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참조 https://www.youtube.com/watch?v=5V_iHjiey2o&list=PLRx0vPvlEmdBx9X5xSgcEk4CEbzEiws8C&index=16

참조 https://www.youtube.com/watch?v=E8LPYLcIn4Q&list=PLRx0vPvlEmdBx9X5xSgcEk4CEbzEiws8C&index=14

참조 https://www.youtube.com/watch?v=2SwYwlVcxhA&list=PLRx0vPvlEmdBx9X5xSgcEk4CEbzEiws8C&index=13

TrackBar import cv2 import numpy as np def change_color(x): r = cv2.getTrackbarPos("R", "Image") g = cv2.getTrackbarPos("G", "Image") b = cv2.getTrackbarPos("B", "Image") image[:] = [b, g, r] cv2.imshow('Image', image) image = np.zeros((600, 400, 3), np.uint8) cv2.namedWindow("Image") cv2.createTrackbar("R", "Image", 0, 255, change_color) cv2.createTrackbar("G", "Image", 0, 255, change_color) cv..

임계점 처리하기 참조 https://github.com/ndb796/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/10.%20OpenCV%20%EC%9E%84%EA%B3%84%EC%A0%90%20%EC%B2%98%EB%A6%AC%ED%95%98%EA%B8%B0/OpenCV%20%EC%9E%84%EA%B3%84%EC%A0%90%20%EC%B2%98%EB%A6%AC%ED%95%98%EA%B8%B0.ipynb

이미지 합치기 참고 https://github.com/ndb796/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/09.%20OpenCV%20%EC%9D%B4%EB%AF%B8%EC%A7%80%20%ED%95%A9%EC%B9%98%EA%B8%B0/OpenCV%20%EC%9D%B4%EB%AF%B8%EC%A7%80%20%ED%95%A9%EC%B9%98%EA%B8%B0.ipynb

참조 https://github.com/ndb796/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/08.%20OpenCV%20%EC%9D%B4%EB%AF%B8%EC%A7%80%20%EB%B3%80%ED%98%95/OpenCV%20%EC%9D%B4%EB%AF%B8%EC%A7%80%20%EB%B3%80%ED%98%95.ipynb

참조 https://github.com/ndb796/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/07.%20OpenCV%20%EC%9D%B4%EB%AF%B8%EC%A7%80%20%EC%97%B0%EC%82%B0/OpenCV%20%EC%9D%B4%EB%AF%B8%EC%A7%80%20%EC%97%B0%EC%82%B0.ipynb

참조 [1] - https://github.com/ndb796/Python-Data-Analysis-and-Image-Processing-Tutorial

https://www.kaggle.com/uciml/pima-indians-diabetes-database Pima Indians Diabetes Database Predict the onset of diabetes based on diagnostic measures www.kaggle.com Pima 인디언 관련 당뇨병 데이터를 보고 당뇨병을 예측하는 것입니다. Content The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, ins..