- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
I had one model with multi inputs (4 inputs and 3 outputs ) like this
model.infer(
{
tensor0:data0,
tensor1:data1,
tensor2:data2,
tensor3:data3
})
I try to find the sample code (C/C++) for this case but I can't, does anyone have any samples for this case?
appreciate any help.
Link Copied
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi FaithfulNg,
Thank you for reaching out to us.
Could you please share more info regarding the use case of your model so that we can share a suitable sample that fits your use case?
Regards,
Hairul
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi Hairul,
my model can't be public and I try another example
ort_inputs = {
"image_embeddings": image_embedding,
"point_coords": onnx_coord,
"point_labels": onnx_label,
"mask_input": onnx_mask_input,
"has_mask_input": onnx_has_mask_input,
"orig_im_size": np.array(image.shape[:2], dtype=np.float32)
}
https://colab.research.google.com/drive/1wmjHHcrZ_s8iFuVFh9iHo6GbUS_xH5xq#scrollTo=9689b1bf
I try to infer to get results but I use ` ProfilingInfo ` to check the status and see all layers had the status NOT_RUN.
I deleted my code and switch to ONNX and I can't post the code I wrote here but this is the way I set inputs
ov::preprocess::PrePostProcessor prePostProcessor(pModel);
prePostProcessor.input("image_embeddings").tensor()
prePostProcessor.input("point_coords").tensor()
prePostProcessor.input("point_labels").tensor()
prePostProcessor.input("mask_input").tensor()
prePostProcessor.input("has_mask_input").tensor()
prePostProcessor.input("orig_im_size").tensor()
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi FaithfulNg,
Thank you for sharing the information.
I've managed to find an OpenVINO Notebook Tutorial which also utilizes Segment Anything model. You can refer to the Object masks from prompts with SAM and OpenVINO as reference on running model with multiple inputs using Python.
Unfortunately, there's no C/C++ sample on this from OpenVINO and it is only available in the OpenVINO Jupyter Notebook which is using Python.
Regards,
Hairul
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi FaithfulNg,
This thread will no longer be monitored since we have provided information. If you need any additional information from Intel, please submit a new question.
Regards,
Hairul

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page