The BEST Way to Create Every Camera Angle in Nano Banana PRO
Mastering structured multi-angle generation from a single reference image solves the persistent challenge of character and clothing consistency in indie AI filmmaking.
What this lesson covers
This tutorial breaks down two rapid workflows for AI filmmaking using Nano Banana Pro on LTX: the Grid Method and the Infinite Angles Method. It demonstrates how to maintain character consistency and execute dynamic camera movements from a single foundational image.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 01:48 ↗
Starting with a full-body reference image ensures that subsequent multi-angle generations maintain consistent face, clothing, and body proportions.
- 02:35 ↗
The Grid Method involves prompting a 3x3 cinematic sequence with sequential numbers on each frame to simplify individual frame extraction.
- 04:46 ↗
The Infinite Angles Method uses a foundational image and chains successive prompts together by focusing on what happens next in the story.
- 06:34 ↗
Adding specific time increments like '5 seconds later' or 'one minute later' to prompts helps guide the model when generating sequential action shots.
Workflow outlined in the video
- Begin your character design process with a clear, full-body reference shot to anchor future generations.
- Generate a 3x3 grid using sequential numbers on frames to easily extract specific camera angles for image-to-video pipelines.
- Apply the time-delta prompting technique ('X seconds later') to maintain continuity in action sequences.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
How to interpret the numbers
38,454 views captured 22 October 2026. ReelStack recommendation score: 46/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 65% performance: 1.71× views vs 4 other channel videos observed at a similar age. View-evidence factor 97% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- Momentum pending: collecting daily snapshots; its 20% weight goes to observed performance, not free points
- 10% engagement: 59/100; likes + 4× comments, smoothed with a 500-view neutral prior