https://github.com/nobuotsukamoto/benchmarks
TensorFlow, TensorFlow-Lite Pytorch, Torchvision, TensorRT Benchmarks
https://github.com/nobuotsukamoto/benchmarks
benchmarks object-detection pytorch tensorflow tensorflow-lite tensorrt torchvision
Last synced: 5 months ago
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TensorFlow, TensorFlow-Lite Pytorch, Torchvision, TensorRT Benchmarks
- Host: GitHub
- URL: https://github.com/nobuotsukamoto/benchmarks
- Owner: NobuoTsukamoto
- License: mit
- Created: 2021-04-19T13:51:18.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-11-26T11:01:17.000Z (11 months ago)
- Last Synced: 2025-03-30T22:41:31.419Z (6 months ago)
- Topics: benchmarks, object-detection, pytorch, tensorflow, tensorflow-lite, tensorrt, torchvision
- Language: Python
- Homepage:
- Size: 1.44 MB
- Stars: 22
- Watchers: 3
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Benchmarks
## About
Benchmarks such as TensorFlow, TensorFlow-Lite, PyTorch, Torchvision, etc...
## Summary
### HostPC / Google Colaboratory
|Description|Benchmarks|Framework|HW|
|:--|:--|:--|:--|
|[TF2 Detection Models](tensorflow/tf2_detection_model_zoo/local_gtx1070.md)|AP, Latency|TensorFlow
XLA Auto-clustering|Local PC GTX1070|
|[TF2 Detection Models](tensorflow/tf2_detection_model_zoo/colab_p100.md)|AP, Latency|TensorFlow
TF-TRT
XLA Auto-clustering|Google Colab Tesla P100|
|[TF2 Detection Models](tensorflow/tf2_detection_model_zoo/colab_v100.md)|AP, Latency|TensorFlow|Google Colab Tesla V100|
|[TF2 Detection Models](tensorflow/tf2_detection_model_zoo/v100_vs_p100_vs_gtx1070.md)|Latency|TensorFlow|V100 vs P100 vs GTX1070|
|[Torchvision detection models](pytorch/torchvision/README.md)|AP, Latency,
YouTube video|PyTorch, Torchvision|Local PC GTX1070|
### Raspberry Pi / Coral Dev Board + EdgeTPU
|Description|Benchmarks|Framework|HW|
|:--|:--|:--|:--|
|[TensorFlow 1 Detection Model Zoo](tensorflow/lite/tf1_detection_model_zoo/raspi.md)|AP, Latency|TensorFlow Lite
XNNPACK delegate
ARM NN delegate
EdgeTPU delegate|Raspberry Pi 2, 3, 4
Coral USB Accelerator|
|[EdgeTPU Models](tensorflow/lite/tf1_detection_model_zoo/devboard.md)|Latency|TensorFlow Lite
EdgeTPU delegate|Coral Dev Board|
|[EfficientDet-Lite](tensorflow/lite/efficentdet/efficientdet.md)|AP, Latency|TensorFlow Lit
XNNPACK delegate
ARM NN delegate
EdgeTPU delegate|Raspberry Pi 2, 3, 4
Coral USB Accelerator|
|[YOLOX TensorFlow LiteM](tensorflow/lite/yolox)|AP, Latency|TensorFlow Lite
XNNPACK delegate|Raspberry Pi 4|
|[TF-Lite SpaghettiNet EdgeTpu Latency vs max_detections](tensorflow/lite/spaghettinet/latency_vs_map.md)|AP, Latency|TensorFlow Lite EdgeTPU delegate|Raspberry Pi 4 + Coral USB Accelerator
Coral Dev Board|
### Jetson
|Description|Benchmarks|Framework|HW|
|:--|:--|:--|:--|
|[TensorRT EfficientDet and TensorFlow Object Detection API](tensorrt/jetson/detection/README.md)| Latency,
YouTube video | TensorRT | Jetson Nano |
|[TensorRT Autoseg-EdgeTPU and
DeepLab v3+ MobilenetEdgeTPUV2](tensorrt/jetson/deeplabv3_edgetpuv2/deeplabv3_edgetpuv2.md)| Latency,
YouTube video | TensorRT | Jetson Nano |
|[TensorRT Fast-SCNN](tensorrt/jetson/fast_scnn/README.md)| Latency,
YouTube video | TensorRT | Jetson Nano |
|[TensorRT Ultra-Fast-Lane-Detection](tensorrt/jetson/ultra_falst_lane_detection/README.md)| Latency,
YouTube video | TensorRT | Jetson Nano |
### TensorFlow Lite on RISC-V SoC
|Description|Benchmarks|Framework|HW|
|:--|:--|:--|:--|
|[Sipeed Lichee RV Dock Allwinner D1](tensorflow/lite/riscv/lichee_rv_dock/README.md) | Latency | TensorFlow Lite | CPU |
|[StarFive VisionFive 2](tensorflow/lite/riscv/visionfive2/README.md) | Latency | TensorFlow Lite | CPU, GPU |
## Reference
- [TensorFlow 1 Detection Model Zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md)
- [TensorFlow 2 Detection Model Zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2_detection_zoo.md)
- [TensorFlow XLA Auto-clustering](https://www.tensorflow.org/xla#auto-clustering)
- [TF-TRT (tensorflow / tensorrt)](https://github.com/tensorflow/tensorrt)
- FP32 XNNPACK: [PINTO0309/TensorflowLite-bin](https://github.com/PINTO0309/TensorflowLite-bin)
- [EfficientDet](https://github.com/google/automl/tree/master/efficientdet)
- [The Arm NN TensorFlow Lite delegate](https://github.com/ARM-software/armnn/tree/branches/armnn_21_05/delegate)
- [ARM Compute Librarry](https://github.com/ARM-software/ComputeLibrary)
- [Coral EdgeTPU](https://coral.ai/)
- [PINTO0309/Bazel_bin](https://github.com/PINTO0309/Bazel_bin)
- [PyTorch](https://pytorch.org/)
- [Torchvision](https://pytorch.org/vision/stable/)
- [TensorRT](https://github.com/NVIDIA/TensorRT)
- [meta-tensorflow-lite](https://github.com/NobuoTsukamoto/meta-tensorflow-lite)
- [Yocto Project](https://www.yoctoproject.org/)