Image classification algorithm

Image Classification Algorithms—Mobilenet v1

This example mainly implements the following functions:

1. Load the mobilenet v1 image classification model
2. Read the zebra_cls.jpg static image as the input of the model
3. Parse the model output to get the classification result of the image

1. How to run

Execute the test_mobilenetv1.py program

Program path: /app/pydev_demo/01_basic_sample/

sunrise@ubuntu:~$ cd /app/pydev_demo/01_basic_sample/
sunrise@ubuntu:/app/pydev_demo/01_basic_sample$ sudo ./test_mobilenetv1.py

2. Expected results

Output the prediction results of the image classification algorithm, id and confidence.

zebra_cls.jpg is a picture of a zebra. According to the classification of the ImageNet dataset, the returned result id is 340 and the confidence is 0.991851.

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========== Classification result ==========
cls id: 340 Confidence: 0.991851