app.py

import numpy as np
import cv2
import glob
import gradio as gr

def shi_tomasi(image, max_corners=100, min_quality=0.01, min_dist=10):

    gray_img = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
    corners_img = cv2.goodFeaturesToTrack(gray_img,max_corners, min_quality, min_dist)
    corners_img = np.int0(corners_img)

    for corners in corners_img:
        x,y = corners.ravel()
        cv2.circle(image,(x,y),3,[0,255,0],-1)

    return image


demo = gr.Interface(
    shi_tomasi, 
    inputs=[gr.inputs.Image(type="numpy"),
            gr.Slider(0, 2000, value=100, step=1, label='Maximum Number of Corners'),
            gr.Slider(0.01, 0.99, value=0.01, step=0.01, label='Minimum Corner Quality'),
            gr.Slider(0, 100, value=10, step=1, label='Minumum Euclidean Distance Between Corners'),
            ], 
    outputs=gr.outputs.Image(type="numpy"),
    title="Corner Detection",
    description="Shi-Tomasi Corner Detection",
    examples=list(map(lambda x: [x, 100, 0.01, 10], glob.glob('./examples/*.jpg'))),
    allow_flagging="never",

)


if __name__ == "__main__":
    demo.launch()