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Create AI-Generated Pokemon Cards (Using Python, Midjourney, GPT)

Hacker News

Create AI-Generated Pokemon Cards (Using Python, Midjourney, GPT)

Hey HN! I wanted to share this Python CLI that uses AI to generate a collection of Pokemon cards (with different elements, abilities and evolutions). It constructs a prompt for Midjourney (art generation AI) and GPT-3 (NLP AI) to create the image, names and back-story, and then puts them all together with a card template. I've been messing around with Midjourney and GPT, and wanted to explore using it with some kind of structured goal. Prompts and generations are stateless, so it was interesting to try and make them consistent and useful — especially for something structured like a collection of Pokemon cards that had to respect a set of requirements. I also recorded a video about the design process and challenges here: https://youtu.be/IrDRHzT26F4

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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