Problem : Determine the Feet and corresponding Shoe size of a person without Deep Learning, given a image clicked by the person itself.

• Clone the repo
• Install required packages using requirements.txt
• keep the image inside "data" folder. A sample image has already been kept in data folder.
• run main.py

• convert raw image to HSV format
• Remove noise using Gaussian Blur
• Run k-means clustering on preprocessed image for color based segmentation
• Detect the edges in clustered image.
• Find contours in Edge Detection output
• Generate the bounding Box to get the height/width of Paper and Feet

• OpenCV
• Sklearn

• Printer Paper is used as a reference (Height/Width is known and White background will help in Preprocessing)
• Foot should be in center, touching one edge of paper.
• Floor color should be different than white.
• Image should be clicked form top angle.
• Paper should be completely visible in the clicked image.

Designed Solution gives feet size in CM's, that can be compared with below chart for Corresponding Shoe Size

• If floor color is white, then it will difficult to segment the paper.
• Feet should not go out of the paper. Currently A4 size printer paper has ben chosen as reference. To fit all sizes, A1 paper can be taken as reference.
• If there is no closed curv after edge detection, its difficult to find bounding box. Only closed curv is considered as a contour. And bounding box is generated on top of that. As it can be seen in the below image, bounding box is not generated on feet but only on the paper.

• Deep learning models (Trained on feet and shoe Dataset) can be used to segment the paper and feet with more accuracy. One can use "Part Grouping Network"

• OpenCV - https://docs.opencv.org/3.4/d4/d73/tutorial_py_contours_begin.html
• Part grouping Network - Paper