Skip to content
Flow Like logo Flow Like Docs

Image Classification Node

AI/ML/ONNX

Image Classification

Image Classification with ONNX-Models. Download models from: MobileNetV2 (https://github.com/onnx/models/tree/main/validated/vision/classification/mobilenet), SqueezeNet (https://github.com/onnx/models/tree/main/validated/vision/classification/squeezenet), ResNet (https://github.com/onnx/models/tree/main/validated/vision/classification/resnet), EfficientNet (https://github.com/onnx/models/tree/main/validated/vision/classification/efficientnet-lite4)

image_classificationonnx
Inputs7
Outputs2
Security exposure10/10
Packageonnx

Ratings

Scores range from 0 to 10. Higher values mean more impact, exposure, or operational weight.

No score metadata has been set for this node yet.

Input Pins

7

Input

Execution
exec_in

Initiate Execution

Model

Struct
model

ONNX Model Session

NodeOnnxSessionNodeOnnxSession1 fields
session_refstringrequired

Cache ID for Session

Schema enforced

Image

Struct
image_in

Image Object

NodeImageNodeImage1 fields
image_refstringrequired
Schema enforced

Mean

Float Array
mean

Image Mean for Normalization (per channel)

Default [0.485,0.456,0.406]

Std

Float Array
std

Image Standard Deviation for Normalization (per channel)

Default [0.229,0.224,0.225]

Crop

Float
crop_pct

Center Crop Percentage

Default 0.875
Range 0 to 1

Softmax?

Boolean
softmax

Scale Outputs with Softmax

Default true

Output Pins

2

Output

Execution
exec_out

Done with the Execution

Predictions

Struct Array
predictions

Class Predictions

ClassPredictionClassPrediction3 fields
class_idxinteger:uint32required

Class index (0-based)

format uint32min 0
scorenumber:floatrequired

Confidence score (typically 0.0-1.0)

format float
labelstring | null

Optional human-readable class label

Node Info

Internal name
image_classification
Category
AI/ML/ONNX
Version
1