import numpy as np
import numpy.typing as npt
import cv2
import uz_framework.image as uz_image
from matplotlib import pyplot as plt

VIDEO_PATH = "./datam/raw_recording.webm"
MY_SIFT = False

def start_realtime_keypoint_detection():
    # Read video
    cap = cv2.VideoCapture(VIDEO_PATH)
    count = 0
    sift = cv2.SIFT_create()
    while cap.isOpened():
        ret,frame = cap.read()
        frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY) # Convert to grayscale
        if MY_SIFT:
            #sift_keypoints,_  = uz_image.hessian(frame)
            _, sift_keypoints = uz_image.hessian_points(frame, 3, 0.004)
            sift_keypoints = np.float64(sift_keypoints)
            kps = []
            for keypoint in sift_keypoints:
                y, x = keypoint
                kps.append(cv2.KeyPoint(x=x, y=y, size=1))
        else:
            kps, _ = sift.detectAndCompute(frame, None)
        frame = cv2.drawKeypoints(frame, kps, None, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
        #cv2.imshow('hello', frame)
        cv2.imwrite("./datam/true_sift/%d.jpg" % count, frame)
        print(f'{count} <- frame')
        count = count + 1
        #if cv2.waitKey(10) & 0xFF == ord('q'):
            #break
    
    cap.release()
    cv2.destroyAllWindows() # destroy all opened windows

if __name__ == '__main__':
    start_realtime_keypoint_detection()