def fd_SIFT_v2(image):
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
sift = cv2.xfeatures2d.SIFT_create()
kp = sift.detect(gray, None)
image = cv2.drawKeypoints(gray, kp, image)
cv2.show('sift_keypoints.jpg', image)
return kp
def sift_detection():
img = cv.imread('./../wu.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
sift = cv.xfeatures2d.SIFT_create()
kp = sift.detect(gray, None)
img = cv.drawKeypoints(gray, kp, img)
cv.show('sift_keypoints', img)
def binary_HSV(img):
hsv_low = np.array([25, 75, 165])
hsv_high = np.array([40, 255, 255])
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) # BGR转HSV
dst = cv2.inRange(hsv, hsv_low, hsv_high) # 通过HSV的高低阈值，提取图像部分区域
cv2.show("Binary HSV Outpt:", dst)
return dst
def birdsEyeTrans(self):
IMAGE_H = 480
IMAGE_W = 640
src = np.float32([[0, IMAGE_H], [1207, IMAGE_H], [0, 0], [IMAGE_W, 0]])
dst = np.float32([[569, IMAGE_H], [711, IMAGE_H], [0, 0], [IMAGE_W,
0]])
M = cv2.getPerspectiveTransform(src, dst) # The transformation matrix
Minv = cv2.getPerspectiveTransform(dst, src) # Inverse transformation
img = self.process_image(self, self.capture) # Read the test img
img = img[450:(450 + IMAGE_H),
0:IMAGE_W] # Apply np slicing for ROI crop
warped_img = cv2.warpPerspective(img, M,
(IMAGE_W, IMAGE_H)) # Image warping
cv2.imshow(cv2.cvtColor(warped_img, cv2.COLOR_BGR2RGB)) # Show results
cv2.show()
import cv2
cap = cv2.VideoCapture(0)
cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)
while True:
retrieval, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30))
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
#face_detect()
cv2.show('', frame)
cv2.release()
cv2.destroyAllWindows()
os.mkdir(path + str(ID))
print("Directory " + path + str(ID) + " Created")
except FileExistsError:
print("Directory " + path + str(ID) + " already exists.")
sampleN = 0
while (1):
ret, img = cap.read()
frame = img.copy()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
sampleN += 1
cv2.imwrite(path + str(ID) + "\\" + str(sampleN) + ".jpg",
gray[y:y + h, x:x + w])
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
cv2.waitKey(100)
cv2.show('img', img)
cv2.waitKey(1)
if (sampleN > 40):
break
def Display_image(img):
cv2.show(img)
cv2.waitKey(-1)
#Display_image(example1_gray)
while (True):
print('시작')
start = input('엔터키 입력')
try:
if start == '':
for i in range(0, 5):
print(os.listdir(pathList)[i])
original_image = cv2.imread(pathList + "/" +
os.listdir(pathList)[i])
if original_image is None:
error = np.zeros((1000, 1000), np.uint8)
cv2.putText(error, "No file", (50, 300),
cv.FONT_HERSHEY_SIMPLEX, 4, (255, 255, 255), 2)
cv2.namedWindow("window 2")
cv2.show('window 2', error)
key = cv2.waitKey(0)
if key == 27:
break
elif key == 13:
continue
original_image = cv2.resize(
original_image,
dsize=(int(original_image.shape[1] / 6),
int(original_image.shape[0] / 8)),
interpolation=cv2.INTER_AREA)
height, width = original_image.shape[:2]
#print("height: %d width: %d" %(height,width))
cv2.namedWindow("window 1", cv2.WINDOW_NORMAL)
cv2.imshow("window 1", original_image)
KP = 15
KD = 5
def initialize_motors():
gpio.setmode(gpio.board)
gpio.setup(L_MOTOR_PIN, gpio.out)
gpio.setup(R_MOTOR_PIN, gpio.out)
l_motor = gpio.PWM(L_MOTOR_PIN, 50)
r_motor = gpio.PWM(R_MOTOR_PIN, 50)
l_motor.start(100)
r_motor.start(100)
def drive_motor(motor, percent_speed):
duty_cycle = percent_speed * 100
motor.ChangeDutyCycle(duty_cycle)
##########################################
camera = PiCamera()
raw_capture = PiRGBArray(camera)
time_sleep(1)
for frame in camera.capture_continous(raw_capture, format="bgr", use_video_port=true):
img = frame.array
cv2.show('Raw image', img)
raw_capture.truncate(0)
camera.close()
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output2.avi', fourcc, 20, (1000, 1000))
while (True):
ret, frame = cap.read()
frame = cv2.flip(frame, flipCode=1) ## flipped sideways
#gray = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
cv2.imshow('frame', frame)
out.write(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
out.release()
cap = cv2.VideoCapture('output2.avi')
while (cap.isOpened()):
ret, frame = cap.read()
cv2.show('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
def camera():
authenticator = IAMAuthenticator(
apikey="ZQBgX2TPs2CmC3wNLWGEr7X3xDmq42sDsqTZVCsjdke8")
flag = False
obj = VisualRecognitionV4(version='2021-03-25',
authenticator=authenticator)
obj.set_service_url(
service_url=
'https://api.us-south.visual-recognition.watson.cloud.ibm.com/instances/2fa93f7c-36f0-48f9-abb1-15845fbe94e1'
)
while True:
success, img = cap.read()
cv2.imwrite('4.jpg', img)
with open('4.jpg', 'rb') as honda_file, open('4.jpg',
'rb') as dice_file:
result = obj.analyze(
collection_ids=[
"17951ae7-0169-4551-ac19-a3864c7eed65",
'17951ae7-0169-4551-ac19-a3864c7eed65'
],
features=[AnalyzeEnums.Features.OBJECTS.value],
images_file=[
FileWithMetadata(honda_file),
],
threshold=0.15).get_result()
#print(json.dumps(result, indent=2))
img = cv2.imread('4.jpg')
try:
left = result['images'][0]['objects']['collections'][0]['objects'][
0]['location']['left']
top = result['images'][0]['objects']['collections'][0]['objects'][
0]['location']['top']
width = result['images'][0]['objects']['collections'][0][
'objects'][0]['location']['width']
height = result['images'][0]['objects']['collections'][0][
'objects'][0]['location']['height']
img = cv2.imread('4.jpg')
cv2.rectangle(img, (left, top), (left + width, top + height),
(255, 0, 0), 2)
name = result['images'][0]['objects']['collections'][0]['objects'][
0]['object']
with open('data.txt', 'r') as f:
f.write(str(name))
cv2.putText(img, name, (left, top), cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 0, 0), 2)
cv2.imshow('gasm', img)
k = cv2.waitKey(30) & 0xff
if k == 27: # press 'ESC' to quit
break
cv2.show('gasm', img)
if name == 'gun' and flag == False:
flag = True
SendMail()
except:
cv2.imshow('gasm', img)
# pass
# cv2.show('gasm',img)
cap.release()
# cv2.waitKey(0)
cv2.destroyAllWindows()
from PIL import Image
import numpy as np
from tools.deeplab import Deeplab
capture = cv2.VideoCapture("input_video/demo.mp4")
fps = capture.get(cv2.CAP_PROP_FPS)
size = (int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)),
int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
print("fps: {}\nsize: {}".format(fps, size))
# 读取视频时长（帧总数）
total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
print("[INFO] {} total frames in video".format(total))
# 调用VideoWrite（）函数
videoWrite = cv2.VideoWriter(
filename='output/Video.avi',
fourcc=cv2.VideoWriter_fourcc(*"MPEG"),
fps=fps,
frameSize=size,
isColor=True,
)
index = 0
deeplab = Deeplab()
while capture.isOpened():
# 读取某一帧
ref, frame = capture.read()
frame = frame[:, :, ::-1]
# 进行检测
frame = deeplab.main(frame, index, total)
frame = frame[:, :, ::-1].astype(dtype=np.uint8)
videoWrite.write(frame)
cv2.show(frame)
index += 1
import scipy as sp
import numpy as np
import scipy.ndimage as nd
import matplotlib.pyplot as plt
import cv2
img = cv2.imread('C:\Users\Debika Dutt\Documents\UB\CSE573\Bridge.jpg', 0)
LoG = nd.gaussian_laplace(img, 2)
thres = np.absolute(LoG).mean() * 0.75
output = sp.zeros(LoG.shape)
w = output.shape[1]
h = output.shape[0]
for y in range(1, h - 1):
for x in range(1, w - 1):
patch = LoG[y - 1:y + 2, x - 1:x + 2]
p = LoG[y, x]
maxP = patch.max()
minP = patch.min()
if (p > 0):
zeroCross = True if minP < 0 else False
else:
zeroCross = True if maxP > 0 else False
if ((maxP - minP) > thres) and zeroCross:
output[y, x] = 1
cv2.imshow("img", output)
cv2.show()
import cv2
import numpy as np
imagen = cv2.imread("/home/Pictures/sign_DoubleCurve.png")
imagen = cv2.cvtColor(imagen, cv2.COLOR_BGR2HSV)
imagen = np.array(image1, dtype=np.float64)
random_bright = .5 + np.random.uniform()
image[:, :, 2] = image[:, :, 2] * random_bright
image[:, :, 2][image[:, :, 2] > 255] = 255
image = np.array(image, dtype=np.uint8)
image = np.cv2.cvtColor(image)
cv2.show(image, "imagen.png")
1、没有安装tesseract.exe (pip install py..过了)
- 安装了之后，去找.py文件，在默认路径前添加一个r，不然 / 的符号, windows系统无法识别
- r：保持字符原始值的意思
2、该模板的中文版本可能不好用，可以直接使用百度OCR去进行文字识别
3、目前还没有需要识别文字，可以去尝试识别英文即可
"""
from PIL import Image
import pytesseract
import cv2
import os
preprocess = "blur"
image = cv2.imread("./images/4.png")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2BGRA)
if preprocess == "thresh":
gray = cv2.medianBlur(gray, 3)
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, gray)
text = pytesseract.image_to_string(Image.open(filename))
print(text)
os.remove(filename)
cv2.show("Image", image)
cv2.imshow("Output", gray)
cv2.waitKey(0)
def main():
img = readImage(sys.argv[1])
canny = findCannyEdges(img)
contours = findContours(canny)
cv2.imshow('img',contours)
cv2.show()
for face_encoding in face_encodings:
matches = face_recognition.compare_faces(known_face_encodings,
face_encoding)
name = "Unknown"
if True in matches:
first_match_index = match.index(True)
name = known_face_names[first_match_index]
process_this_frame = not process_this_frame
for (top, right, bottom, left), name in zip(face_locations, face_names):
top *= 4
right *= 4
bottom *= 4
left *= 4
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255),
cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0,
(255, 255, 255), 1)
cv2.show('Video', frame)
if cv2.waitkey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
""" Created on Sat Feb 16 8:19:21AM 2019 @author: Matt-Gleich How to convert BRG to other color-spaces such as HSV or Gray-scale """ import numpy as np import cv2 photo_path = '/Users/matthewgleich/Desktop/First/CV2_Test_Images/Solid_Red_Sized__25214.1507754519.jpg' img = cv2.imread(photo_path, 0) rows, cols = img.shape M = cv2.getRotationMatrix2d((cols / 2, rows / 2), 90, 1) dst = cv2.warpAffine(img, M(cols, rows)) cv2.show(img)
