mobile_object_localizer

mobile_object_localizer_v1

Input

(Image from https://commons.wikimedia.org/wiki/File:Il_cuore_di_Como.jpg)

Shape : (1, 3, 192, 192)

Output

• detection_boxes shape : (1, 100, 4)
• detection_classes shape : (1, 100)
• detection_scores shape : (1, 100)
• num_detections shape : (1,)

Usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 mobile_object_localizer.py

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 mobile_object_localizer.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --video option, you can input the video.
If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 mobile_object_localizer.py --video VIDEO_PATH

Reference

• mobile_object_localizer_v1

Framework

TensorFlow Hub

Model Format

ONNX opset=11

Netron

mobile_object_localizer.onnx.prototxt