Glad to hear !
Eric Chung PRO
DawnC
AI & ML interests
Computer Vision, LLM, Hybrid Architectures, MultiModel
Recent Activity
replied to
their
post
11 days ago
🚀 VisionScout Now Speaks More Like Me — Thanks to LLMs!
I'm thrilled to share a major update to VisionScout, my end-to-end vision system.
Beyond robust object detection (YOLOv8) and semantic context (CLIP), VisionScout now features a powerful LLM-based scene narrator (Llama 3.2), improving the clarity, accuracy, and fluidity of scene understanding.
This isn’t about replacing the pipeline , it’s about giving it a better voice. ✨
⭐️ What the LLM Brings
Fluent, Natural Descriptions:
The LLM transforms structured outputs into human-readable narratives.
Smarter Contextual Flow:
It weaves lighting, objects, zones, and insights into a unified story.
Grounded Expression:
Carefully prompt-engineered to stay factual — it enhances, not hallucinates.
Helpful Discrepancy Handling:
When YOLO and CLIP diverge, the LLM adds clarity through reasoning.
VisionScout Still Includes:
🖼️ YOLOv8-based detection (Nano / Medium / XLarge)
📊 Real-time stats & confidence insights
🧠 Scene understanding via multimodal fusion
🎬 Video analysis & object tracking
🎯 My Goal
I built VisionScout to bridge the gap between raw vision data and meaningful understanding.
This latest LLM integration helps the system communicate its insights in a way that’s more accurate, more human, and more useful.
Try it out 👉 https://huggingface.co/spaces/DawnC/VisionScout
If you find this update valuable, a Like❤️ or comment means a lot!
#LLM #ComputerVision #MachineLearning #TechForLife
updated
a Space
11 days ago
DawnC/VisionScout
posted
an
update
11 days ago
🚀 VisionScout Now Speaks More Like Me — Thanks to LLMs!
I'm thrilled to share a major update to VisionScout, my end-to-end vision system.
Beyond robust object detection (YOLOv8) and semantic context (CLIP), VisionScout now features a powerful LLM-based scene narrator (Llama 3.2), improving the clarity, accuracy, and fluidity of scene understanding.
This isn’t about replacing the pipeline , it’s about giving it a better voice. ✨
⭐️ What the LLM Brings
Fluent, Natural Descriptions:
The LLM transforms structured outputs into human-readable narratives.
Smarter Contextual Flow:
It weaves lighting, objects, zones, and insights into a unified story.
Grounded Expression:
Carefully prompt-engineered to stay factual — it enhances, not hallucinates.
Helpful Discrepancy Handling:
When YOLO and CLIP diverge, the LLM adds clarity through reasoning.
VisionScout Still Includes:
🖼️ YOLOv8-based detection (Nano / Medium / XLarge)
📊 Real-time stats & confidence insights
🧠 Scene understanding via multimodal fusion
🎬 Video analysis & object tracking
🎯 My Goal
I built VisionScout to bridge the gap between raw vision data and meaningful understanding.
This latest LLM integration helps the system communicate its insights in a way that’s more accurate, more human, and more useful.
Try it out 👉 https://huggingface.co/spaces/DawnC/VisionScout
If you find this update valuable, a Like❤️ or comment means a lot!
#LLM #ComputerVision #MachineLearning #TechForLife
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DawnC's activity
replied to
their
post
11 days ago
posted
an
update
11 days ago
Post
2539
🚀 VisionScout Now Speaks More Like Me — Thanks to LLMs!
I'm thrilled to share a major update to VisionScout, my end-to-end vision system.
Beyond robust object detection (YOLOv8) and semantic context (CLIP), VisionScout now features a powerful LLM-based scene narrator (Llama 3.2), improving the clarity, accuracy, and fluidity of scene understanding.
This isn’t about replacing the pipeline , it’s about giving it a better voice. ✨
⭐️ What the LLM Brings
Fluent, Natural Descriptions:
The LLM transforms structured outputs into human-readable narratives.
Smarter Contextual Flow:
It weaves lighting, objects, zones, and insights into a unified story.
Grounded Expression:
Carefully prompt-engineered to stay factual — it enhances, not hallucinates.
Helpful Discrepancy Handling:
When YOLO and CLIP diverge, the LLM adds clarity through reasoning.
VisionScout Still Includes:
🖼️ YOLOv8-based detection (Nano / Medium / XLarge)
📊 Real-time stats & confidence insights
🧠 Scene understanding via multimodal fusion
🎬 Video analysis & object tracking
🎯 My Goal
I built VisionScout to bridge the gap between raw vision data and meaningful understanding.
This latest LLM integration helps the system communicate its insights in a way that’s more accurate, more human, and more useful.
Try it out 👉 DawnC/VisionScout
If you find this update valuable, a Like❤️ or comment means a lot!
#LLM #ComputerVision #MachineLearning #TechForLife
I'm thrilled to share a major update to VisionScout, my end-to-end vision system.
Beyond robust object detection (YOLOv8) and semantic context (CLIP), VisionScout now features a powerful LLM-based scene narrator (Llama 3.2), improving the clarity, accuracy, and fluidity of scene understanding.
This isn’t about replacing the pipeline , it’s about giving it a better voice. ✨
⭐️ What the LLM Brings
Fluent, Natural Descriptions:
The LLM transforms structured outputs into human-readable narratives.
Smarter Contextual Flow:
It weaves lighting, objects, zones, and insights into a unified story.
Grounded Expression:
Carefully prompt-engineered to stay factual — it enhances, not hallucinates.
Helpful Discrepancy Handling:
When YOLO and CLIP diverge, the LLM adds clarity through reasoning.
VisionScout Still Includes:
🖼️ YOLOv8-based detection (Nano / Medium / XLarge)
📊 Real-time stats & confidence insights
🧠 Scene understanding via multimodal fusion
🎬 Video analysis & object tracking
🎯 My Goal
I built VisionScout to bridge the gap between raw vision data and meaningful understanding.
This latest LLM integration helps the system communicate its insights in a way that’s more accurate, more human, and more useful.
Try it out 👉 DawnC/VisionScout
If you find this update valuable, a Like❤️ or comment means a lot!
#LLM #ComputerVision #MachineLearning #TechForLife
-
- 2 replies
posted
an
update
15 days ago
Post
3467
PawMatchAI 🐾: The Complete Dog Breed Platform
PawMatchAI offers a comprehensive suite of features designed for dog enthusiasts and prospective owners alike. This all-in-one platform delivers five essential tools to enhance your canine experience:
1. 🔍Breed Detection: Upload any dog photo and the AI accurately identifies breeds from an extensive database of 124+ different dog breeds. The system detects dogs in the image and provides confident breed identification results.
2.📊Breed Information: Access detailed profiles for each breed covering exercise requirements, typical lifespan, grooming needs, health considerations, and noise behavior - giving you complete understanding of any breed's characteristics.
3.📋 Breed Comparison : Compare any two breeds side-by-side with intuitive visualizations highlighting differences in care requirements, personality traits, health factors, and more - perfect for making informed decisions.
4.💡 Breed Recommendation: Receive personalized breed suggestions based on your lifestyle preferences. The sophisticated matching system evaluates compatibility across multiple factors including living space, exercise capacity, experience level, and family situation.
5.🎨 Style Transfer: Transform your dog photos into artistic masterpieces with five distinct styles: Japanese Anime, Classic Cartoon, Oil Painting, Watercolor, and Cyberpunk - adding a creative dimension to your pet photography.
👋Explore PawMatchAI today:
DawnC/PawMatchAI
If you enjoy this project or find it valuable for your canine companions, I'd greatly appreciate your support with a Like❤️ for this project.
#ArtificialIntelligence #MachineLearning #ComputerVision #PetTech #TechForLife
PawMatchAI offers a comprehensive suite of features designed for dog enthusiasts and prospective owners alike. This all-in-one platform delivers five essential tools to enhance your canine experience:
1. 🔍Breed Detection: Upload any dog photo and the AI accurately identifies breeds from an extensive database of 124+ different dog breeds. The system detects dogs in the image and provides confident breed identification results.
2.📊Breed Information: Access detailed profiles for each breed covering exercise requirements, typical lifespan, grooming needs, health considerations, and noise behavior - giving you complete understanding of any breed's characteristics.
3.📋 Breed Comparison : Compare any two breeds side-by-side with intuitive visualizations highlighting differences in care requirements, personality traits, health factors, and more - perfect for making informed decisions.
4.💡 Breed Recommendation: Receive personalized breed suggestions based on your lifestyle preferences. The sophisticated matching system evaluates compatibility across multiple factors including living space, exercise capacity, experience level, and family situation.
5.🎨 Style Transfer: Transform your dog photos into artistic masterpieces with five distinct styles: Japanese Anime, Classic Cartoon, Oil Painting, Watercolor, and Cyberpunk - adding a creative dimension to your pet photography.
👋Explore PawMatchAI today:
DawnC/PawMatchAI
If you enjoy this project or find it valuable for your canine companions, I'd greatly appreciate your support with a Like❤️ for this project.
#ArtificialIntelligence #MachineLearning #ComputerVision #PetTech #TechForLife
reacted to
wolfram's
post with 🔥
16 days ago
Post
7098
Finally finished my extensive **Qwen 3 evaluations** across a range of formats and quantisations, focusing on **MMLU-Pro** (Computer Science).
A few take-aways stood out - especially for those interested in local deployment and performance trade-offs:
1️⃣ **Qwen3-235B-A22B** (via Fireworks API) tops the table at **83.66%** with ~55 tok/s.
2️⃣ But the **30B-A3B Unsloth** quant delivered **82.20%** while running locally at ~45 tok/s and with zero API spend.
3️⃣ The same Unsloth build is ~5x faster than Qwen's **Qwen3-32B**, which scores **82.20%** as well yet crawls at <10 tok/s.
4️⃣ On Apple silicon, the **30B MLX** port hits **79.51%** while sustaining ~64 tok/s - arguably today's best speed/quality trade-off for Mac setups.
5️⃣ The **0.6B** micro-model races above 180 tok/s but tops out at **37.56%** - that's why it's not even on the graph (50 % performance cut-off).
All local runs were done with LM Studio on an M4 MacBook Pro, using Qwen's official recommended settings.
**Conclusion:** Quantised 30B models now get you ~98 % of frontier-class accuracy - at a fraction of the latency, cost, and energy. For most local RAG or agent workloads, they're not just good enough - they're the new default.
Well done, Qwen - you really whipped the llama's ass! And to OpenAI: for your upcoming open model, please make it MoE, with toggleable reasoning, and release it in many sizes. *This* is the future!
A few take-aways stood out - especially for those interested in local deployment and performance trade-offs:
1️⃣ **Qwen3-235B-A22B** (via Fireworks API) tops the table at **83.66%** with ~55 tok/s.
2️⃣ But the **30B-A3B Unsloth** quant delivered **82.20%** while running locally at ~45 tok/s and with zero API spend.
3️⃣ The same Unsloth build is ~5x faster than Qwen's **Qwen3-32B**, which scores **82.20%** as well yet crawls at <10 tok/s.
4️⃣ On Apple silicon, the **30B MLX** port hits **79.51%** while sustaining ~64 tok/s - arguably today's best speed/quality trade-off for Mac setups.
5️⃣ The **0.6B** micro-model races above 180 tok/s but tops out at **37.56%** - that's why it's not even on the graph (50 % performance cut-off).
All local runs were done with LM Studio on an M4 MacBook Pro, using Qwen's official recommended settings.
**Conclusion:** Quantised 30B models now get you ~98 % of frontier-class accuracy - at a fraction of the latency, cost, and energy. For most local RAG or agent workloads, they're not just good enough - they're the new default.
Well done, Qwen - you really whipped the llama's ass! And to OpenAI: for your upcoming open model, please make it MoE, with toggleable reasoning, and release it in many sizes. *This* is the future!
- 4 replies
posted
an
update
16 days ago
Post
5333
VisionScout — Now with Video Analysis! 🚀
I’m excited to announce a major update to VisionScout, my interactive vision tool that now supports VIDEO PROCESSING, in addition to powerful object detection and scene understanding!
⭐️ NEW: Video Analysis Is Here!
🎬 Upload any video file to detect and track objects using YOLOv8.
⏱️ Customize processing intervals to balance speed and thoroughness.
📊 Get comprehensive statistics and summaries showing object appearances across the entire video.
What else can VisionScout do?
🖼️ Analyze any image and detect 80 object types with YOLOv8.
🔄 Switch between Nano, Medium, and XLarge models for speed or accuracy.
🎯 Filter by object classes (people, vehicles, animals, etc.) to focus on what matters.
📊 View detailed stats on detections, confidence levels, and distributions.
🧠 Understand scenes — interpreting environments and potential activities.
⚠️ Automatically identify possible safety concerns based on detected objects.
What’s coming next?
🔎 Expanding YOLO’s object categories.
⚡ Faster real-time performance.
📱 Improved mobile responsiveness.
My goal:
To bridge the gap between raw detection and meaningful interpretation.
I’m constantly exploring ways to help machines not just "see" but truly understand context — and to make these advanced tools accessible to everyone, regardless of technical background.
Try it now! 🖼️👉 DawnC/VisionScout
If you enjoy VisionScout, a ❤️ Like for this project or feedback would mean a lot and keeps me motivated to keep building and improving!
#ComputerVision #ObjectDetection #VideoAnalysis #YOLO #SceneUnderstanding #MachineLearning #TechForLife
I’m excited to announce a major update to VisionScout, my interactive vision tool that now supports VIDEO PROCESSING, in addition to powerful object detection and scene understanding!
⭐️ NEW: Video Analysis Is Here!
🎬 Upload any video file to detect and track objects using YOLOv8.
⏱️ Customize processing intervals to balance speed and thoroughness.
📊 Get comprehensive statistics and summaries showing object appearances across the entire video.
What else can VisionScout do?
🖼️ Analyze any image and detect 80 object types with YOLOv8.
🔄 Switch between Nano, Medium, and XLarge models for speed or accuracy.
🎯 Filter by object classes (people, vehicles, animals, etc.) to focus on what matters.
📊 View detailed stats on detections, confidence levels, and distributions.
🧠 Understand scenes — interpreting environments and potential activities.
⚠️ Automatically identify possible safety concerns based on detected objects.
What’s coming next?
🔎 Expanding YOLO’s object categories.
⚡ Faster real-time performance.
📱 Improved mobile responsiveness.
My goal:
To bridge the gap between raw detection and meaningful interpretation.
I’m constantly exploring ways to help machines not just "see" but truly understand context — and to make these advanced tools accessible to everyone, regardless of technical background.
Try it now! 🖼️👉 DawnC/VisionScout
If you enjoy VisionScout, a ❤️ Like for this project or feedback would mean a lot and keeps me motivated to keep building and improving!
#ComputerVision #ObjectDetection #VideoAnalysis #YOLO #SceneUnderstanding #MachineLearning #TechForLife
- 2 replies
posted
an
update
21 days ago
Post
2949
VisionScout — Now with Scene Understanding! 🚀
I'm excited to share a major update to VisionScout, my interactive vision tool that combines powerful object detection with emerging scene understanding capabilities! 👀🔍
What can VisionScout do today?
🖼️ Upload any image and detect 80 object types using YOLOv8.
🔄 Instantly switch between Nano, Medium, and XLarge models depending on speed vs. accuracy needs.
🎯 Filter specific classes (people, vehicles, animals, etc.) to focus only on what matters to you.
📊 View detailed statistics on detected objects, confidence levels, and spatial distribution.
⭐️ NEW: Scene understanding layer now added!
- Automatically interprets the scene based on detected objects.
- Uses a combination of rule-based reasoning and CLIP-powered semantic validation.
- Outputs descriptions, possible activities, and even safety concerns.
What’s coming next?
🔎 Expanding YOLO’s object categories.
🎥 Adding video processing and multi-frame object tracking.
⚡ Faster real-time performance.
📱 Improved mobile responsiveness.
My goal:
To make advanced vision tools accessible to everyone, from beginners to experts , while continuing to push for more accurate and meaningful scene interpretation.
Try it yourself! 🖼️
👉 DawnC/VisionScout
If you enjoy VisionScout, feel free to give the project a ❤️, it really helps and keeps me motivated to keep building and improving!
Stay tuned for more updates!
#ComputerVision #ObjectDetection #YOLO #SceneUnderstanding #MachineLearning #TechForLife
I'm excited to share a major update to VisionScout, my interactive vision tool that combines powerful object detection with emerging scene understanding capabilities! 👀🔍
What can VisionScout do today?
🖼️ Upload any image and detect 80 object types using YOLOv8.
🔄 Instantly switch between Nano, Medium, and XLarge models depending on speed vs. accuracy needs.
🎯 Filter specific classes (people, vehicles, animals, etc.) to focus only on what matters to you.
📊 View detailed statistics on detected objects, confidence levels, and spatial distribution.
⭐️ NEW: Scene understanding layer now added!
- Automatically interprets the scene based on detected objects.
- Uses a combination of rule-based reasoning and CLIP-powered semantic validation.
- Outputs descriptions, possible activities, and even safety concerns.
What’s coming next?
🔎 Expanding YOLO’s object categories.
🎥 Adding video processing and multi-frame object tracking.
⚡ Faster real-time performance.
📱 Improved mobile responsiveness.
My goal:
To make advanced vision tools accessible to everyone, from beginners to experts , while continuing to push for more accurate and meaningful scene interpretation.
Try it yourself! 🖼️
👉 DawnC/VisionScout
If you enjoy VisionScout, feel free to give the project a ❤️, it really helps and keeps me motivated to keep building and improving!
Stay tuned for more updates!
#ComputerVision #ObjectDetection #YOLO #SceneUnderstanding #MachineLearning #TechForLife
posted
an
update
28 days ago
Post
4255
I'm excited to introduce VisionScout —an interactive vision tool that makes computer vision both accessible and powerful! 👀🔍
What can VisionScout do right now?
🖼️ Upload any image and detect 80 different object types using YOLOv8.
🔄 Instantly switch between Nano, Medium, and XLarge models depending on your speed vs. accuracy needs.
🎯 Filter specific classes (people, vehicles, animals, etc.) to focus only on what matters to you.
📊 View detailed statistics about detected objects, confidence levels, and spatial distribution.
🎨 Enjoy a clean, intuitive interface with responsive design and enhanced visualizations.
What's next?
I'm working on exciting updates:
- Support for more models
- Video processing and object tracking across frames
- Faster real-time detection
- Improved mobile responsiveness
The goal is to build a complete but user-friendly vision toolkit for both beginners and advanced users.
Try it yourself! 🚀
DawnC/VisionScout
I'd love to hear your feedback , what features would you find most useful? Any specific use cases you'd love to see supported?
Give it a try and let me know your thoughts in the comments! Stay tuned for future updates.
#ComputerVision #ObjectDetection #YOLO #MachineLearning #TechForLife
What can VisionScout do right now?
🖼️ Upload any image and detect 80 different object types using YOLOv8.
🔄 Instantly switch between Nano, Medium, and XLarge models depending on your speed vs. accuracy needs.
🎯 Filter specific classes (people, vehicles, animals, etc.) to focus only on what matters to you.
📊 View detailed statistics about detected objects, confidence levels, and spatial distribution.
🎨 Enjoy a clean, intuitive interface with responsive design and enhanced visualizations.
What's next?
I'm working on exciting updates:
- Support for more models
- Video processing and object tracking across frames
- Faster real-time detection
- Improved mobile responsiveness
The goal is to build a complete but user-friendly vision toolkit for both beginners and advanced users.
Try it yourself! 🚀
DawnC/VisionScout
I'd love to hear your feedback , what features would you find most useful? Any specific use cases you'd love to see supported?
Give it a try and let me know your thoughts in the comments! Stay tuned for future updates.
#ComputerVision #ObjectDetection #YOLO #MachineLearning #TechForLife
reacted to
seawolf2357's
post with ❤️
about 1 month ago
Post
6635
🔥 AgenticAI: The Ultimate Multimodal AI with 16 MBTI Girlfriend Personas! 🔥
Hello AI community! Today, our team is thrilled to introduce AgenticAI, an innovative open-source AI assistant that combines deep technical capabilities with uniquely personalized interaction. 💘
🛠️ MBTI 16 Types SPACES Collections link
seawolf2357/heartsync-mbti-67f793d752ef1fa542e16560
✨ 16 MBTI Girlfriend Personas
Complete MBTI Implementation: All 16 MBTI female personas modeled after iconic characters (Dana Scully, Lara Croft, etc.)
Persona Depth: Customize age groups and thinking patterns for hyper-personalized AI interactions
Personality Consistency: Each MBTI type demonstrates consistent problem-solving approaches, conversation patterns, and emotional expressions
🚀 Cutting-Edge Multimodal Capabilities
Integrated File Analysis: Deep analysis and cross-referencing of images, videos, CSV, PDF, and TXT files
Advanced Image Understanding: Interprets complex diagrams, mathematical equations, charts, and tables
Video Processing: Extracts key frames from videos and understands contextual meaning
Document RAG: Intelligent analysis and summarization of PDF/CSV/TXT files
💡 Deep Research & Knowledge Enhancement
Real-time Web Search: SerpHouse API integration for latest information retrieval and citation
Deep Reasoning Chains: Step-by-step inference process for solving complex problems
Academic Analysis: In-depth approach to mathematical problems, scientific questions, and data analysis
Structured Knowledge Generation: Systematic code, data analysis, and report creation
🖼️ Creative Generation Engine
FLUX Image Generation: Custom image creation reflecting the selected MBTI persona traits
Data Visualization: Automatic generation of code for visualizing complex datasets
Creative Writing: Story and scenario writing matching the selected persona's style
Hello AI community! Today, our team is thrilled to introduce AgenticAI, an innovative open-source AI assistant that combines deep technical capabilities with uniquely personalized interaction. 💘
🛠️ MBTI 16 Types SPACES Collections link
seawolf2357/heartsync-mbti-67f793d752ef1fa542e16560
✨ 16 MBTI Girlfriend Personas
Complete MBTI Implementation: All 16 MBTI female personas modeled after iconic characters (Dana Scully, Lara Croft, etc.)
Persona Depth: Customize age groups and thinking patterns for hyper-personalized AI interactions
Personality Consistency: Each MBTI type demonstrates consistent problem-solving approaches, conversation patterns, and emotional expressions
🚀 Cutting-Edge Multimodal Capabilities
Integrated File Analysis: Deep analysis and cross-referencing of images, videos, CSV, PDF, and TXT files
Advanced Image Understanding: Interprets complex diagrams, mathematical equations, charts, and tables
Video Processing: Extracts key frames from videos and understands contextual meaning
Document RAG: Intelligent analysis and summarization of PDF/CSV/TXT files
💡 Deep Research & Knowledge Enhancement
Real-time Web Search: SerpHouse API integration for latest information retrieval and citation
Deep Reasoning Chains: Step-by-step inference process for solving complex problems
Academic Analysis: In-depth approach to mathematical problems, scientific questions, and data analysis
Structured Knowledge Generation: Systematic code, data analysis, and report creation
🖼️ Creative Generation Engine
FLUX Image Generation: Custom image creation reflecting the selected MBTI persona traits
Data Visualization: Automatic generation of code for visualizing complex datasets
Creative Writing: Story and scenario writing matching the selected persona's style
- 1 reply
reacted to
John6666's
post with 👍
about 1 month ago
Post
7992
I used up my Zero GPU Quota yesterday (about 12 hours ago). At the time, I got a message saying “Retry at 13:45 (approx.)”, but now it's just changed to “Retry at 03:22”.
Anyway, everyone, let's be careful not to use up our Quota...
Related: https://huggingface.co/posts/Keltezaa/754755723533287#67e6ed5e3394f1ed9ca41dbd
Anyway, everyone, let's be careful not to use up our Quota...
Related: https://huggingface.co/posts/Keltezaa/754755723533287#67e6ed5e3394f1ed9ca41dbd
- 1 reply
posted
an
update
about 2 months ago
Post
2580
New in PawMatchAI🐾 : Turn Your Dog Photos into Art!
I’m excited to introduce a brand-new creative feature — Dog Style Transfer is now live on PawMatchAI!
Just upload your dog’s photo and transform it into 5 artistic styles:
🌸 Japanese Anime
📚 Classic Cartoon
🖼️ Oil Painting
🎨 Watercolor
🌆 Cyberpunk
All powered by Stable Diffusion and enhanced with smart prompt tuning to preserve your dog’s unique traits and breed identity , so the artwork stays true to your furry friend.
Whether you're creating a custom portrait or just having fun, this feature brings your pet photos to life in completely new ways.
And here’s a little secret: although it’s designed with dogs in mind, it actually works on any photo — cats, plush toys, even humans. Feel free to experiment!
Results may not always be perfectly accurate, sometimes your photo might come back looking a little different, or even beyond your imagination. But that’s part of the fun! It’s all about creative surprises and letting the AI do its thing.
Try it now: DawnC/PawMatchAI
If this new feature made you smile, a ❤️ for this space would mean a lot.
#AIArt #StyleTransfer #StableDiffusion #ComputerVision #MachineLearning #DeepLearning
I’m excited to introduce a brand-new creative feature — Dog Style Transfer is now live on PawMatchAI!
Just upload your dog’s photo and transform it into 5 artistic styles:
🌸 Japanese Anime
📚 Classic Cartoon
🖼️ Oil Painting
🎨 Watercolor
🌆 Cyberpunk
All powered by Stable Diffusion and enhanced with smart prompt tuning to preserve your dog’s unique traits and breed identity , so the artwork stays true to your furry friend.
Whether you're creating a custom portrait or just having fun, this feature brings your pet photos to life in completely new ways.
And here’s a little secret: although it’s designed with dogs in mind, it actually works on any photo — cats, plush toys, even humans. Feel free to experiment!
Results may not always be perfectly accurate, sometimes your photo might come back looking a little different, or even beyond your imagination. But that’s part of the fun! It’s all about creative surprises and letting the AI do its thing.
Try it now: DawnC/PawMatchAI
If this new feature made you smile, a ❤️ for this space would mean a lot.
#AIArt #StyleTransfer #StableDiffusion #ComputerVision #MachineLearning #DeepLearning
-
- 2 replies
posted
an
update
about 2 months ago
Post
2386
🌐 PawMatchAI Update: Smarter Visualization with Radar Charts! 🐾
I’ve just added a new feature to the project that bridges the gap between breed recognition and real world decision-making:
👉 Radar charts for lifestyle-based breed insights.
🎯 Why This Matters
Choosing the right dog isn’t just about knowing the breed , it’s about how that breed fits into your lifestyle.
To make this intuitive, each breed now comes with a six-dimensional radar chart that reflects:
- Space Requirements
- Exercise Needs
- Grooming Level
- Owner Experience
- Health Considerations
- Noise Behavior
Users can also compare two breeds side-by-side using radar and bar charts — perfect for making thoughtful, informed choices.
💡 What’s Behind It?
All visualizations are directly powered by the same internal database used by the recommendation engine, ensuring consistent, explainable results.
🐶 Try It Out
Whether you're a first-time dog owner or a seasoned canine lover, this update makes it easier than ever to match with your ideal companion.
👉 Explore it here:
🔗 DawnC/PawMatchAI
Thanks for all the support so far, if you find this project helpful or interesting, feel free to leave a ❤️ on the Hugging Face Space!
#AI #ComputerVision #DataVisualization #DeepLearning #DataScience
I’ve just added a new feature to the project that bridges the gap between breed recognition and real world decision-making:
👉 Radar charts for lifestyle-based breed insights.
🎯 Why This Matters
Choosing the right dog isn’t just about knowing the breed , it’s about how that breed fits into your lifestyle.
To make this intuitive, each breed now comes with a six-dimensional radar chart that reflects:
- Space Requirements
- Exercise Needs
- Grooming Level
- Owner Experience
- Health Considerations
- Noise Behavior
Users can also compare two breeds side-by-side using radar and bar charts — perfect for making thoughtful, informed choices.
💡 What’s Behind It?
All visualizations are directly powered by the same internal database used by the recommendation engine, ensuring consistent, explainable results.
🐶 Try It Out
Whether you're a first-time dog owner or a seasoned canine lover, this update makes it easier than ever to match with your ideal companion.
👉 Explore it here:
🔗 DawnC/PawMatchAI
Thanks for all the support so far, if you find this project helpful or interesting, feel free to leave a ❤️ on the Hugging Face Space!
#AI #ComputerVision #DataVisualization #DeepLearning #DataScience
- 4 replies
replied to
their
post
4 months ago
Thank you for your positive feedback and your offer to help with marketing. I truly appreciate the interest in this project!
Naturally, it’s great if more people get to know about this project, as it helps showcase my work. However, at this stage, I don’t have any plans to monetize it. My primary focus remains on career transition into the tech industry, and this project serves as a portfolio piece demonstrating my technical skills.
That said, I’m always open to technical discussions and improvements that could enhance its educational value. If there’s something particularly interesting, I might consider exploring it in the future.
Thanks again for your support and for understanding my current priorities!
replied to
their
post
4 months ago
Thank you for the thorough review of the license changes. After careful consideration, I have decided to fully implement the Apache License 2.0. This update ensures that the project adheres to widely accepted open-source licensing standards while maintaining proper attribution.
The project is now fully under the standard Apache 2.0 license, meaning:
- Full redistribution rights are granted, both for commercial and non-commercial use
- Attribution requirements are clearly defined as per the Apache 2.0 license
- Patent rights are explicitly granted
- No additional restrictions beyond the standard Apache 2.0 terms
I have removed any previous mentions of "personal use" to align with Apache 2.0's unrestricted usage model. The license now fully complies with the standard terms without any additional conditions.
replied to
their
post
4 months ago
Thank you for your valuable insights and suggestions regarding the licensing issues. After careful consideration, I have updated the project's licensing terms to better reflect both the open-source community's needs and the project's purpose.
Initially, I chose a more restrictive license (CC BY-NC-ND 4.0) to protect the project's integrity as part of my career transition portfolio. However, after reflecting on the practical aspects of software licensing and the spirit of open-source collaboration, I decided to revise the terms.
The new license now:
- Allows broader usage, including potential commercial applications
- Maintains core attribution requirements to recognize original contributions
- Simplifies usage while preserving the project's value as a portfolio piece
This update strikes a balance between open-source principles and ensuring proper credit for the work. While it removes previous restrictions, it still requires attribution to acknowledge the original author.
I appreciate your thoughts on the challenges of enforcing restrictions in the software domain. With this new approach, I aim to focus more on proper attribution rather than limiting usage, which I believe aligns better with both community values and the project's intent.
Thanks again for your feedback—it helped me think through this issue more thoroughly.
replied to
their
post
4 months ago
Thank you for your interest in my project and for sharing the Free Software Foundation's philosophy. I appreciate your question about the licensing.
I would like to clarify that my project uses the CC BY-NC-ND 4.0 (Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International) license. This license allows:
- Viewing and learning from the project content
- Sharing the original content (with attribution to me as the original author)
- Use for personal study and academic research purposes
However, it specifically prohibits:
- Commercial use
- Distribution of modified versions
- Creation of derivative works
This differs from traditional free software licenses as it provides more protection for intellectual property rights while still supporting educational and research purposes.
posted
an
update
4 months ago
Post
1277
🌟 PawMatchAI: Making Breed Selection More Intuitive! 🐕
Excited to share the latest breakthrough in my AI-powered companion for finding your perfect furry friend! I've made significant improvements in breed recognition through innovative learning techniques!
✨ What's New?
🎯 Major Recognition Enhancement:
- Implemented ICARL with advanced knowledge distillation, inspired by human learning processes
- Dramatically improved recognition of challenging breeds like Havanese
- Created an intelligent learning system that mimics how expert teachers adapt their teaching style
- Added smart feature protection to maintain recognition accuracy across all breeds
🔬 Technical Innovations:
- Enhanced breed recognition through advanced morphological feature analysis
- Implemented sophisticated feature extraction system for body proportions, head features, tail structure, fur texture, and color patterns
- Added intelligent attention mechanism for dynamic feature focus
- Improved multi-dog detection with enhanced spatial analysis
🎯 Key Features:
- Smart breed recognition powered by biomimetic AI architecture
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Taking inspiration from both AI technology and natural learning processes, this project continues to evolve in making breed selection more accessible while pushing the boundaries of AI capabilities.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ fuel the continuous improvement of this project!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision #TechForLife #ICARL #KnowledgeDistillation
Excited to share the latest breakthrough in my AI-powered companion for finding your perfect furry friend! I've made significant improvements in breed recognition through innovative learning techniques!
✨ What's New?
🎯 Major Recognition Enhancement:
- Implemented ICARL with advanced knowledge distillation, inspired by human learning processes
- Dramatically improved recognition of challenging breeds like Havanese
- Created an intelligent learning system that mimics how expert teachers adapt their teaching style
- Added smart feature protection to maintain recognition accuracy across all breeds
🔬 Technical Innovations:
- Enhanced breed recognition through advanced morphological feature analysis
- Implemented sophisticated feature extraction system for body proportions, head features, tail structure, fur texture, and color patterns
- Added intelligent attention mechanism for dynamic feature focus
- Improved multi-dog detection with enhanced spatial analysis
🎯 Key Features:
- Smart breed recognition powered by biomimetic AI architecture
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Taking inspiration from both AI technology and natural learning processes, this project continues to evolve in making breed selection more accessible while pushing the boundaries of AI capabilities.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ fuel the continuous improvement of this project!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision #TechForLife #ICARL #KnowledgeDistillation
-
- 10 replies
replied to
their
post
5 months ago
Thank you! I'm glad you liked it. I’ll keep working to make it even better!
posted
an
update
5 months ago
Post
2334
🌟 PawMatchAI: Making Breed Selection More Intuitive! 🐕
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! I've made significant architectural improvements to enhance breed recognition accuracy and feature detection.
✨ What's New?
Enhanced breed recognition through advanced morphological feature analysis:
- Implemented a sophisticated feature extraction system that analyzes specific characteristics like body proportions, head features, tail structure, fur texture, and color patterns
- Added an intelligent attention mechanism that dynamically focuses on the most relevant features for each image
- Improved multi-dog detection capabilities through enhanced spatial feature analysis
- Achieved better precision in distinguishing subtle breed characteristics
🎯 Key Features:
Smart breed recognition powered by advanced AI architecture
Visual matching scores with intuitive color indicators
Detailed breed comparisons with interactive tooltips
Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Combining my passion for AI and pets, this project represents another step toward creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ on this space fuel this project's growth!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision #TechForLife
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! I've made significant architectural improvements to enhance breed recognition accuracy and feature detection.
✨ What's New?
Enhanced breed recognition through advanced morphological feature analysis:
- Implemented a sophisticated feature extraction system that analyzes specific characteristics like body proportions, head features, tail structure, fur texture, and color patterns
- Added an intelligent attention mechanism that dynamically focuses on the most relevant features for each image
- Improved multi-dog detection capabilities through enhanced spatial feature analysis
- Achieved better precision in distinguishing subtle breed characteristics
🎯 Key Features:
Smart breed recognition powered by advanced AI architecture
Visual matching scores with intuitive color indicators
Detailed breed comparisons with interactive tooltips
Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Combining my passion for AI and pets, this project represents another step toward creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ on this space fuel this project's growth!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision #TechForLife
-
- 2 replies
posted
an
update
5 months ago
Post
1452
🌟 PawMatchAI: Making Breed Selection More Intuitive! 🐕
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! The breed recommendation system just got a visual upgrade to help you make better decisions.
✨ What's New?
Enhanced breed recognition accuracy through strategic model improvements:
- Upgraded to a fine-tuned ConvNeXt architecture for superior feature extraction
- Implemented progressive layer unfreezing during training
- Optimized data augmentation pipeline for better generalization
- Achieved 8% improvement in breed classification accuracy
🎯 Key Features:
- Smart breed recognition powered by AI
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Combining my passion for AI and pets, this project represents another step toward my goal of creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ on this space fuel this project's growth!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision
See translation
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! The breed recommendation system just got a visual upgrade to help you make better decisions.
✨ What's New?
Enhanced breed recognition accuracy through strategic model improvements:
- Upgraded to a fine-tuned ConvNeXt architecture for superior feature extraction
- Implemented progressive layer unfreezing during training
- Optimized data augmentation pipeline for better generalization
- Achieved 8% improvement in breed classification accuracy
🎯 Key Features:
- Smart breed recognition powered by AI
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Combining my passion for AI and pets, this project represents another step toward my goal of creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ on this space fuel this project's growth!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision
See translation
posted
an
update
5 months ago
Post
1866
🌟 PawMatchAI: Making Breed Selection More Intuitive! 🐕
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! The breed recommendation system just got a visual upgrade to help you make better decisions.
✨ What's New?
The matching system now features color-coded progress bars and helpful tooltips - making it easier than ever to understand how each breed fits your lifestyle preferences! Behind the scenes, I'm continuously improving the breed recognition accuracy and recommendation algorithms.
🎯 Key Features:
- Smart breed recognition powered by AI
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Combining my passion for AI and pets, this project represents another step toward my goal of creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ help shape this ongoing development journey!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! The breed recommendation system just got a visual upgrade to help you make better decisions.
✨ What's New?
The matching system now features color-coded progress bars and helpful tooltips - making it easier than ever to understand how each breed fits your lifestyle preferences! Behind the scenes, I'm continuously improving the breed recognition accuracy and recommendation algorithms.
🎯 Key Features:
- Smart breed recognition powered by AI
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs
💭 Project Vision
Combining my passion for AI and pets, this project represents another step toward my goal of creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.
👉 Try it now: DawnC/PawMatchAI
Your likes ❤️ help shape this ongoing development journey!
#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision