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fashionai-key-points-detection

Cascaded Pyramid Network for FashionAI Key Points Detection

Input

blouse

blouse/5ac2a09a11b0488bf1e39713f36e88d4.jpg

dress

dress/303e65590dc524f8eb67936bea48d489.jpg

outwear

outwear/513816cb9c691bef7e0edb40468717b1.jpg

skirt

skirt/0ecf970028d7a6a98002c826a76f9fb1.jpg

trousers

trousers/11ce236c6d8ccc54874a5d7dfdf1d8c4.jpg

(Image from https://tianchi.aliyun.com/museum7/?spm=5176.14046517.J_9711814210.23.2bd17c0aFQzXFg#/newprodetail?productId=7)

Output

blouse

Output

dress

Output

outwear

Output

skirt

Output

trousers

Output

Example keypoints

Example keypoints of the five clothing categories are as follows.

Example keypoints

(Image from https://github.com/HiKapok/tf.fashionAI/blob/master/demos/outline.jpg)

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 fashionai-key-points-detection.py

You can specify the "clothing type" by specifying after the --clothing-type option. The clothing type is selected from blouse, dress, outwear.

$ python3 fashionai-key-points-detection.py --clothing-type blouse

If you want to specify the input image, put the image path after the --input option.

$ python3 fashionai-key-points-detection.py --input 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 fashionai-key-points-detection.py --video VIDEO_PATH

Reference

Framework

Pytorch

Model Format

ONNX opset = 11

Netron