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Image Segmentation Models for NVIDIA Jetson
Explore our recommended image segmentation models for use on NVIDIA Jetson devices.
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Object Detection
Classification
Instance Segmentation
Semantic Segmentation
Keypoint Detection
Vision Language
OCR
Pose Estimation
Chart Question Answering
Document Question Answering (DocQA)
Video Classification
Open Vocabulary Object Detection
Multi-Label Classification
Region Proposal
Phrase Grounding
Referring Expression Segmentation
Zero Shot Segmentation
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Foundation Vision
Multimodal Vision
LLMS with Vision Capabilities
Image Embedding
Real-Time Vision
Zero-shot Detection
Image Captioning
Image Similarity
Image Tagging
Visual Question Answering
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Deploy select models (i.e. YOLOv8, CLIP) using the Roboflow Hosted API, or your own hardware using
Roboflow Inference
.
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models.
YOLOv8 Instance Segmentation
The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks.
Instance Segmentation
Deploy with Roboflow
YOLOv9
YOLOv9 is an object detection model architecture released on February 21st, 2024.
Object Detection
Deploy with Roboflow
YOLOv5
A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results.
Object Detection
Deploy with Roboflow
YOLO11
YOLO11 is a computer vision model that you can use for object detection, segmentation, and classification.
Object Detection
Deploy with Roboflow
YOLOv7 Instance Segmentation
YOLOv7 Instance Segmentation lets you perform segmentation tasks with the YOLOv7 model.
Instance Segmentation
Deploy with Roboflow
YOLOv7
YOLOv7 is a state of the art object detection model.
Object Detection
Deploy with Roboflow
YOLOv9 Image Segmentation
Deploy with Roboflow
Florence 2 Image Segmentation
Referring Expression Segmentation
Deploy with Roboflow
Visual Question Answering
Image Tagging
Image Similarity
Image Captioning
Zero-shot Detection
Real-Time Vision
Image Embedding
LLMS with Vision Capabilities
Multimodal Vision
Foundation Vision