VLM-Seek
An open-source visual language model that supports open-vocabulary object detection described in natural language. It incorporates a None mechanism that explicitly returns a not-found result when a target object is absent, making it suitable for industrial vision inspection and patrol scenarios.
Timeline (last 90 days)
VLM-Seek supports visual localization by describing targets in natural language, without needing to pre-define targets as fixed categories.
VLM-Seek incorporates a None mechanism that directly returns a not-found result when no target matching the description exists in the candidate regions, rather than forcibly drawing an incorrect bounding box.
Deploying VLM-Seek requires three things: inference code, model weights, and region detector weights.
VLM-Seek's inference code can be pulled from the official GitHub repository, while the model weights and region detector weights can be downloaded from the ModelScope community.
VLM-Seek belongs to open-vocabulary object detection, which is fundamentally different from fixed-category detectors such as YOLO and Faster R-CNN.
VLM-Seek adopts a two-stage architecture in which a region detector first generates candidate regions, and then a vision-language model determines which region best matches the text description.
VLM-Seek can be deployed either as a local private deployment or by calling a public cloud API; the former is suited for businesses with high data security requirements, while the latter is suited for rapid integration.
All Facts (7)
VLM-Seek supports visual localization by describing targets in natural language, without needing to pre-define targets as fixed categories.
50%UnverifiedVLM-Seek incorporates a None mechanism that directly returns a not-found result when no target matching the description exists in the candidate regions, rather than forcibly drawing an incorrect bounding box.
50%UnverifiedDeploying VLM-Seek requires three things: inference code, model weights, and region detector weights.
50%UnverifiedVLM-Seek's inference code can be pulled from the official GitHub repository, while the model weights and region detector weights can be downloaded from the ModelScope community.
50%UnverifiedVLM-Seek belongs to open-vocabulary object detection, which is fundamentally different from fixed-category detectors such as YOLO and Faster R-CNN.
50%UnverifiedVLM-Seek adopts a two-stage architecture in which a region detector first generates candidate regions, and then a vision-language model determines which region best matches the text description.
50%UnverifiedVLM-Seek can be deployed either as a local private deployment or by calling a public cloud API; the former is suited for businesses with high data security requirements, while the latter is suited for rapid integration.
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