed computation:

• WebAssembly Official Site: webassembly.org
• MDN WebAssembly: WebAssembly on MDN
• W3C Specification: WebAssembly Core Specification
• Ideal for color conversion loops and heavy numeric processing

---

7. General Web Performance

Performance measurement & optimization:

• MDN Web Performance: Web Performance Guides
• MDN Performance API: Performance API
• Use browser DevTools profiling to identify real bottlenecks

---

🎯 Quick Implementation Checklist

For VideoLab specifically:

1. ✅ Add willReadFrequently: true when creating canvas context
2. ✅ Check ws.bufferedAmount < threshold before each ws.send()
3. ✅ Pre-allocate and reuse Uint8Array buffers for DDP packets
4. ✅ Replace setInterval with requestAnimationFrame for capture loop
5. ✅ Consider moving capture to OffscreenCanvas + Worker for larger matrices

Would you like code examples implementing any of these optimizations with the official API patterns?

---

🧠 Learnings used

Learnt from: softhack007
Repo: MoonModules/WLED-MM PR: 0
File: :0-0
Timestamp: 2025-11-14T13:55:44.442Z
Learning: In MoonModules/WLED-MM, always flag Variable Length Arrays (VLA) during code reviews, especially when they could overflow available stack space (typically 2K-4K on ESP32/ESP8266). VLAs based on dynamic parameters like segment dimensions, particle counts, or pixel buffers should be highlighted and require justification from the author. Prefer fixed-size arrays, heap allocation, or bounded VLAs with explicit maximum size constraints.

---

Learnt from: DedeHai
Repo: MoonModules/WLED-MM PR: 253
File: usermods/audioreactive/audio_source.h:1256-1261
Timestamp: 2025-07-12T04:20:14.546Z
Learning: In WLED AudioReactive usermod, DC offset removal optimization in DMAadcSource::getSamples() should be implemented after PR #248 merges, which will change the sample buffer from float to int16. This eliminates the need for temporary integer buffers and allows direct integer arithmetic on the native buffer type for better memory efficiency on resource-constrained MCUs like C3 and S2.

[softhack007]

@coderabbitai yes please show me some (official) code examples for the quick implementation checklist.

[coderabbitai]

@softhack007, here are practical code examples based on official MDN API patterns for each checklist item:

---

1️⃣ Canvas Context with willReadFrequently

Before:

let ctx = canvas.getContext('2d');

After (MDN pattern):

// Tell browser you'll read pixels frequently - enables CPU-backed canvas
let ctx = canvas.getContext('2d', { willReadFrequently: true });

Reference: HTMLCanvasElement.getContext() - MDN

---

2️⃣ WebSocket Flow Control with bufferedAmount

Before (videolab.htm):

function sendDDP(rgb, start, len) {
    for (let i = 0; i < len; i += maxDDPpx) {
        // ... create packet ...
        ws.send(pkt.buffer);  // ❌ No backpressure handling
    }
}

After (MDN pattern):

const MAX_BUFFER_SIZE = 65536; // 64KB threshold (tune based on testing)

function sendDDP(rgb, start, len) {
    for (let i = 0; i < len; i += maxDDPpx) {
        // Check buffer before sending (MDN bufferedAmount pattern)
        if (ws.bufferedAmount > MAX_BUFFER_SIZE) {
            console.warn('WebSocket buffer full, skipping frame');
            return; // Skip this frame to avoid buffer overflow
        }
        
        // ... create packet ...
        ws.send(pkt.buffer);
    }
}

// Optional: Monitor buffer health
setInterval(() => {
    if (ws && ws.readyState === WebSocket.OPEN) {
        console.log('WS buffer:', ws.bufferedAmount, 'bytes');
    }
}, 1000);

Reference: WebSocket.bufferedAmount - MDN

---

3️⃣ Pre-allocated Packet Buffers

Before (common.js line 186):

function sendDDP(rgb, start, len) {
    for (let i = 0; i < len; i += maxDDPpx) {
        let dLen = Math.min(maxDDPpx, len - i) * 3;
        let pkt = new Uint8Array(11 + dLen); // ❌ Allocates every packet
        // ... fill packet ...
        ws.send(pkt.buffer);
    }
}

After (MDN TypedArray pattern):

// Pre-allocate reusable buffer (allocate once at startup)
const MAX_PACKET_SIZE = 11 + (472 * 3); // DDP header + max pixels
let packetBuffer = new ArrayBuffer(MAX_PACKET_SIZE);
let packetView = new Uint8Array(packetBuffer);

function sendDDP(rgb, start, len) {
    for (let i = 0; i < len; i += maxDDPpx) {
        let dLen = Math.min(maxDDPpx, len - i) * 3;
        
        // Reuse pre-allocated buffer (zero-copy)
        // DDP header (11 bytes)
        packetView[0] = 0x41; // 'A' - DDP protocol ID
        // ... rest of header ...
        
        // Copy pixel data using TypedArray.set (fast bulk copy)
        packetView.set(
            rgb.subarray(start + i * 3, start + i * 3 + dLen),
            11
        );
        
        // Send only the used portion
        ws.send(packetView.buffer.slice(0, 11 + dLen));
    }
}

Reference: TypedArray.set() - MDN

---

4️⃣ Replace setInterval with requestAnimationFrame

Before (videolab.htm line 710):

let capTimer;

function startCapture() {
    capTimer = setInterval(capFrame, 33); // ❌ Fixed 33ms, drifts over time
}

function stopCapture() {
    clearInterval(capTimer);
}

After (MDN requestAnimationFrame pattern):

let rafId = null;
let lastFrameTime = 0;
const TARGET_FPS = 30;
const FRAME_INTERVAL = 1000 / TARGET_FPS;

function startCapture() {
    function frameLoop(timestamp) {
        // Throttle to target FPS using high-res timestamp
        if (timestamp - lastFrameTime >= FRAME_INTERVAL) {
            capFrame();
            lastFrameTime = timestamp;
        }
        
        // Continue loop
        rafId = requestAnimationFrame(frameLoop);
    }
    
    rafId = requestAnimationFrame(frameLoop);
}

function stopCapture() {
    if (rafId !== null) {
        cancelAnimationFrame(rafId);
        rafId = null;
    }
}

function capFrame() {
    // ... existing capture logic ...
    
    // Optional: adaptive FPS based on buffer state
    if (ws && ws.bufferedAmount > 32768) {
        console.warn('Slowing down due to buffer pressure');
        lastFrameTime += FRAME_INTERVAL; // Skip next frame
    }
}

Reference: Window.requestAnimationFrame() - MDN

---

5️⃣ OffscreenCanvas + Web Worker (Advanced)

Main Thread (videolab.htm):

let worker;
let offscreen;

function initOffscreenCapture() {
    // Transfer canvas control to OffscreenCanvas
    const canvas = document.getElementById('videoCanvas');
    offscreen = canvas.transferControlToOffscreen();
    
    // Create worker
    worker = new Worker('capture-worker.js');
    
    // Send canvas to worker
    worker.postMessage({
        type: 'init',
        canvas: offscreen,
        width: mw,
        height: mh
    }, [offscreen]); // Transfer ownership
    
    // Receive processed frames
    worker.onmessage = (e) => {
        if (e.data.type === 'frame') {
            sendDDP(e.data.rgb, 0, e.data.rgb.length / 3);
        }
    };
}

function startCapture() {
    worker.postMessage({ type: 'start', fps: 30 });
}

function stopCapture() {
    worker.postMessage({ type: 'stop' });
}

Worker Thread (capture-worker.js):

let ctx;
let width, height;
let rafId;
let rgbBuffer;

self.onmessage = (e) => {
    switch(e.data.type) {
        case 'init':
            const canvas = e.data.canvas;
            width = e.data.width;
            height = e.data.height;
            
            // Create context with willReadFrequently in worker
            ctx = canvas.getContext('2d', { willReadFrequently: true });
            rgbBuffer = new Uint8Array(width * height * 3);
            break;
            
        case 'start':
            const fps = e.data.fps;
            const interval = 1000 / fps;
            let lastTime = 0;
            
            function captureLoop(timestamp) {
                if (timestamp - lastTime >= interval) {
                    // Capture frame (happens off main thread!)
                    const imageData = ctx.getImageData(0, 0, width, height);
                    const data = imageData.data;
                    
                    // Convert RGBA to RGB
                    for (let i = 0; i < width * height; i++) {
                        rgbBuffer[i * 3] = data[i * 4];
                        rgbBuffer[i * 3 + 1] = data[i * 4 + 1];
                        rgbBuffer[i * 3 + 2] = data[i * 4 + 2];
                    }
                    
                    // Send back to main thread
                    self.postMessage({
                        type: 'frame',
                        rgb: rgbBuffer
                    }, [rgbBuffer.buffer]); // Transfer ownership back
                    
                    // Re-allocate for next frame
                    rgbBuffer = new Uint8Array(width * height * 3);
                    lastTime = timestamp;
                }
                
                rafId = requestAnimationFrame(captureLoop);
            }
            
            rafId = requestAnimationFrame(captureLoop);
            break;
            
        case 'stop':
            if (rafId) cancelAnimationFrame(rafId);
            break;
    }
};

References:

• OffscreenCanvas - MDN
• HTMLCanvasElement.transferControlToOffscreen() - MDN
• Using Web Workers - MDN

---

🎯 Recommended Implementation Order

1. Start simple: Apply examples 1-3 first (context options, bufferedAmount, buffer reuse)
2. Measure impact: Profile with browser DevTools to see improvements
3. If still slow: Try example 4 (requestAnimationFrame)
4. For large matrices (>64×64): Consider example 5 (Web Worker)

---

All examples follow official MDN patterns and can be tested directly in VideoLab. Would you like help integrating any of these into the actual codebase?

---

🧠 Learnings used

Learnt from: softhack007
Repo: MoonModules/WLED-MM PR: 0
File: :0-0
Timestamp: 2025-11-14T13:55:44.442Z
Learning: In MoonModules/WLED-MM, always flag Variable Length Arrays (VLA) during code reviews, especially when they could overflow available stack space (typically 2K-4K on ESP32/ESP8266). VLAs based on dynamic parameters like segment dimensions, particle counts, or pixel buffers should be highlighted and require justification from the author. Prefer fixed-size arrays, heap allocation, or bounded VLAs with explicit maximum size constraints.

---

Learnt from: DedeHai
Repo: MoonModules/WLED-MM PR: 253
File: usermods/audioreactive/audio_source.h:1256-1261
Timestamp: 2025-07-12T04:20:14.546Z
Learning: In WLED AudioReactive usermod, DC offset removal optimization in DMAadcSource::getSamples() should be implemented after PR #248 merges, which will change the sample buffer from float to int16. This eliminates the need for temporary integer buffers and allows direct integer arithmetic on the native buffer type for better memory efficiency on resource-constrained MCUs like C3 and S2.

---

Learnt from: DedeHai
Repo: MoonModules/WLED-MM PR: 237
File: wled00/FXparticleSystem.cpp:678-743
Timestamp: 2025-05-04T10:32:30.457Z
Learning: In the Particle System implementation for WLED, stack allocation is preferred over heap allocation for temporary rendering buffers because there's enough stack memory available and heap allocations can cause memory fragmentation.

---

Learnt from: DedeHai
Repo: MoonModules/WLED-MM PR: 248
File: usermods/audioreactive/audio_reactive.h:199-200
Timestamp: 2025-06-30T17:53:37.232Z
Learning: In WLED AudioReactive usermod, when using ArduinoFFT (enabled via UM_AUDIOREACTIVE_USE_ARDUINO_FFT), it's acceptable and necessary to redefine the global sqrt macro to sqrtf within the conditional compilation block for performance optimization. This is a specific requirement for ArduinoFFT optimization that can provide 10-50% performance improvement on ESP32.

---

Learnt from: DedeHai
Repo: MoonModules/WLED-MM PR: 248
File: usermods/audioreactive/audio_reactive.h:1121-1121
Timestamp: 2025-06-30T17:58:27.987Z
Learning: In WLED AudioReactive usermod's runMicFilter function, the different cutoff frequencies between float (80Hz) and integer (90Hz) FFT implementations are intentional. The higher 90Hz cutoff for integer math helps preserve precision by avoiding overly aggressive filtering where integer arithmetic limitations could compound errors. The 10Hz difference between 80Hz and 90Hz is negligible from an audio performance standpoint but provides better precision for integer calculations.

[DedeHai]

@DedeHai does any of these make sense to you?

It's a "shot in the dark", but the rabbit sometimes has a few good points when none of the "humans" have any clue where to start looking. The points about gamma correction and color conversion are surely wrong, but the comments about flow control, worker threads, canvas context and time drift could be something to look into 🔍

I am sure I am not using the most optimal way a canvas can be used, I took the same or similar approach here as I did in the GIF tool. At one point I probably need to benchmark the critical functions to see which ones are slowing down the code as even for just 1000 pixels it already takes quite a bit of CPU power to make it run smoothly which may be related to how the pixels are extracted from the canvas.
The flow control sounds like a thing I may need to look into. I only tested this on chrome so far. The suggestion from the rabbit to drop frames if the buffer is full seems redundant: sure it may save some CPU cycles but if the buffer is full, the frame is dropped anyway, a better approach may be to skip a frame if the buffer is half-full or so to slow down FPS instead of skipping a lot of frames once it is full which may result in a smoother overall video transfer.
I will be working on this tool in the coming days but I will fix the UI first and afterwards do optimizations. I still have a lot of copilot tokens left this month and there are improved coding models available since a few days so might test those out.