How to run onnx model inference?
#32
by nived2 - opened
Can somebody share the code snippet to run the onnx files in this repo?
import onnxruntime as ort
import numpy as np
import torch
from PIL import Image
from io import BytesIO
from utilities import postprocess_image, preprocess_image
def initialize_model(model_path):
ort_sess = ort.InferenceSession(model_path)
return ort_sess
def process_image_buffer(image_buffer, ort_sess):
image = Image.open(BytesIO(image_buffer))
image_np = np.array(image)
orig_im_size = image_np.shape[0:2]
model_input_size = [1024, 1024]
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
processed_image = preprocess_image(image_np, model_input_size).to(device)
image_np_for_model = processed_image.cpu().numpy(
) if device.type == 'cuda' else processed_image.numpy()
input_name = ort_sess.get_inputs()[0].name
result = ort_sess.run(None, {input_name: image_np_for_model})
result_tensor = torch.tensor(result[0][0], dtype=torch.float32)
result_image = postprocess_image(result_tensor, orig_im_size)
pil_im = Image.fromarray(result_image)
no_bg_image = Image.new("RGBA", pil_im.size, (0, 0, 0, 0))
no_bg_image.paste(image, mask=pil_im)
output_buffer = BytesIO()
no_bg_image.save(output_buffer, format='PNG')
output_buffer.seek(0)
return output_buffer.getvalue()
model_path = "model/model_fp16.onnx"
ort_sess = initialize_model(model_path)