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Hunyuan3D-2.1
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Image-to-3D Generation
Doron Adler PRO
Norod78
AI & ML interests
Fooling around with Generative machine learning models.
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The MobileCLIP2-S0 checkpoint seems to have issues
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#2 opened 18 days ago
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Norod78
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DawnC's
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PawMatchAI — Now with SBERT-Powered Recommendations! 🐶✨
⭐️ NEW: Description-based recommendations are here!
Just type in your lifestyle or preferences (e.g. “I live in an apartment and want a quiet dog”), and PawMatchAI uses SBERT semantic embeddings to understand your needs and suggest compatible breeds.
What can PawMatchAI do today?
📸 Upload a photo to identify your dog from 124 breeds with detailed info.
⚖️ Compare two breeds side-by-side, from grooming needs to health insights.
📊 Visualize breed traits with radar and comparison charts.
🎨 Try Style Transfer to turn your dog’s photo into anime, watercolor, cyberpunk, and more.
What’s next?
🎯 More fine-tuned recommendations.
📱 Mobile-friendly deployment.
🐾 Expansion to additional species.
My goal:
To make breed discovery not only accurate but also interactive and fun — combining computer vision, semantic understanding, and creativity to help people find their perfect companion.
👉 Try it here:
DawnC/PawMatchAI
If you enjoy PawMatchAI, please give the project a ❤️ — it really helps and keeps me motivated to keep improving!
#ComputerVision #SBERT #DeepLearning #MachineLearning #TechForLife
⭐️ NEW: Description-based recommendations are here!
Just type in your lifestyle or preferences (e.g. “I live in an apartment and want a quiet dog”), and PawMatchAI uses SBERT semantic embeddings to understand your needs and suggest compatible breeds.
What can PawMatchAI do today?
📸 Upload a photo to identify your dog from 124 breeds with detailed info.
⚖️ Compare two breeds side-by-side, from grooming needs to health insights.
📊 Visualize breed traits with radar and comparison charts.
🎨 Try Style Transfer to turn your dog’s photo into anime, watercolor, cyberpunk, and more.
What’s next?
🎯 More fine-tuned recommendations.
📱 Mobile-friendly deployment.
🐾 Expansion to additional species.
My goal:
To make breed discovery not only accurate but also interactive and fun — combining computer vision, semantic understanding, and creativity to help people find their perfect companion.
👉 Try it here:
DawnC/PawMatchAI
If you enjoy PawMatchAI, please give the project a ❤️ — it really helps and keeps me motivated to keep improving!
#ComputerVision #SBERT #DeepLearning #MachineLearning #TechForLife
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Okay this is insane... WebGPU-accelerated semantic video tracking, powered by DINOv3 and Transformers.js! 🤯
Demo (+ source code): webml-community/DINOv3-video-tracking
This will revolutionize AI-powered video editors... which can now run 100% locally in your browser, no server inference required (costs $0)! 😍
How does it work? 🤔
1️⃣ Generate and cache image features for each frame
2️⃣ Create a list of embeddings for selected patch(es)
3️⃣ Compute cosine similarity between each patch and the selected patch(es)
4️⃣ Highlight those whose score is above some threshold
... et voilà! 🥳
You can also make selections across frames to improve temporal consistency! This is super useful if the object changes its appearance slightly throughout the video.
Excited to see what the community builds with it!
Demo (+ source code): webml-community/DINOv3-video-tracking
This will revolutionize AI-powered video editors... which can now run 100% locally in your browser, no server inference required (costs $0)! 😍
How does it work? 🤔
1️⃣ Generate and cache image features for each frame
2️⃣ Create a list of embeddings for selected patch(es)
3️⃣ Compute cosine similarity between each patch and the selected patch(es)
4️⃣ Highlight those whose score is above some threshold
... et voilà! 🥳
You can also make selections across frames to improve temporal consistency! This is super useful if the object changes its appearance slightly throughout the video.
Excited to see what the community builds with it!
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