About getting edge image using onnx runtime

[lyysl]

I tried to convert the .pth file to .onnx files onnx. I followed this website onnxruntime. Finally I get a numpy array with size (5,1,1,256,256). Should I get an array with 3 dimension rather than 5 dimension? Thank you.

import onnxruntime as ort
import numpy as np
import cv2
import matplotlib.pyplot as plt

img_path = "0.jpg"
input_img = cv2.imread(img_path)

mean = np.array([0.485, 0.456, 0.406]) * 255.0
scale = 1 / 255.0
std = [0.229, 0.224, 0.225]
input_blob = cv2.dnn.blobFromImage(
    image=input_img,
    scalefactor=scale,
    size=(256, 256),  # img target size
    mean=mean,
    swapRB=True,  # BGR -> RGB
    crop=False  # center crop
)
input_blob[0] /= np.asarray(std, dtype=np.float32).reshape(3, 1, 1)

ort_sess = ort.InferenceSession("pidinet_tiny_converted_new.onnx")
outputs = ort_sess.run(None, {'input': input_blob})

outputs = np.asarray(outputs)
print(outputs.shape)

[lyysl]

There were some problems when I convert the model. I solved the problem, thank you.