{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"hf-space-zcxu-eric--magicanimate","slug":"zcxu-eric--magicanimate","name":"magicanimate","type":"webapp","url":"https://huggingface.co/spaces/zcxu-eric/magicanimate","page_url":"https://unfragile.ai/zcxu-eric--magicanimate","categories":["automation"],"tags":["gradio","region:us"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"hf-space-zcxu-eric--magicanimate__cap_0","uri":"capability://image.visual.motion.guided.video.animation.synthesis","name":"motion-guided video animation synthesis","description":"Generates animated video sequences from static images by accepting motion guidance (typically from reference videos or motion vectors). The system uses diffusion-based video generation with temporal consistency constraints, processing input images through a latent space representation and applying motion conditioning to produce frame-by-frame animations that preserve spatial coherence while following the specified motion trajectory.","intents":["I want to animate a static portrait photo by providing a reference video showing the desired motion","I need to generate a short video clip from a single image with controlled motion patterns","I want to create character animations by specifying motion guidance without manual keyframing"],"best_for":["Content creators building animation pipelines without 3D modeling expertise","Researchers prototyping video generation with motion conditioning","Teams automating character animation from static assets"],"limitations":["Requires clear motion reference input; ambiguous or complex multi-object motion may produce inconsistent results","Output video length and quality depend on computational resources available on HuggingFace Spaces (typically 5-10 second clips)","Motion guidance must be spatially aligned with input image; misalignment degrades animation quality","No fine-grained control over individual object trajectories; motion is applied globally"],"requires":["Static image input (PNG, JPG, WebP format)","Motion reference (video file or motion vector data)","Modern web browser with WebGL support for Gradio interface","Internet connection to HuggingFace Spaces infrastructure"],"input_types":["image (static photograph or artwork)","video (reference motion guidance)","motion vectors (optional, if supported)"],"output_types":["video (MP4 or WebM format)","frame sequence (PNG or JPG)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-zcxu-eric--magicanimate__cap_1","uri":"capability://automation.workflow.web.based.interactive.animation.preview","name":"web-based interactive animation preview","description":"Provides a Gradio-based web interface for real-time parameter adjustment and animation preview without local installation. The interface streams processing status updates and renders output video directly in the browser, leveraging HuggingFace Spaces' containerized execution environment to handle GPU-accelerated inference while maintaining responsive UI feedback through WebSocket-based status polling.","intents":["I want to experiment with animation parameters without setting up local dependencies","I need to quickly preview animation results before downloading or integrating into my pipeline","I want to share animation generation capabilities with non-technical stakeholders via a shareable link"],"best_for":["Non-technical users exploring animation capabilities without CLI/SDK knowledge","Teams collaborating on animation parameters through shared web links","Researchers prototyping without local GPU infrastructure"],"limitations":["Processing speed depends on HuggingFace Spaces queue and resource availability; peak hours may introduce 5-30 second delays","No persistent session state; parameters reset between page refreshes","Limited to Gradio's UI component library; advanced parameter controls may be simplified","Output files stored temporarily; no automatic archival or version history"],"requires":["Modern web browser (Chrome, Firefox, Safari, Edge)","JavaScript enabled for Gradio interface rendering","Stable internet connection to HuggingFace Spaces","No local GPU required (inference runs on Spaces infrastructure)"],"input_types":["image (uploaded via web form)","video (uploaded via web form)","text parameters (motion intensity, duration, etc.)"],"output_types":["video (streamed to browser)","status messages (real-time processing updates)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-zcxu-eric--magicanimate__cap_2","uri":"capability://automation.workflow.batch.animation.generation.with.queue.management","name":"batch animation generation with queue management","description":"Processes multiple animation requests sequentially through HuggingFace Spaces' built-in job queue system, automatically managing GPU resource allocation and preventing concurrent inference conflicts. The system queues requests, tracks processing status per submission, and returns results asynchronously, enabling users to submit multiple animation jobs without blocking on individual completions.","intents":["I want to generate animations for 10+ images in a single session without manual resubmission","I need to understand processing time and queue position before my animation starts","I want to submit animations and check results later without keeping the browser tab open"],"best_for":["Content creators processing image libraries into animated sequences","Batch processing workflows in automated pipelines","Users with variable internet connectivity who need asynchronous job submission"],"limitations":["Queue position depends on concurrent user load; no priority system or SLA guarantees","Results expire after a fixed period (typically 24-48 hours on HuggingFace Spaces); no persistent storage","No batch API endpoint; each submission requires separate web form interaction or API call","Queue status visibility limited to estimated position; no detailed resource utilization metrics"],"requires":["HuggingFace Spaces account (free tier sufficient)","Web browser or HTTP client for API requests","Patience for queue wait times during peak usage"],"input_types":["image (multiple submissions)","video (multiple submissions)"],"output_types":["video (asynchronous delivery)","queue status (JSON or HTML)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-zcxu-eric--magicanimate__cap_3","uri":"capability://image.visual.motion.reference.video.analysis.and.extraction","name":"motion reference video analysis and extraction","description":"Analyzes uploaded reference videos to extract motion patterns, optical flow, or pose keypoints that condition the animation synthesis. The system processes video frames through computer vision models (likely pose estimation or optical flow networks) to derive motion guidance vectors, which are then applied to the static input image during diffusion-based generation.","intents":["I want to extract motion from a reference video and apply it to a different image","I need to understand what motion patterns the system extracted from my reference video","I want to use a dancer's motion on a different character without manual annotation"],"best_for":["Animation artists transferring motion between characters","Researchers studying motion transfer in video synthesis","Content creators remixing motion across different subjects"],"limitations":["Motion extraction accuracy depends on video clarity and lighting; low-quality references produce degraded animations","Pose-based motion extraction may fail on non-humanoid subjects or complex articulated objects","Temporal resolution limited by video frame rate; high-speed motion may be undersampled","No visualization of extracted motion vectors; users cannot inspect or edit motion guidance before synthesis"],"requires":["Reference video file (MP4, WebM, or AVI format)","Video duration typically 2-10 seconds for optimal results","Clear subject visibility in reference video (good lighting, minimal occlusion)"],"input_types":["video (reference motion source)"],"output_types":["motion vectors (internal representation)","pose keypoints (if pose-based extraction)","optical flow maps (if flow-based extraction)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-zcxu-eric--magicanimate__cap_4","uri":"capability://image.visual.temporal.consistency.enforcement.across.frames","name":"temporal consistency enforcement across frames","description":"Maintains spatial and appearance coherence across generated video frames through latent-space temporal constraints and cross-frame attention mechanisms. The diffusion model applies temporal smoothing and consistency losses during generation, ensuring that object positions, lighting, and textures remain stable across the animation sequence rather than flickering or drifting.","intents":["I want smooth, flicker-free animations without jittery artifacts between frames","I need consistent character appearance throughout the animation despite motion changes","I want to avoid temporal aliasing or strobing effects in fast-motion sequences"],"best_for":["Professional animation pipelines requiring broadcast-quality output","Content creators sensitive to visual artifacts in social media content","Researchers studying temporal coherence in diffusion-based video generation"],"limitations":["Temporal consistency constraints increase inference time by 20-40% compared to frame-independent generation","Extreme motion or occlusions may break temporal coherence despite constraints","No user control over consistency strength; fixed to model defaults","Consistency enforcement may over-smooth fine details or suppress subtle motion"],"requires":["Diffusion model with temporal attention layers (architecture-dependent)","Sufficient GPU memory for cross-frame attention computation (typically 8GB+ VRAM)"],"input_types":["image (static input)","motion guidance (reference video or vectors)"],"output_types":["video (temporally consistent frames)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hf-space-zcxu-eric--magicanimate__cap_5","uri":"capability://automation.workflow.open.source.model.deployment.on.huggingface.infrastructure","name":"open-source model deployment on huggingface infrastructure","description":"Deploys the magicanimate model as a public, open-source application on HuggingFace Spaces, providing free GPU-accelerated inference without requiring users to clone repositories or manage dependencies. The deployment uses Docker containerization and HuggingFace's managed GPU allocation, automatically scaling inference based on demand while maintaining reproducibility through version-pinned dependencies.","intents":["I want to try the model without installing Python, CUDA, or managing local dependencies","I need to integrate magicanimate into my workflow via a public API or web interface","I want to contribute improvements or fork the model for my own use case"],"best_for":["Researchers and developers exploring the model without local GPU access","Open-source contributors building on top of magicanimate","Teams evaluating the model before committing to local deployment"],"limitations":["Inference speed limited by HuggingFace Spaces GPU tier (typically T4 or A100); slower than high-end local GPUs","Queue wait times during peak usage; no guaranteed SLA","Temporary storage only; outputs deleted after 24-48 hours","No fine-tuning or custom model weights; limited to pre-trained checkpoint"],"requires":["Internet connection to HuggingFace Spaces","No local dependencies or GPU required","Free HuggingFace account (optional, for higher rate limits)"],"input_types":["image","video"],"output_types":["video"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":23,"verified":false,"data_access_risk":"low","permissions":["Static image input (PNG, JPG, WebP format)","Motion reference (video file or motion vector data)","Modern web browser with WebGL support for Gradio interface","Internet connection to HuggingFace Spaces infrastructure","Modern web browser (Chrome, Firefox, Safari, Edge)","JavaScript enabled for Gradio interface rendering","Stable internet connection to HuggingFace Spaces","No local GPU required (inference runs on Spaces infrastructure)","HuggingFace Spaces account (free tier sufficient)","Web browser or HTTP client for API requests"],"failure_modes":["Requires clear motion reference input; ambiguous or complex multi-object motion may produce inconsistent results","Output video length and quality depend on computational resources available on HuggingFace Spaces (typically 5-10 second clips)","Motion guidance must be spatially aligned with input image; misalignment degrades animation quality","No fine-grained control over individual object trajectories; motion is applied globally","Processing speed depends on HuggingFace Spaces queue and resource availability; peak hours may introduce 5-30 second delays","No persistent session state; parameters reset between page refreshes","Limited to Gradio's UI component library; advanced parameter controls may be simplified","Output files stored temporarily; no automatic archival or version history","Queue position depends on concurrent user load; no priority system or SLA guarantees","Results expire after a fixed period (typically 24-48 hours on HuggingFace Spaces); no persistent storage","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.22,"ecosystem":0.36,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.325Z","last_scraped_at":"2026-05-03T14:22:48.012Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=zcxu-eric--magicanimate","compare_url":"https://unfragile.ai/compare?artifact=zcxu-eric--magicanimate"}},"signature":"k4lNoUj64lhML5dEzgUFhUOuhyLqR9Nwq9Cc6+0EXbd+AeJauJb3zA7SumPi6WhNhPBRE1LRmAp6Cybe4rGZBw==","signedAt":"2026-06-20T10:52:00.413Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/zcxu-eric--magicanimate","artifact":"https://unfragile.ai/zcxu-eric--magicanimate","verify":"https://unfragile.ai/api/v1/verify?slug=zcxu-eric--magicanimate","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}