def main():
"""
Main function.
"""
print("OpenCV version:" + cv2.getVersionString())
print("Waiting for input of driver...")
keyboard.wait('a', True)
print("Desert Bot started, enjoy the ride!")
while not keyboard.is_pressed('q'):
frame = pyautogui.screenshot()
frame = cv2.cvtColor(np.array(frame), cv2.COLOR_RGB2BGR)
lane = detect_lane(frame)
if lane is not None:
keyboard.press('a')
for x1, y1, x2, y2 in lane:
if min([x1, x2]) <= int(frame.shape[1] * 0.31):
keyboard.press('j')
time.sleep(0.05)
keyboard.release('j')
else:
print('No lane detected!')
cv2.destroyAllWindows()
def __init__(self):
self.__DEBUG = True
self.__AVOID_LOOP = False
self.__cv_version = cv2.getVersionString()
self.__img_counter = 0
self.__img_optimizer = ImageOptimizer()
self.__match_filed_finder = MatchFieldFinder()
self.__red_range_lower = np.array((17, 15, 60), dtype="uint8")
self.__red_range_upper = np.array((50, 56, 255), dtype="uint8")
self.__blue_range_lower = np.array((86, 31, 4), dtype="uint8")
self.__blue_range_upper = np.array((220, 88, 50), dtype="uint8")
self.__red_range_hsv_lower_1 = np.array([0, 100, 50])
self.__red_range_hsv_lower_2 = np.array([150, 100, 50])
self.__red_range_hsv_upper_1 = np.array([10, 255, 255])
self.__red_range_hsv_upper_2 = np.array([190, 255, 255])
self.__blue_range_hsv_lower = np.array([100, 120, 30])
self.__blue_range_hsv_upper = np.array([120, 255, 255])
self.__ip = os.getenv('PEPPER_IP')
self.__pw = os.getenv('PEPPER_PW')
def __init__(self,
resolution=(800, 600),
use_pi_camera=False,
fullscreen=False):
self._ESC = 27
self._facerecognizer = FaceRecognizer()
self._smilerecognizer = SmileRecognizer()
self._trigger = SnapshotTrigger("images")
self._display = StreamDisplay("Photobooth", fullscreen)
self._camstream = CameraStream(use_pi_camera=use_pi_camera,
resolution=resolution).start()
self._stopped = False
self._smile_cascade = cv2.CascadeClassifier(
'recognition/haarcascades/smile.xml')
print("Using OpenCV: " + cv2.getVersionString())
print("Using Python: " + sys.version)
sleep(2)
return Block(0, date.datetime.now(), "Genesis Block", "0")
def next_block(last_block):
this_index = last_block.index + 1
this_timestamp = date.datetime.now()
this_data = "Hey! I'm block " + str(this_index)
previous_hash = last_block.hash
return Block(this_index, this_timestamp, this_data, previous_hash)
# Create the blockchain and add the genesis block
blockchain = [create_genesis_block()]
previous_block = blockchain[0]
# How many blocks should we add to the chain
# after the genesis block
num_of_blocks_to_add = 20
# Add blocks to the chain
for i in range(0, num_of_blocks_to_add):
block_to_add = next_block(previous_block)
blockchain.append(block_to_add)
previous_block = block_to_add
# Tell everyone about it!
print("Block #{} has been added to the blockchain!".format(
block_to_add.index))
print(block_to_add)
print("Hash: {}\n".format(block_to_add.hash))
print(cv.getVersionString())
import cv2 as cv
import os
from matplotlib import pyplot as plt
os.chdir(r'.\Module\OpenCV')
print('OpenCV的当前版本：', cv.getVersionString()) # 查看版本信息
img = cv.imread('tower.jpg', 1) # 读取图片
"""
img = cv.imread(文件名,[,参数])
第二个参数是一个标志，它指定了读取图像的方式。
cv.IMREAD_COLOR： 加载彩色图像，任何图像的透明度都会被忽视，如果不传参数，这个值是默认值。
cv.IMREAD_GRAYSCALE：以灰度模式加载图像。
cv.IMREAD_UNCHANGED：加载图像，包括alpha通道
注意：这三个标志可以简化为 1 、 0 、 -1 。
"""
"""
print(img[20, 30]) # 读取像素可以通过行坐标和列坐标来进行访问，灰度图像直接返回灰度值，彩色图像则返回B、G、R三个分量
blue = img[20, 30, 0] # 在获取彩色图片像素时的第二个参数 0|1|2 的含义是获取 BGR 三个通道的像素。
green = img[20, 30, 1]
red = img[20, 30, 2]
print(blue, green, red)
# 像素依次赋值
img[20, 30, 0] = 255
img[20, 30, 1] = 255
img[20, 30, 2] = 255
print(img[20, 30])
# 也可以通过数组直接对像素点一次赋值：
img[20, 30] = [0, 0, 0]
print(img[20, 30])
img[0:200, 50:100] = [255, 255, 255] # 对一个区域的像素进行赋值,全都赋值成为白色
"""
import cv2
import struct
import time
import numpy as np
if __name__ == '__main__':
print("version: {0}".format(cv2.getVersionString()))
temp = cv2.imread(filename="WeChat.jpg")
target = cv2.resize(src=temp, dsize=(390, 209))
start = time.time()
with open(file="image.bin", mode="rb") as f:
buff = f.read(209 * 390 * 4)
for i in range(209):
for j in range(390):
target[i][j] = np.array([
buff[i * 390 * 4 + j * 4 + 0],
buff[i * 390 * 4 + j * 4 + 1],
buff[i * 390 * 4 + j * 4 + 2]
],
dtype=np.uint8)
end = time.time()
print("assignment cost: %.3f s" % (end - start))
while True:
cv2.imshow("target", target)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.destroyAllWindows()
# -*- coding: utf-8 -*-
# Copyright (C) 2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import cv2
print('OpenCV version:', cv2.getVersionString())
print('OpenVX:', cv2.haveOpenVX())
print('CPUs:', cv2.getNumberOfCPUs())
import cv2
import time
argument = {"fps": 0, "backup_time": 0, "message": "loading. . ."}
if __name__ == '__main__':
camera = cv2.VideoCapture(0, cv2.CAP_DSHOW)
print("OpenCV:{0}".format(cv2.getVersionString()))
camera.set(propId=3, value=800)
camera.set(propId=4, value=480)
print(camera.get(propId=3), camera.get(propId=4))
while True:
moment = time.gmtime().tm_sec
if moment != argument["backup_time"]:
argument["backup_time"] = moment
argument["message"] = "\rfps:{0}".format(argument["fps"])
print(argument["message"], end="")
argument["fps"] = 0
argument["fps"] += 1
ret, frame = camera.read()
frame = frame[0:480, 0:800]
frame[0:480, 800:848] = [23, 56, 255]
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
result = frame
result[0:240, 0:400] = cv2.resize(frame, (400, 240))
result[0:240, 400:800] = cv2.resize(hsv, (400, 240))
cv2.imshow(winname="frame width:800 height:480", mat=result)
if cv2.waitKey(delay=10) & 0xFF == ord('q'):
break
self._work_path + '\\Controller\\images\\temp\\contours.png',
self._img_obj)
print('--------------------------------------------')
paragraphs = self.find_paragraph(region, iterations=3)
if self._DEBUG:
cv2.waitKey(0)
cv2.destroyAllWindows()
return paragraphs
if __name__ == '__main__':
print('--------------------------------------------')
print('OpenCV Ver:{}'.format(cv2.getVersionString()))
# image_path = 'test_image/text_line/news{}.png'.format(14) # qq bug 14 18 17
# image_path = 'test_image/text_line/qq{}.png'.format(6) # bug: 6 open运算后解决6
# image_path = 'test_image/text_line/baidu{}.png'.format(2) # bug: 6
# image_path = 'test_image/text_line/shouhu{}.png'.format(4)
# image_path = 'test_image/text_line/sina{}.png'.format(4) # bug:4
# image_path = 'test_image/text_line/163_{}.png'.format(6) # bug: 6 7
image_path = 'test_image/text_line/ifeng{}.png'.format(
8) # bug:3 7 8 font_size=15
start = datetime.now()
d = NewsTitleList(font_size=18)
d._DEBUG = True
d.find_title(image_path)
end = datetime.now()
import cv2 CONTOURS_INDEX = 1 if cv2.getVersionString()[0] == '3' else 0
def __init__(self):
self.__DEBUG = True
self.__cv_version = cv2.getVersionString()
import sys
from math import sqrt, floor
import cv2
# This code combines face detection with open CV's code for object tracking to detect and track a face automatically
(major_ver, minor_ver, subminor_ver) = (cv2.getVersionString()).split('.')
draw_debug_elements = True
faces_for_debug = []
def draw_face_debug_objects(frame):
centre = get_centre(frame)
for (x, y, w, h) in faces_for_debug:
# Bounding box
p1 = (x, y)
p2 = (x + w, y + h)
cv2.rectangle(frame, p1, p2, (0, 255, 0), 2)
# Line to centre
line_p1 = (int(x + (w / 2)), int(y + (h / 2)))
cv2.line(frame, line_p1, centre, (0, 127, 255))
def save_face_for_debug(face_bounding_box):
faces_for_debug.append(face_bounding_box)
import cv2
print('cv2 version is ' + str(cv2.getVersionString()))
def capture_config(camera_port=0):
frame_height = 480
frame_width = 640
cap = cv2.VideoCapture(camera_port)
cap.set(3, frame_width)
cap.set(4, frame_height)
if not cap.isOpened():
print('Unable to read camera feed')
return False
return cap
cap = capture_config()
while cap:
ret, frame = cap.read()
cv2.imshow('captured frame', frame)
if cv2.waitKey(0) & 0xff == ord('q'):
cap.release()
cv2.destroyAllWindows()
break
offset) >= x >= (lastDimension[0] - offset) and (
lastDimension[1] + offset) >= y >= (lastDimension[1] -
offset):
return True
return False
def rotate_clockwise(self, matrix):
for x in range(3):
temp = matrix[x][0]
matrix[x][0] = matrix[x][2]
matrix[x][2] = temp
return matrix
if __name__ == '__main__':
detect_board = DetectBoard()
cv2_version = cv2.getVersionString()
if str.find(cv2_version, "3.4.") != -1:
print("Using opencv version ", cv2_version)
connection_url = os.getenv('PEPPER_IP') + ":9559"
app = qi.Application(["--qi-url=" + connection_url])
app.start()
session = app.session
# local testing pipeline
# board = detect_board.get_picture_board()
# detect board on pepper
board = detect_board.get_board(session)
print(board)
