Video to notes keyframes without manual screenshots
FrameNotes detects meaningful visual changes, filters repeated frames, and keeps the images that make a video easier to review.
Beta: short-video MVP, local upload recommended
Video to notes, video to markdown, and video transcript with screenshots for short learning videos. FrameNotes extracts keyframes, transcript segments, and structured outputs so recordings become readable AI video notes.
Link conversion may be affected by platform access restrictions. For reliable results, upload a local MP4, MOV, AVI, or MKV file.
The caption appears directly under the image, so the reader can understand what was said at that moment without switching back to the video.
Live Demo Preview
The product goal is simple: turn a video into a scrollable reading document. Instead of a folder full of screenshots or a raw transcript, FrameNotes puts the useful visual context and the corresponding words into the same timeline.
Core Features
FrameNotes detects meaningful visual changes, filters repeated frames, and keeps the images that make a video easier to review.
Cloud ASR providers turn clear audio into readable transcript segments. When timestamps are available, captions are matched under the right image.
Generate HTML, Markdown, and presentation-style pages for study, research, and review workflows.
How It Works
The workflow separates upload, visual extraction, transcription, and export into visible stages. That makes a processing task easier to understand and gives failures a specific place instead of leaving the user with an endless loading screen.
For the most reliable beta experience, choose a local MP4, MOV, AVI, or MKV file. The browser uploads the file first, then FrameNotes creates a task ID that can be used to restore progress after a refresh. YouTube links are available as a convenience, but platform login, age, Premium, and cookie checks can prevent server-side access.
FrameNotes analyzes the video timeline for meaningful visual changes. It keeps useful slides, diagrams, browser states, and presentation moments while filtering near-duplicate frames. This produces a smaller set of images that is easier to scan than fixed-interval screenshots and avoids filling a note with repeated views of the same slide.
The processing job separates the audio and sends it to the configured speech-to-text provider. Transcript quality depends on clear speech, background noise, language support, and provider availability. When timestamp data is returned, FrameNotes matches each transcript segment to the image shown during that part of the recording.
After image and transcript processing finishes, FrameNotes generates a reading-first result. The standalone HTML file embeds its images for convenient local viewing. Markdown can be downloaded with its image folder as a ZIP package, while Word and presentation-style HTML provide alternative formats for editing, reviewing, or sharing.
What You Get
A useful conversion is more than a transcript dump or a screenshot folder. FrameNotes keeps the relationship between time, image, and spoken context, then packages the result in formats that can be opened outside the website.
Each selected keyframe includes its time range and the transcript text associated with that moment. The result preserves enough sequence to understand how the speaker moved from one idea to the next. It is designed for review and reference, not as a replacement for the original video or a promise of a perfect verbatim record.
Use standalone HTML when you want one file that opens in a browser with images visible. Use the Markdown ZIP when you want editable text plus a stable relative image folder. Use DOCX for a conventional document workflow. JSON remains available as structured task data for technical inspection and future integrations.
FrameNotes reports the current stage, percentage, and task status instead of showing a single indefinite loading message. Recent task IDs are stored in the browser so progress can be checked after a refresh. If download, transcription, or processing fails, the public interface should show a useful product message rather than inventing transcript text.
Use Cases
Turn a short lesson into review notes that pair the instructor's slides with the explanation delivered at that moment. Students can revisit definitions, diagrams, and examples without repeatedly scrubbing through the full recording.
Capture the visual structure of a recorded lecture and keep the related transcript nearby. This is especially useful when a speaker builds an argument across several slides and the image alone does not preserve the spoken context.
Create a searchable reference from interviews, talks, webinars, or product demonstrations. Researchers can keep key visual evidence beside the speaker's words, then move the Markdown package into their preferred knowledge-management workflow.
Convert a short source video into a compact research document before outlining an article, lesson, or response. FrameNotes helps organize source material, but users should still verify quotations and facts against the original recording.
For short recorded walkthroughs, extract important interface states and the explanation around them. The result can support internal review or documentation, provided participants are authorized to upload and process the recording.
When a recording includes useful on-screen references, names, charts, or chapter cards, FrameNotes combines those visuals with transcript segments. Audio-only material can still be transcribed, although the visual-note benefit is naturally smaller.
FAQ
Yes, link-based conversion is supported, but YouTube access can be affected by platform restrictions. Local video upload is the most reliable path for the current beta.
The current app processes uploads in a server job directory. Product analytics should record task metadata only; uploaded source videos are not intended as permanent user content storage.
The public beta currently supports videos under 30 minutes and local files under 500 MB. Longer videos still need a separate worker pipeline and may be gated.
Current outputs include a standalone HTML result page, Markdown files, a Markdown ZIP package with images, a Word document, and a presentation-style HTML page.
Transcription depends on the configured ASR provider, API quota, audio clarity, supported language, and provider availability. Failed tasks should show the provider error instead of fake captions.
The current upload interface accepts MP4, MOV, AVI, and MKV files. MP4 with a common H.264 video track and a standard audio track is usually the most portable choice. The public beta currently recommends files under 500 MB and videos under 30 minutes.
Yes. The extraction stage compares visual changes and filters near-duplicate frames instead of saving an image every few seconds. Results still vary with the source: rapid animations may create more images, while a mostly static talking-head video may produce fewer useful keyframes.
Language support comes from the speech-to-text provider configured by the service. Clear speech and a provider-supported language generally produce better results. Mixed languages, heavy accents, overlapping speakers, music, and poor audio can reduce accuracy, so important wording should be checked against the source.
Once upload finishes and the API creates a task ID, processing runs as a background job. The frontend keeps recent task IDs in local browser storage and can restore their status after a refresh. Do not close the page during the initial file upload, because no server task exists until that upload completes.
The current beta focuses on extracting key images, generating a transcript, aligning text with the visual timeline, and exporting readable notes. It does not promise a fully rewritten AI summary for every video. The output is intended to preserve source context so users can review and organize it themselves.