An
Animating the World of Van Gogh with Stable Diffusion and AnimateDiff [video]
Hacker NewsAnimating the World of Van Gogh with Stable Diffusion and AnimateDiff [video]
I know I'm very late to the game but tried to realize Van Gogh's work with AI. Workflow is quite straightforward, generated all the video samples through Automatic1000's Web-UI by leveraging SD1.5 + Motionv3 in AnimateDiff. Rendered everything on my RTX 3080TIM laptop. Took me decent 40 mins for different experiments and generations.
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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal69%69% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue26%26% 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, crypto11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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