Use FFmpeg to decode a screen recording and write selected frames as numbered image files, then let Node.js process those files as they are produced. For example, the FFmpeg filter fps=1 extracts about one frame per second, while -ss, -t and -frames:v let you choose a time window or cap the output. This approach avoids loading the entire recording—or every extracted image—into a Node.js array.
Choose how to sample the recording
Before writing code, decide whether you need a regular sample, a single image, or a bounded segment. These are different jobs: a rate controls how often FFmpeg emits frames; a seek position and duration control the part of the video being read; and a frame limit caps how many images are written.
| Goal | FFmpeg option or filter | Example |
|---|---|---|
| One frame per second | -vf fps=1 |
Sample the recording at a one-frame-per-second rate. |
| Five frames per second | -vf fps=5 |
Write a denser regular sample. |
| One frame at a timestamp | -ss and -frames:v 1 |
Seek to a point and emit one image. |
| A time-bounded sample | -ss, -t and -vf |
Start at a chosen point, process a duration, and sample at a chosen rate. |
| A maximum frame count | -frames:v |
Stop after the specified number of output frames. |
A filter such as fps=1 describes sampling frequency; it does not mean “the first frame only.” For a one-off image, use -frames:v 1. If matching exact timestamps matters, verify the extracted images against the input’s time base: an output sequence number is not necessarily a wall-clock timestamp.
Install FFmpeg and prepare a Node.js project
Install FFmpeg using the package manager or distribution appropriate to your operating system, and make sure the ffmpeg executable is available on the process PATH. Confirm that it runs with ffmpeg -version. Node.js must also be installed. The example below uses ECMAScript modules and built-in Node.js modules, so it does not need an npm wrapper package.
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Create a project directory and initialize it with
npm init -y. -
Enable ES modules by adding
"type": "module"to the project’spackage.json, or save the script with an.mjsextension. -
Put the recording at
recording.mp4in the project directory, or change the input path in the script. -
Save the following code as
extract-frames.mjsand runnode extract-frames.mjs.Do these 3 things before closing this tab:
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Extract frames with Node.js child_process
This script creates the output directory, starts FFmpeg with an argument array, collects diagnostic output from stderr, and waits for FFmpeg to finish. It writes sequential PNG files named frame-00000.png, frame-00001.png, and so on.
import { spawn } from 'node:child_process';
import { mkdir } from 'node:fs/promises';
await mkdir('frames', { recursive: true });
const args = [
'-hide_banner',
'-loglevel', 'error',
'-i', 'recording.mp4',
'-vf', 'fps=1',
'-start_number', '0',
'frames/frame-%05d.png'
];
const ffmpeg = spawn('ffmpeg', args, {
stdio: ['ignore', 'ignore', 'pipe']
});
let diagnostics = '';
ffmpeg.stderr.setEncoding('utf8');
ffmpeg.stderr.on('data', chunk => {
diagnostics += chunk;
});
const exitCode = await new Promise((resolve, reject) => {
ffmpeg.once('error', reject);
ffmpeg.once('close', resolve);
});
if (exitCode !== 0) {
throw new Error(`ffmpeg failed (${exitCode}): ${diagnostics}`);
}
console.log('Frame extraction complete.');The array passed to spawn keeps each option and value separate instead of building a shell command string. This avoids shell-quoting problems with paths that contain spaces and makes the effective FFmpeg arguments easy to inspect. Standard output is ignored because this command writes image files; standard error is retained for diagnostics. The close event provides the process exit code after its stdio streams have closed, while the error event catches failures to start the process, such as a missing executable.
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Change the sample rate or output format
Replace 'fps', '1'—in this example, the single filter argument 'fps=1'—with 'fps=5' for five sampled frames per second. Change the filename suffix to .jpg or .webp to use another output format supported by the FFmpeg build. PNG preserves lossless pixels; JPEG and WebP may reduce storage use. Choose based on the needs of the downstream OCR, computer-vision, or archival step, and validate the image quality for that use.
Capture one frame at a timestamp
For a single representative image, use this command:
ffmpeg -ss 00:00:12.500 -i recording.mp4 -frames:v 1 frame.pngIn Node.js, pass the same tokens as an argument array, for example ['-ss', '00:00:12.500', '-i', 'recording.mp4', '-frames:v', '1', 'frame.png']. Seeking before the input is useful for a fast seek; if precision at a particular point matters, check the result against the source rather than assuming every seek lands on an exact display timestamp.
Extract a bounded segment
To sample a ten-second segment beginning at two minutes, producing two frames per second, run:
ffmpeg -ss 00:02:00 -i recording.mp4 -t 00:00:10 -vf fps=2 frames/frame-%05d.webpThe seek, duration, sampling filter and output suffix can be adjusted independently. A bounded interval helps limit temporary output, but the number of actual images depends on the input and sampling behavior; do not treat the requested duration multiplied by the nominal rate as a guaranteed frame count.
Choose filenames and image formats
The image2 output muxer accepts numbered filename patterns such as img-%03d.jpeg. The number of percent signs indicates the minimum number of digits, so %05d yields five-digit sequence numbers for ordinary values. Use -start_number when you want a particular first index. Numbered files sort naturally and are straightforward to enumerate in Node.js.
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For workflows that need names based on presentation timestamps or formatted times, FFmpeg also has timestamp-oriented options such as frame_pts and strftime. These are alternatives to a simple sequence counter; choose them only when timestamp-derived naming is useful to the consumer. A single output image can be limited with -frames:v 1.
Process frames without accumulating them in memory
Writing every extracted image into an array or keeping all decoded pixels in memory makes resource use grow with the recording. A simpler pattern is to process paths through a bounded queue: enumerate completed frame files, give each path to OCR or image analysis, persist its result, and then delete or archive the image. Limit the number of concurrent consumers so a slow analysis service cannot cause an unbounded backlog.
For a basic sequential workflow, run FFmpeg to completion and then process files one at a time. This is easy to reason about but waits until extraction finishes before analysis begins. To overlap extraction and analysis, watch the output directory for new files or build a producer-consumer pipeline. In either case, use a queue with a fixed capacity and pause or throttle production when consumers fall behind. Handle partial output carefully: do not open a file until it is complete, and do not treat a directory listing as a reliable ordering mechanism without sorting by the numeric sequence.
When a pipe is appropriate
For streaming, FFmpeg can emit image data through a pipe, but the consumer must know how to identify complete frame boundaries. With raw video, that means knowing the width, height, pixel format and resulting frame size before parsing the byte stream. If any of those assumptions is wrong, frame boundaries become invalid and the pixels may be misinterpreted. A file sequence is often the safer option when output size is manageable; a pipe avoids per-frame files but requires explicit framing and backpressure.
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The fluent-ffmpeg wrapper documents methods including .frames(), .save(), .pipe() and .run(), as well as lifecycle events and a screenshot helper that accepts a count, timemarks, output folder, filename tokens, size and fast-seek settings. It can make sparse thumbnail jobs more convenient, while direct spawn keeps the exact FFmpeg flags visible.
import ffmpeg from 'fluent-ffmpeg';
ffmpeg('recording.mp4')
.outputOptions(['-vf', 'fps=1'])
.on('error', err => console.error(err.message))
.on('end', () => console.log('frames complete'))
.save('frames/frame-%05d.png');Choose one approach based on what the job needs rather than mixing abstractions without a reason:
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- Direct spawn: use it when exact argument ordering, stderr diagnostics, process exit status, or minimizing wrapper dependencies is important.
- Wrapper: use it when its helper methods express the job more clearly, especially for sparse timemark-based thumbnails.
- Files: use numbered output when downstream processing is easier with paths and storage use is acceptable.
- Pipe: use it when avoiding per-image files is worth implementing framing and backpressure correctly.
In production, log the generated command or argument list, pin the FFmpeg binary and version in the deployment environment, and treat an absent executable as a startup or configuration error.
Troubleshoot common failures
spawn ffmpeg ENOENT: Node.js could not find the executable. Install FFmpeg in the runtime environment or configure the executable path explicitly, then verify it from the same service account that runs Node.js.- Nonzero FFmpeg exit code: inspect the captured stderr text for an invalid input path, unsupported codec, malformed option, or unwritable output directory. Do not report success solely because some image files exist; a failed run can leave partial output.
- No images appear: check that the input contains a decodable video stream, the output directory exists and is writable, the selected time window overlaps the video, and the output pattern is valid.
- Unexpectedly sparse or dense output: verify the intended sampling semantics.
fps=1is a filter rate;-frames:v 1is a hard output-count limit. They solve different problems. - Images are too large or disk fills: lower the sampling rate, restrict the segment with
-ssand-t, or choose a more compact image format if it satisfies the analysis quality requirement. Remove processed files when they no longer need to be retained. - Memory rises during analysis: avoid collecting image buffers or results indefinitely. Bound concurrency and queue length, persist results incrementally, and apply backpressure to the producer.
- Frames do not align with expected timestamps: do not infer elapsed wall-clock time solely from the sequence index. Validate seek behavior and the source time base; use timestamp-oriented naming if the downstream workflow needs presentation-time references.
Performance, reliability and cost considerations
Extraction speed, memory use and output volume depend on the recording’s codec, resolution, hardware, sampling rate and chosen image format. There is no single throughput or memory figure that applies to all Node.js/FFmpeg jobs. Measure representative recordings in the deployment environment before setting queue sizes, concurrency, disk quotas or processing deadlines.
Reliability comes from making the process boundary observable: capture stderr, check the exit code, handle spawn errors, and distinguish complete output from partial files. For repeatable deployments, pin the FFmpeg binary/version and keep the invocation visible in logs. Storage requirements are governed chiefly by the portion of video sampled, sample rate, image dimensions and encoding choice; bound the time window or clean up files when disk use must remain predictable.
Or skip the browser setup
If what you need is a clean image of a live web page—not frames from an existing screen recording—ScreenshotNeo takes a webpage screenshot through one API request. It is not a video-frame extractor and does not replace FFmpeg for recordings.
cURL example, documented at ScreenshotNeo’s API docs:
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpScreenshotNeo removes cookie/consent banners, newsletter popups and chat widgets before capture; bot checks, blank pages and failed loads are never billed. Its MCP server provides screenshot tools for AI agents, and the Free plan includes 1,000 screenshots per month with no card; paid plans start at $5 for 3,000. Sign up for the free plan.
The Tool Desk
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Does fps=1 select exactly one frame from the entire recording?
No. It samples at a rate of one frame per second. Use -frames:v 1 when you need a one-image output limit.
Can the output filenames contain timestamps instead of sequence numbers?
Yes. FFmpeg documents timestamp-oriented options including frame_pts and strftime; use them when presentation-time-based naming is required.
Is a screenshot API suitable for extracting frames from an MP4?
No. A screenshot API captures a webpage; use FFmpeg to decode video recordings.
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