{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"reddit-1su7bnx","slug":"deepseek-v4-people","name":"Deepseek v4 people","type":"model","url":"https://i.redd.it/obqgr0phx2xg1.jpeg","page_url":"https://unfragile.ai/deepseek-v4-people","categories":["llm-apis"],"tags":["localllama"],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"pending_review","verified":false},"capabilities":[{"id":"reddit-1su7bnx__cap_0","uri":"capability://image.visual.people.detection.and.recognition","name":"people detection and recognition","description":"This capability employs advanced neural network architectures optimized for image processing to identify and recognize individuals in images. It utilizes a combination of convolutional neural networks (CNNs) and transformer models to enhance accuracy and speed in detecting faces and features, allowing for real-time processing. The model is trained on diverse datasets to improve its robustness against variations in lighting, angles, and occlusions, making it distinct in its ability to handle complex scenarios.","intents":["How can I detect and recognize people in images for my application?","What model should I use for real-time face recognition in my security system?","Can I integrate a people detection feature into my mobile app?"],"best_for":["developers building security and surveillance applications","researchers in computer vision","teams creating social media platforms with tagging features"],"limitations":["Performance may degrade with low-resolution images or extreme angles, requiring high-quality input for best results.","Limited to detecting faces and may not recognize individuals in crowded scenes."],"requires":["Python 3.8+","TensorFlow 2.6+","OpenCV 4.5+"],"input_types":["image"],"output_types":["structured data (JSON with coordinates and IDs)"],"categories":["image-visual","computer-vision"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"reddit-1su7bnx__cap_1","uri":"capability://image.visual.image.preprocessing.for.enhanced.recognition","name":"image preprocessing for enhanced recognition","description":"This capability includes a suite of image preprocessing techniques such as normalization, histogram equalization, and noise reduction to prepare images for optimal recognition performance. By applying these techniques before feeding images into the recognition model, it ensures that variations in image quality do not adversely affect detection accuracy. The preprocessing pipeline is customizable, allowing users to adjust parameters based on their specific use cases.","intents":["How can I improve the quality of images before processing them for recognition?","What preprocessing steps should I take to enhance face detection accuracy?","Can I automate image enhancement for bulk processing in my application?"],"best_for":["developers focused on improving model accuracy","data scientists working with image datasets","teams developing applications requiring high recognition rates"],"limitations":["Preprocessing may introduce latency, especially with large batches of images, requiring optimization for real-time applications.","Not all preprocessing techniques are suitable for every type of image."],"requires":["Python 3.8+","OpenCV 4.5+"],"input_types":["image"],"output_types":["image (enhanced)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"reddit-1su7bnx__cap_2","uri":"capability://image.visual.multi.person.tracking","name":"multi-person tracking","description":"This capability enables the simultaneous tracking of multiple individuals across video frames using a combination of object detection and tracking algorithms. It employs techniques like Kalman filtering and optical flow to maintain identity consistency, allowing for accurate tracking even when individuals occlude each other. The model is designed to operate in real-time, making it suitable for applications in surveillance and event monitoring.","intents":["How can I track multiple people in a video stream for my security application?","What tools do I need to implement real-time tracking of individuals?","Can I integrate multi-person tracking into my existing video processing pipeline?"],"best_for":["security developers implementing surveillance systems","event organizers needing crowd monitoring solutions","researchers studying human behavior in public spaces"],"limitations":["Tracking accuracy may decrease in crowded environments or with rapid movements, necessitating fine-tuning for specific scenarios.","Requires significant computational resources for real-time processing."],"requires":["Python 3.8+","OpenCV 4.5+","TensorFlow 2.6+"],"input_types":["video"],"output_types":["structured data (JSON with tracking IDs and coordinates)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":45,"verified":false,"data_access_risk":"low","permissions":["Python 3.8+","TensorFlow 2.6+","OpenCV 4.5+"],"failure_modes":["Performance may degrade with low-resolution images or extreme angles, requiring high-quality input for best results.","Limited to detecting faces and may not recognize individuals in crowded scenes.","Preprocessing may introduce latency, especially with large batches of images, requiring optimization for real-time applications.","Not all preprocessing techniques are suitable for every type of image.","Tracking accuracy may decrease in crowded environments or with rapid movements, necessitating fine-tuning for specific scenarios.","Requires significant computational resources for real-time processing.","builder identity is not verified yet","artifact is still pending review","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.9,"quality":0.06,"ecosystem":0.18,"match_graph":0.25,"freshness":0.5,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"pending_review","updated_at":"2026-05-24T12:16:25.061Z","last_scraped_at":"2026-05-04T07:50:54.765Z","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=deepseek-v4-people","compare_url":"https://unfragile.ai/compare?artifact=deepseek-v4-people"}},"signature":"a1Gxlq+b7h9a8q06e7O82DeeNtFWPO27R633voDGS0txlxFz6Iw4eb1XjEIG/JyU5/ixwSuZd4mEhDmdeu+HCg==","signedAt":"2026-06-22T01:21:10.500Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/deepseek-v4-people","artifact":"https://unfragile.ai/deepseek-v4-people","verify":"https://unfragile.ai/api/v1/verify?slug=deepseek-v4-people","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"}}