Best: Leonardo AI or Midjourney for batch catalog images

Short recommendation
If you need predictable, repeatable batches and asset naming for hundreds of SKUs, lean toward Leonardo AI for the pipeline. It offers better workflow primitives (batch jobs, export controls, and easier automation) out of the box. Use Midjourney only if your primary requirement is the most stylized or highest-perceived creative quality and you’re comfortable building a Discord automation layer.

Why (decision criteria)
- Automation/API & exports: Leonardo wins for a smoother programmatic/batch pipeline and export controls. Midjourney requires Discord automation (bots/webhooks) which adds friction and fragility.
- Consistency: Leonardo’s control tools (fixed seeds, reference images, templates) are easier to lock down across large runs.
- Image quality: Midjourney often produces very high-quality single images; if you need heavily stylized hero shots, it’s great. For catalog consistency across many SKUs, Leonardo is safer.
- Budget & scale: Consider per-image costs and rate limits. If budget is tight, test both and compare cost-per-usable-image.
- Team & skill level: Leonardo is faster to adopt for a product team without a dedicated automation/dev team. If you have dev resources, Midjourney automation is feasible but more work.

Practical checklist (step-by-step)
1) Prepare assets: clean reference photos for angle, scale, and lighting. Create a neutral background reference.
2) Build a prompt template with variables: SKU, product description, angle token, lighting token, negative prompts. Example: "Studio product shot of {SKU} on white seamless background, 45° angle, softbox key light, neutral reflections --no text --seed {seed}".
3) Fix variables for consistency: set a fixed seed per SKU/angle, fixed aspect ratio/resolution, and a standard sampler/steps.
4) Batch generation:
- Preferred: use Leonardo’s batch/export features or API to submit CSV of prompts and SKU fields and pull outputs.
- Alternative: where API isn’t available, automate Discord via a bot or Playwright to send prompts and capture results (more brittle).
5) Post-process automation: auto-run background removal/inpainting (for edge cleanup), standard color correction LUT, and resizing/upscaling as needed.
6) Asset naming & metadata: filename = SKU_angle_seed_version.png (e.g., SKU123_45deg_s1234_v1.png). Save a JSON/CSV row per output with prompt, seed, model/version, job id, timestamp, and quality flag.
7) QA & sampling: Reject by automated heuristics (face detection on non-fashion items, SSIM duplicates, histogram outliers) plus human spot checks (1%–5%).

Automation tips & practical tools
- Use ChatGPT to generate prompt templates and CSV rows from your product data.
- Store prompts and outputs in S3/drive and maintain an index file for re-generation.
- Throttle calls to avoid rate limits; parallelize by SKU batches.

Best-for / Avoid-if
- Best for Leonardo AI: batch cataloging, predictable outputs, teams that need export/asset management without heavy engineering.
- Avoid Leonardo AI if you need the most experimental, stylized art and are willing to build Discord automation.
- Best for Midjourney: single high-impact creative images or stylized catalog hero shots.
- Avoid Midjourney if you need high-volume automation and strict filename/metadata guarantees.

Final tips
Start with a 50-SKU pilot: lock a seed/angle per SKU, iterate prompts, validate cost per usable image, then scale. Keep prompt+seed as the canonical source of truth so you can reproduce any image later.

Recommendation CTA
If you want to try the smoother batch path first, test Leonardo AI for a single SKU batch run and export metadata to validate consistency before committing to the whole catalog.

Compare Leonardo AI and Midjourney