OpenCV-Python

import cv2
print(cv2.getBuildInformation())

#-*- coding:utf-8 -*-

import cv2
import sys
from numpy import array, float32


def main(input_file: str, output_file: str, headless=True):
    cap = cv2.VideoCapture(input_file)
    fps = cap.get(cv2.CAP_PROP_FPS)
    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    input_size = width, height

    print("Input: ", input_file)
    print("Input fps: ", fps)
    print("Input size: ", input_size)
    print("Input frames: ", frames)

    resize_size = 1920, 1080
    print("Resize size: ", resize_size)

    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
    writer = cv2.VideoWriter(output_file, fourcc, fps, resize_size)
    print("Output: ", output_file)
    print("Output fps: ", fps)
    print("Output size: ", resize_size)

    try:
        i = 0
        while True:
            # print(f"{i}/{frames}")
            i += 1

            ret, image = cap.read()
            if not ret:
                break

            if image.shape[0:2] != resize_size:
                image = cv2.resize(image, dsize=resize_size)

            writer.write(image)

            if not headless:
                cv2.imshow("Preview", image)
                if cv2.waitKey(1) & 0xFF == ord('q'):
                    break
    finally:
        cap.release()
        writer.release()
        if not headless:
            cv2.destroyAllWindows()

if __name__ == "__main__":
    main(sys.argv[1], sys.argv[2], True)

import numpy as np
import cv2

cap = cv2.VideoCapture(0)

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Our operations on the frame come here
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Display the resulting frame
    cv2.imshow('frame',gray)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

import cv2
import numpy as npimport os
os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"] = "rtsp_transport;udp"
vcap = cv2.VideoCapture("rtsp://192.168.1.2:5554/camera", cv2.CAP_FFMPEG)
while(1):
    ret, frame = vcap.read()
    if ret == False:
        print("Frame is empty")
        break;
    else:
        cv2.imshow('VIDEO', frame)
        cv2.waitKey(1)

import numpy as np
import cv2

cap = cv2.VideoCapture('vtest.avi')

while(cap.isOpened()):
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    cv2.imshow('frame',gray)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

import numpy as np
import cv2

cap = cv2.VideoCapture(0)

# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))

while(cap.isOpened()):
    ret, frame = cap.read()
    if ret==True:
        frame = cv2.flip(frame,0)

        # write the flipped frame
        out.write(frame)

        cv2.imshow('frame',frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        break

# Release everything if job is finished
cap.release()
out.release()
cv2.destroyAllWindows()

import cv2
img = cv2.imread("lenna.png")
crop_img = img[y:y+h, x:x+w]
cv2.imshow("cropped", crop_img)
cv2.waitKey(0)

# 이미지의 크기를 잡고 이미지의 중심을 계산합니다.
(h, w) = cv2_image.shape[:2]
(cX, cY) = (w // 2, h // 2)

# 이미지의 중심을 중심으로 이미지를 45도 회전합니다.
M = cv2.getRotationMatrix2D((cX, cY), 45, 1.0)
rotated_45 = cv2.warpAffine(cv2_image, M, (w, h))

import cv2

def rotate_image(mat, angle):
    """
    Rotates an image (angle in degrees) and expands image to avoid cropping
    """

    height, width = mat.shape[:2] # image shape has 3 dimensions
    image_center = (width/2, height/2) # getRotationMatrix2D needs coordinates in reverse order (width, height) compared to shape

    rotation_mat = cv2.getRotationMatrix2D(image_center, angle, 1.)

    # rotation calculates the cos and sin, taking absolutes of those.
    abs_cos = abs(rotation_mat[0,0]) 
    abs_sin = abs(rotation_mat[0,1])

    # find the new width and height bounds
    bound_w = int(height * abs_sin + width * abs_cos)
    bound_h = int(height * abs_cos + width * abs_sin)

    # subtract old image center (bringing image back to origo) and adding the new image center coordinates
    rotation_mat[0, 2] += bound_w/2 - image_center[0]
    rotation_mat[1, 2] += bound_h/2 - image_center[1]

    # rotate image with the new bounds and translated rotation matrix
    rotated_mat = cv2.warpAffine(mat, rotation_mat, (bound_w, bound_h))
    return rotated_mat