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Model
Author
MobileNetV2 SSD FPN-Lite (320x320 only)
Officially supported
A pre-trained object detection model designed to locate up to 10 objects within an image, outputting a bounding box for each object detected. The model is around 3.7MB in size. It supports an RGB input at 320x320px. For other resolutions, use FOMO or an NVIDIA TAO model.
Edge Impulse
FOMO (Faster Objects, More Objects) MobileNetV2 0.1
Officially supported
An object detection model based on MobileNetV2 (alpha 0.1) designed to coarsely segment an image into a grid of background vs objects of interest. These models are designed to be <100KB in size and support a grayscale or RGB input at any resolution.
Edge Impulse
FOMO (Faster Objects, More Objects) MobileNetV2 0.35
Officially supported
An object detection model based on MobileNetV2 (alpha 0.35) designed to coarsely segment an image into a grid of background vs objects of interest. These models are designed to be <100KB in size and support a grayscale or RGB input at any resolution.
Edge Impulse
efficientdet-lite
Enterprise
efficientdet-lite
Edge Impulse Inc.
YOLOv5 (yolov5n.pt)
Enterprise
YOLOv5 model with yolov5n.pt pretrained weights
Edge Impulse Inc.
YOLOv3
Enterprise
Fine-tune a pretrained YOLOv3 model based on yolov3-tiny.pt
Edge Impulse Inc.
TI YOLOX
Enterprise
Transfer learning model based on yolox_nano_ti_lite_26p1_41p8_checkpoint.pth
Edge Impulse Inc.
mat_akida_nan_testing
Enterprise
testing of nans coming from akida training
Edge Impulse Inc.
coco-cats
Enterprise
coco-cats
Edge Impulse Inc.
raul-edgeai-regnetx-800mf-fpn-bgr-lite
Enterprise
"TI's EDGEAI optimization of the mmdetection regnetx-800mf-fpn-bgr-lite architecture. https://github.com/TexasInstruments/edgeai-mmdetection"
Edge Impulse Inc.
YOLOv5 for Renesas DRP-AI
Community
Transfer learning model using YOLOv5 v5 branch with yolov5s.pt weights. This block is only compatible with Renesas DRP-AI.
Renesas
YOLOv5
Community
Transfer learning model based on Ultralytics YOLOv5 using yolov5n.pt weights, supports RGB input at any resolution (square images only).
Community blocks
YOLOX for TI TDA4VM
Community
TI's EDGEAI YOLOX. https://github.com/TexasInstruments/edgeai-yolox. Outputs ONNX v7 model format both with and without final detect layers using PyTorch 1.7.1.
See the implementation https://github.com/edgeimpulse/example-custom-ml-block-ti-yolox/tree/onnx-v7
Texas Instruments
NVIDIA TAO RetinaNet
Professional
Enterprise
Object detection model with superior performance on smaller objects. Configurable backbones optimized for targets from MCU to GPU. Supports rectangular input. Image width and height must be multiples of 32. Training requires GPU.
Edge Impulse Inc.
NVIDIA TAO YOLOV3
Professional
Enterprise
Object detection model that is fast and accurate. Configurable backbones optimized for targets from MCU to GPU. Supports rectangular input. Image width and height must be multiples of 32. Training requires GPU.
Edge Impulse Inc.
NVIDIA TAO YOLOV4
Professional
Enterprise
Object detection model that is fast and accurate. Configurable backbones optimized for targets from MCU to GPU. Supports rectangular input. Image width and height must be multiples of 32. Training requires GPU.
Edge Impulse Inc.
NVIDIA TAO SSD
Professional
Enterprise
Object detection model for general purpose use. Configurable backbones optimized for targets from MCU to GPU. Supports rectangular input. Image width and height must be multiples of 32. Training requires GPU.
We're always looking for ways to improve Edge Impulse. If you have any feedback, please let us know!
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YEARLY
$400
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MONTHLY
$475
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Additional usage
Professional Plan includes 1,000 compute minutes per month. Additional usage will be charged at $0.10 per minute, billed monthly.
