MobileNetV3-Small — AX650 Image Classification

MobileNetV3-Small (ImageNet-1k, 1000 classes) compiled to AX650 AXMODEL via Pulsar2.

Model

Item	Value
Architecture	MobileNetV3-Small 100
Source	timm/mobilenetv3_small_100.lamb_in1k
Task	Image Classification (1000 cls)
Input	224×224 BGR, uint8→float [0,1]
Chip	AX650N (NPU3)
Quantization	INT8
Size	3.3 MB
Board	BSP 3.10.2, axengine.InferenceSession

Usage (on AX650 board)

import numpy as np
import axengine

sess = axengine.InferenceSession("model.axmodel")
data = np.random.rand(1, 3, 224, 224).astype(np.float32)
out = sess.run(None, {"images": data})
print(out[0].argmax())  # predicted class