What is the method for detecting images using Python and ONNX?

2 years ago
Liam
2 minutes

To detect images using ONNX, you can follow these steps:

  1. To install the ONNX library, first, you need to install it in your Python environment. You can use the following command for installation:
pip install onnx
  1. Load ONNX model: Next, you need to load your trained ONNX model. You can use the following code to load the ONNX model:
import onnx

model = onnx.load('your_model.onnx')
  1. Create an ONNX runtime environment: Next, you will need to establish an ONNX runtime environment in which the model can be executed. You can create the ONNX runtime environment by using the following code.
import onnxruntime as ort

ort_session = ort.InferenceSession('your_model.onnx')
  1. Preprocessing images: Before making predictions, you may need to preprocess the input images to fit the requirements of the model. You can use libraries like OpenCV or PIL to load and process images.
  2. Make inferences: Lastly, you can use the ONNX runtime environment to make inferences. You can use the following code to infer images:
import numpy as np

# 将图片转换为模型所需的数据格式
input_data = np.array(preprocessed_image)

# 执行推断
output = ort_session.run(None, {ort_session.get_inputs()[0].name: input_data})

In this code example, the preprocessed_image is the image data that has been preprocessed. The ort_session.run() method returns the output result of the model.

Please note that this is just a basic example; you may need to make some modifications based on your specific model and requirements.

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