DEV Community: xi jin

How to Turn Any Video Into an AI Prompt

xi jin — Fri, 04 Sep 2026 07:51:53 +0000

How to Turn Any Video Into an AI Prompt

Have you ever seen a video and thought:

"I want to recreate something like this with AI — but I have no idea what prompt to write."

This is becoming a common problem as AI image and video generation tools get better.

A reference video may contain dozens of useful visual details:

subjects and objects
composition
camera angles
camera movement
lighting
colors
environment
actions
visual style
transitions between scenes

Turning all of that into a useful AI prompt manually can take a surprising amount of time.

A simpler approach is to use a video-to-prompt workflow.

What Is Video to Prompt?

Video to prompt is the process of analyzing an existing video and converting its visual information into a structured text description that can be used with AI generation models.

Instead of writing something generic like:

A cinematic video of a woman walking through a city.

A detailed video prompt might describe:

A woman walking through a neon-lit city street at night, medium tracking shot, shallow depth of field, wet pavement reflecting blue and magenta lights, slow forward camera movement, cinematic lighting, realistic photography, atmospheric urban environment.

The second prompt gives an AI model much more information about what the original video actually looks like.

What Should a Good Video Prompt Capture?

When reverse-engineering a video into a prompt, I usually want to extract several types of information.

1. Subject

Identify the main subject of the scene.

For example:

a person
a car
a product
an animal
a landscape

Then describe important visual characteristics.

2. Scene and Environment

Describe where the action happens.

For example:

futuristic city
minimalist studio
forest at sunset
crowded street
modern office

Environmental details often have a major impact on the generated result.

3. Camera Angle and Composition

This is one of the easiest details to miss when manually writing prompts.

Useful information includes:

close-up
medium shot
wide shot
aerial shot
low-angle shot
over-the-shoulder shot
centered composition

4. Camera Movement

For video generation, camera movement can be especially important.

Examples include:

slow zoom in
tracking shot
camera pan
dolly forward
handheld movement
orbit around the subject

A prompt describing only the subject and style may reproduce the appearance of a scene but completely miss its motion.

5. Lighting

Lighting can dramatically change the result.

Look for things such as:

soft natural light
golden-hour lighting
dramatic side lighting
neon lighting
studio lighting
high contrast
cinematic shadows

6. Visual Style

Finally, describe the overall visual language.

For example:

cinematic
photorealistic
anime
documentary
commercial photography
retro film
cyberpunk
minimalist

The Manual Way

You can analyze a video manually.

Pause the video at important moments and write down:

What is happening?
Who or what is the main subject?
What does the environment look like?
Where is the camera?
How is the camera moving?
What kind of lighting is being used?
What visual style does the scene have?

For a short clip, this works reasonably well.

For longer videos or videos with multiple scenes, however, it quickly becomes tedious.

Automating the Process

I wanted a faster workflow, so I built VideoToPrompt.dev.

The basic workflow is simple:

Upload a video or paste a supported video URL.
Let the tool analyze the visual content.
Detect important scenes and visual elements.
Generate a structured AI prompt.
Use or modify the resulting prompt for your preferred AI model.

The goal isn't simply to produce a generic video summary.

Instead, the analysis focuses on information that is useful when creating AI-generated visual content, such as:

scene descriptions
subjects
actions
camera angles
camera movement
lighting
composition
visual style

Example: From Video to Prompt

Imagine a reference video showing a sports car driving through a city at night.

A basic description might be:

A sports car driving through a city.

That's technically correct, but not particularly useful.

A more detailed prompt could look something like:

A black sports car driving through a modern city at night, low-angle tracking shot from the rear side of the vehicle, wet asphalt reflecting neon signs, blue and red ambient lighting, shallow depth of field, subtle motion blur, cinematic commercial photography, dynamic forward movement, high contrast, realistic details.

Now the prompt contains much more of the visual structure of the reference video.

You can then adapt it depending on whether you're using an AI image generator or an AI video generator.

Video Prompts vs. Image Prompts

There is an important difference between the two.

For an image model, you usually care most about:

subject + environment + composition + lighting + style

For a video model, you also need to think about:

action + camera movement + temporal changes

For example, an image prompt might say:

Close-up portrait of a woman standing in the rain, cinematic lighting, shallow depth of field.

A video prompt can add:

The camera slowly pushes toward the subject while she turns toward the camera, rain falling in the foreground and background.

That extra motion information can make a significant difference.

Where Can You Use the Generated Prompt?

Once you have extracted the visual language of a video, the resulting prompt can be adapted for different generative AI workflows.

For example, you might use it as a starting point for:

AI image generation
AI video generation
storyboarding
shot analysis
creative references
prompt experimentation
recreating the visual style of your own reference footage

The generated prompt doesn't have to be the final prompt.

I find it more useful to think of it as a structured starting point.

You can keep the camera movement but change the subject.

You can keep the composition but change the environment.

Or you can extract the lighting and visual style while creating an entirely different scene.

A Better Prompt Workflow

My preferred workflow is:

Reference video → Visual analysis → Structured prompt → Edit the important variables → Generate

This is much easier than trying to invent every detail from scratch.

It also makes reference-based generation more systematic.

Instead of saying:

"Make something that looks like this."

you can understand why the reference looks the way it does.

Try It

If you have a reference video and want to see what kind of prompt can be extracted from it, you can try:

👉 VideoToPrompt.dev — Video to AI Prompt Generator

Upload a video or provide a supported video URL, generate the prompt, and then modify it for your own workflow.

The interesting part isn't necessarily copying a video exactly.

It's turning visual references into reusable information:

camera + composition + lighting + motion + style + subject

Once those elements are separated, it becomes much easier to experiment with AI-generated images and videos.

How to Convert Bank Statement PDFs to CSV or Excel Without Manual Cleanup

xi jin — Mon, 24 Aug 2026 06:22:10 +0000

How to Convert Bank Statement PDFs to Excel or CSV

Bank statements contain a lot of useful financial data, but unfortunately, that data is often locked inside PDF files.

If you want to analyze your spending, reconcile transactions, prepare accounting records, or import bank activity into another system, manually copying transactions from a PDF into Excel can be extremely time-consuming.

This becomes even more difficult when the statement contains dozens of pages or when you're working with scanned bank statements.

Fortunately, there is a much easier way to convert bank statement PDFs into structured Excel or CSV data.

Why Is It Difficult to Extract Data From Bank Statements?

A bank statement may look like a simple table:

Date	Description	Debit	Credit	Balance
Aug 1	Coffee Shop	$5.40		$2,145.20
Aug 2	Client Payment		$1,200.00	$3,345.20

But PDF files aren't actually spreadsheets.

The information may be stored as separate text elements positioned across the page rather than structured rows and columns.

When you copy the table directly into Excel, you may end up with:

broken transaction descriptions
missing dates
debit and credit amounts in the wrong columns
page headers mixed with transactions
multi-line transactions split into several rows

Scanned statements are even more difficult because the transactions may exist only as images.

The Easier Way: Convert the Statement Automatically

Instead of manually copying every transaction, you can use a bank statement converter to extract the data automatically.

One option is FinConv, an online tool designed specifically for converting bank statements into structured data.

You can upload a bank statement and convert it into formats such as:

Excel (XLSX)
CSV
JSON

This makes the transaction data much easier to work with.

How to Convert a Bank Statement PDF to Excel or CSV

The process is simple.

Step 1: Upload Your Bank Statement

Start with your original bank statement.

Depending on the document, this might be a PDF or a scanned image.

Upload the statement to FinConv.

Step 2: Extract the Transactions

FinConv analyzes the statement and extracts transaction information such as:

transaction dates
descriptions
debit amounts
credit amounts
balances

Instead of manually rebuilding the table, the transaction data is converted into structured rows.

Step 3: Export the Data

Once the statement has been processed, export the transactions in the format that works best for you.

Choose Excel if you want to review or edit the transactions manually.

Choose CSV if you want to import the data into another application or analyze it with scripts.

Choose JSON if you're building an application or automation workflow.

What Can You Do With the Converted Data?

Once your bank statement is converted into structured data, you can use it for many different tasks.

For example:

analyze monthly spending
categorize expenses
find recurring subscriptions
prepare bookkeeping records
reconcile bank accounts
review business cash flow
prepare financial reports
import transactions into internal tools
analyze transactions with Python or other data tools

Instead of spending time cleaning up a PDF, you can focus on analyzing the transactions themselves.

What About Scanned Bank Statements?

Scanned statements can be especially frustrating because you usually can't select or copy the text.

A bank statement extraction tool can process the document and reconstruct the transaction information into structured data.

However, it's always a good idea to review the extracted results, especially when working with scanned documents.

Check that:

transaction dates are correct
descriptions haven't been split incorrectly
debit and credit amounts are in the correct columns
transactions haven't been missed
balances match the original statement

A quick review is usually much easier than manually entering every transaction.

PDF to CSV or PDF to Excel?

Both formats are useful, but they work better for different situations.

Excel is usually better if you want to manually review, filter, categorize, or edit transactions.

CSV is better when you want a simple format that can be imported into other software or processed programmatically.

For developers, JSON can also be useful when bank statement data needs to become part of an application or automated workflow.

Final Thoughts

Bank statements are designed to be read by people, not analyzed as structured data.

That's why copying transactions manually from PDF statements can become frustrating very quickly.

A simpler workflow is:

Bank Statement PDF → Structured Transactions → Excel / CSV / JSON

If you regularly need to extract transactions from bank statements, you can try FinConv – Bank Statement PDF to Excel & CSV Converter.

It turns bank statement files into structured transaction data, so you can spend less time copying and cleaning data and more time actually working with it.