google/owlv2-base-patch16-ensemble
Primitive: /extract · Extract ·
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The OWLv2 model (short for Open-World Localization) was proposed in Scaling Open-Vocabulary Object Detection by Matthias Minderer, Alexey Gritsenko, Neil Houlsby.
MultimodalBounding boxes
Overview
Hardware: — drives latency, throughput & cost
| Size | 155M params |
|---|---|
| Tasks | /extract |
| License | apache-2.0 |
| Latency | 955 ms |
| Throughput | 1.0 mpix/s |
| Cost | — /1M tok |
Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.
Extraction
| Output kinds | Bounding Boxes |
|---|---|
| Inputs | image |
| Max sequence length | — |
Benchmarks
COCO
Object detection on COCO natural images
Corpus: 5,000 Queries: 5,000
default_limit-1000
Performance A10G b1 c4
Detect 0.0 mpix/s
Detect p50 42.1s
Performance L4-SPOT b1 c4
Detect 0.9 mpix/s
Detect p50 901.0ms
Performance L4 b1 c4
Detect 1.1 mpix/s
Detect p50 1.0s
default_limit-100
Performance RTX-4090 b1 c16
Detect 4.3 mpix/s
Detect p50 547.4ms
default
Quality
ap 0.4337
ap50 0.6330
ap75 0.4735
ar 100 0.6083
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