Difference on model outputs (tflite, openvino IR, and Onnx) in model 227_face-detection-adas-0001

[saeidn95]

Issue Type

Feature Request

OS

Ubuntu

OS architecture

x86_64

Programming Language

Python

Framework

OpenVINO

Model name and Weights/Checkpoints URL

227_face-detection-adas-0001 https://github.com/PINTO0309/PINTO_model_zoo/tree/main/227_face-detection-adas-0001

Description

I am looking at the outputs of the 3 versions of the model tflite, onnx and IR openvino. The openvino has 3 outputs and ftlite and onnx each have two outputs. How are they identical to each other?

openvino xlm : [<Output: names[mbox_loc] shape[1,40448] type: f32>, <Output: names[mbox_conf_flatten] shape[1,20224] type: f32>, <Output: names[mbox_priorbox] shape[1,2,40448] type: f32>]

tflite: [<Output: names[StatefulPartitionedCall:0] shape[1,40448] type: f32>, <Output: names[StatefulPartitionedCall:1] shape[1,20224] type: f32>]

onnx: [<Output: names[tf.identity] shape[1,40448] type: f32>, <Output: names[tf.identity_1] shape[1,20224] type: f32>]

Relevant Log Output

-

URL or source code for simple inference testing code