55
VisionScout
🛰
Object Detection & Scene Understanding for Images and Video
Eric Chung PRO
DawnC
AI & ML interests
Computer Vision, LLM, Hybrid Architectures, MultiModel
Recent Activity
updated
a Space
about 14 hours ago
DawnC/VisionScout
upvoted
a
changelog
about 18 hours ago
New Inference Providers Dashboard
posted
an
update
9 days ago
VisionScout Major Update: Enhanced Precision Through Multi-Modal AI Integration
I'm excited to share significant improvements to VisionScout that substantially enhance accuracy and analytical capabilities.
⭐️ Key Enhancements
- CLIP Zero-Shot Landmark Detection: The system now identifies famous landmarks and architectural features without requiring specific training data, expanding scene understanding beyond generic object detection.
- Places365 Environmental Classification: Integration of MIT's Places365 model provides robust scene baseline classification across 365 categories, significantly improving lighting analysis accuracy and overall scene identification precision.
- Enhanced Multi-Modal Fusion: Advanced algorithms now dynamically combine insights from YOLOv8, CLIP, and Places365 to optimize accuracy across diverse scenarios.
- Refined LLM Narratives: Llama 3.2 integration continues to transform analytical data into fluent, contextually rich descriptions while maintaining strict factual accuracy.
🎯 Future Development Focus
Accuracy remains the primary development priority, with ongoing enhancements to multi-modal fusion capabilities. Future work will advance video analysis beyond current object tracking foundations to include comprehensive temporal scene understanding and dynamic narrative generation.
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 #MultiModel #TechForLife
Organizations
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DawnC's activity
updated
a
Space
about 14 hours ago
upvoted
a
changelog
about 18 hours ago
Changelog
New Inference Providers Dashboard
•
31
posted
an
update
9 days ago
Post
3190
VisionScout Major Update: Enhanced Precision Through Multi-Modal AI Integration
I'm excited to share significant improvements to VisionScout that substantially enhance accuracy and analytical capabilities.
⭐️ Key Enhancements
- CLIP Zero-Shot Landmark Detection: The system now identifies famous landmarks and architectural features without requiring specific training data, expanding scene understanding beyond generic object detection.
- Places365 Environmental Classification: Integration of MIT's Places365 model provides robust scene baseline classification across 365 categories, significantly improving lighting analysis accuracy and overall scene identification precision.
- Enhanced Multi-Modal Fusion: Advanced algorithms now dynamically combine insights from YOLOv8, CLIP, and Places365 to optimize accuracy across diverse scenarios.
- Refined LLM Narratives: Llama 3.2 integration continues to transform analytical data into fluent, contextually rich descriptions while maintaining strict factual accuracy.
🎯 Future Development Focus
Accuracy remains the primary development priority, with ongoing enhancements to multi-modal fusion capabilities. Future work will advance video analysis beyond current object tracking foundations to include comprehensive temporal scene understanding and dynamic narrative generation.
Try it out 👉 DawnC/VisionScout
If you find this update valuable, a Like❤️ or comment means a lot!
#LLM #ComputerVision #MachineLearning #MultiModel #TechForLife
I'm excited to share significant improvements to VisionScout that substantially enhance accuracy and analytical capabilities.
⭐️ Key Enhancements
- CLIP Zero-Shot Landmark Detection: The system now identifies famous landmarks and architectural features without requiring specific training data, expanding scene understanding beyond generic object detection.
- Places365 Environmental Classification: Integration of MIT's Places365 model provides robust scene baseline classification across 365 categories, significantly improving lighting analysis accuracy and overall scene identification precision.
- Enhanced Multi-Modal Fusion: Advanced algorithms now dynamically combine insights from YOLOv8, CLIP, and Places365 to optimize accuracy across diverse scenarios.
- Refined LLM Narratives: Llama 3.2 integration continues to transform analytical data into fluent, contextually rich descriptions while maintaining strict factual accuracy.
🎯 Future Development Focus
Accuracy remains the primary development priority, with ongoing enhancements to multi-modal fusion capabilities. Future work will advance video analysis beyond current object tracking foundations to include comprehensive temporal scene understanding and dynamic narrative generation.
Try it out 👉 DawnC/VisionScout
If you find this update valuable, a Like❤️ or comment means a lot!
#LLM #ComputerVision #MachineLearning #MultiModel #TechForLife
replied to
their
post
23 days ago
Glad to hear !
posted
an
update
24 days ago
Post
2569
🚀 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
28 days ago
Post
3474
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 🔥
28 days ago
Post
7182
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
updated
a
Space
29 days ago
posted
an
update
29 days ago
Post
5341
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
about 1 month ago
Post
2954
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
about 1 month ago
Post
4257
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
liked
a
Space
about 1 month ago
published
a
Space
about 1 month ago
updated
2
Spaces
about 2 months ago
reacted to
seawolf2357's
post with ❤️
about 2 months ago
Post
6663
🔥 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 2 months ago
Post
9390
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