PyTorch Image Object Detection Faster R-CNN ResNet-50 Batch CPU

Model: PyTorch Image Object Detection — Faster R-CNN ResNet-50 FPN (pretrained on COCO) Accelerator: CPU only Host: 50 × n1-standard-4 (4 vCPUs, 15 GB RAM)

This batch pipeline performs object detection using an open-source PyTorch Faster R-CNN ResNet-50 FPN model on CPU. It reads image URIs from GCS, decodes and preprocesses images, and runs batched inference with a fixed batch size.

The following graphs show various metrics when running PyTorch Image Object Detection Faster R-CNN ResNet-50 Batch CPU pipeline. See the glossary for definitions.

Full pipeline implementation is available here.

What is the estimated cost to run the pipeline?

RunTime and EstimatedCost

How has various metrics changed when running the pipeline for different Beam SDK versions?

AvgThroughputBytesPerSec by Version

AvgThroughputElementsPerSec by Version

How has various metrics changed over time when running the pipeline?

AvgThroughputBytesPerSec by Date

AvgThroughputElementsPerSec by Date