Develop Reference

threading with open cv and FFMPEG

I'm working on a project which get several CCTV streams and preform some processing with OpenCV. Then I want to get those streams back with rtmp/rtsp protocols.
I can use openCV with threading in python and preform my processing and return in scale of 4 frames from each stream sequentially.
Is there any way to use this python library and FFMPEG to send each stream to corresponding rtmp/rtsp with FFMPG?
`class LoadStreams: # multiple IP or RTSP cameras
def __init__(self, sources='streams.txt', img_size =(1290,720)):
self.mode = 'images'
self.img_size = img_size
if os.path.isfile(sources):
with open(sources, 'r') as f:
sources = [x.strip() for x in f.read().splitlines() if len(x.strip())]
else:
sources = [sources]
n = len(sources)
self.imgs = [None] * n
self.sources = sources
for i, s in enumerate(sources):
cap = cv2.VideoCapture(eval(s) if s.isnumeric() else s)
assert cap.isOpened(), 'Failed to open %s' % s
w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
self.fps = cap.get(cv2.CAP_PROP_FPS) % 100
_, self.imgs[i] = cap.read() # guarantee first frame
thread = Thread(target=self.update, args=([i, cap]), daemon=True)
print(' success (%gx%g at %.2f FPS).' % (w, h, self.fps))
thread.start()
def update(self, index, cap):
n = 0
while cap.isOpened():
n += 1
# _, self.imgs[index] = cap.read()
cap.grab()
if n == 4: # read every 4th frame
_, self.imgs[index] = cap.retrieve()
n = 0
time.sleep(0.01) # wait time
def __iter__(self):
self.count = -1
return self
def __next__(self):
self.count += 1
img0 = self.imgs.copy()
if cv2.waitKey(1) == ord('q'): # q to quit
cv2.destroyAllWindows()
raise StopIteration`
enter image description here
Being able to use ffmpeg for n frames from A_in streaming to A_out url and get n from B_in url stream to B_out url.

How to print every x seconds while rest of code runs without being stopped?

I've seen ways of using the time.sleep() function, however that stops the rest of the code from running.
I'm making a hand recognition script and want the video output to be hindered by a certain value being printed every second.
This is my code:
import cv2
from cvzone.HandTrackingModule import HandDetector
import time
cap = cv2.VideoCapture(0)
detector = HandDetector(maxHands=1, detectionCon=0.7)
length = 0
while True:
success, img = cap.read()
hands, img = detector.findHands(img)
if hands:
hand1 = hands[0]
lmlist1 = hand1["lmList"]
bbox = hand1["bbox"]
cp1 = hand1["center"]
HandType = hand1["type"]
#fingers1 = detector.fingersUp(hand1)
#print(fingers1)
length, info, img = detector.findDistance(lmlist1[8], lmlist1[5], img)
print(length)
time.sleep(1)
cv2.imshow("Image", img)
cv2.waitKey(1)
if cv2.waitKey(1) == ord("q"):
break
cap.release()
cv2.destroyAllWindows()
The problem is that because of:
print(length)
time.sleep(1)
the frame rate of the video is reduced to 1fps.
Is there a way to run the printing command so that it doesn't affect the frame rate?
Thanks.
EDIT
This is the new code and fps is still low on my computer.
import cv2
from cvzone.HandTrackingModule import HandDetector
import time
import threading
import math
#Resolution: 720 x 1280
cap = cv2.VideoCapture(0)
detector = HandDetector(maxHands=1, detectionCon=0.7)
length = 0
fingerpos = [1,1,1,1,1]
def index(img):
lil, info, img = detector.findDistance(lmlist1[8], lmlist1[5], img)
lib, info, img = detector.findDistance(lmlist1[6], lmlist1[5], img)
lit, info, img = detector.findDistance(lmlist1[8], lmlist1[6], img)
index_angle = (lib**2 + lit**2 - lil**2) / (2 * lib * lit)
index_angle = math.degrees(math.acos(index_angle))
return int(index_angle)
def middle(img):
lml, info, img = detector.findDistance(lmlist1[12], lmlist1[9], img)
lmb, info, img = detector.findDistance(lmlist1[12], lmlist1[10], img)
lmt, info, img = detector.findDistance(lmlist1[10], lmlist1[9], img)
middle_angle = (lmb**2 + lmt**2 - lml**2) / (2 * lmb * lmt)
middle_angle = math.degrees(math.acos(middle_angle))
return int(middle_angle)
def ring(img):
lrl, info, img = detector.findDistance(lmlist1[16], lmlist1[13], img)
lrb, info, img = detector.findDistance(lmlist1[16], lmlist1[14], img)
lrt, info, img = detector.findDistance(lmlist1[14], lmlist1[13], img)
ring_angle = (lrb**2 + lrt**2 - lrl**2) / (2 * lrb * lrt)
ring_angle = math.degrees(math.acos(ring_angle))
return int(ring_angle)
def pinky(img):
lpl, info, img = detector.findDistance(lmlist1[20], lmlist1[17], img)
lpb, info, img = detector.findDistance(lmlist1[20], lmlist1[18], img)
lpt, info, img = detector.findDistance(lmlist1[18], lmlist1[17], img)
pinky_angle = (lpb**2 + lpt**2 - lpl**2) / (2 * lpb * lpt)
pinky_angle = math.degrees(math.acos(pinky_angle))
return int(pinky_angle)
def thumb(img):
ltl, info, img = detector.findDistance(lmlist1[4], lmlist1[2], img)
ltb, info, img = detector.findDistance(lmlist1[4], lmlist1[3], img)
ltt, info, img = detector.findDistance(lmlist1[3], lmlist1[2], img)
thumb_angle = (ltb**2 + ltt**2 - ltl**2) / (2 * ltb * ltt)
thumb_angle = math.degrees(math.acos(thumb_angle))
return int(thumb_angle)
def data(img):
print(str(thumb(img)) + ", " + str(index(img)) + ", " + str(middle(img)) + ", " + str(ring(img)) + ", " + str(pinky(img)))
time.sleep(0.5)
threading.Thread(target=data).start()
while True:
success, img = cap.read()
#img = cv2.resize(img, (640, 420))
hands, img = detector.findHands(img)
#print('Resolution: ' + str(img.shape[0]) + ' x ' + str(img.shape[1]))
if hands:
hand1 = hands[0]
lmlist1 = hand1["lmList"]
bbox = hand1["bbox"]
cp1 = hand1["center"]
HandType = hand1["type"]
data(img)
#print(str(thumb(img)) + ", " + str(index(img)) + ", " + str(middle(img)) + ", " + str(ring(img)) + ", " + str(pinky(img)))
cv2.imshow("Image", img)
cv2.waitKey(1)
if cv2.waitKey(1) == ord("q"):
break
cap.release()
cv2.destroyAllWindows()

One way is to use time.time to measure how much time has passed (will print 'hi' every 5 seconds or so, this is less precise because if some part of the loop takes more time, it may print later than expected):
import time
start = time.time()
while True:
# run some code
current_time = time.time()
if current_time - start >= 5:
print('hi')
start = current_time
Or use threading module to run a loop concurrently (will print 'hi' every 5 seconds, this is also more precise, because the time measurement is not affected by the speed of the "main" loop (as is the case with the above code)):
import time
import threading
def loop():
while True:
time.sleep(5)
print('hi')
threading.Thread(target=loop).start()
while True:
# run some code
pass # this can be removed after you add the actual code

How to run a script but print only the output obtained after 1 min for first time and 3 min after every time till the script runs?(Python)

So I have am working with YOLOv4 to process video frames for object detection of one class : Human and every time a Human is detected in frame it prints a line in the terminal " Number of human detected :" and gives the number of human detected in a particular frame. Now I want the code to run as it is but instead of printing the above output for every frame, it should print the output of the videoframe it processes at the first 1 min mark and there after at every 3 min mark till the video is fully processed. So for a 5 min video, i would want the statement to be printed at the following videotimestamps: 1:00, 4:00. For a 8 min video it would be: 1:00, 4:00, 7:00.... and so on. I tried using schedule module but it seems to just schedule the entire code to run after 1 min.
from imutils.video import VideoStream
from imutils.video import FPS
import numpy as np
import argparse
import imutils
import time
import cv2
from collections import OrderedDict
import numpy as np
import matplotlib.pyplot as plt
import datetime
import schedule
import time
from time import sleep
file = "test2"
input = "C:/Users/asmita.nandi/Downloads/" + file + ".mp4"
output = "C:/Users/asmita.nandi/Downloads/" + file + ".avi"
net = cv2.dnn.readNet( "C:/Users/asmita.nandi/Downloads/custom-yolov4-tiny_human-608
(1).cfg","C:/Users/asmita.nandi/Downloads/custom-yolov4-tiny-detector_human.weights")
labelsPath = "C:/Users/asmita.nandi/Downloads/human_label.txt"
def event(input,output,net,labelsPath):
LABELS = open(labelsPath).read().strip().split("\n")
np.random.seed(1)
cmap = plt.get_cmap('tab20b')
colors = [cmap(i)[:3] for i in np.linspace(0, 1, 6)]
CONF_THRESH, NMS_THRESH = 0.25, 0.25
vs = cv2.VideoCapture(input)
fp = vs.get(cv2.CAP_PROP_FPS)
writer = None
W = None
H = None
totalFrames = 0
TotalHuman = 0
while True:
frame = vs.read()
frame = frame[1] if input else frame
if input is not None and frame is None:
break
(H, W) = frame.shape[:2]
print(H,W)
if W is None or H is None:
(H, W) = frame.shape[:2]
if output is not None and writer is None:
fourcc = cv2.VideoWriter_fourcc(*"MJPG")
writer = cv2.VideoWriter(output, fourcc,fp,(W,H), True)
ln = net.getLayerNames()
ln = [ln[i[0] - 1] for i in net.getUnconnectedOutLayers()]
blob = cv2.dnn.blobFromImage(frame, 1 / 255.0, (608,608), swapRB=True, crop=False)
net.setInput(blob)
start = time.time()
layerOutputs = net.forward(ln)
print(layerOutputs)
end = time.time()
boxes = []
confidences = []
classIDs = []
(H, W) = frame.shape[:2]
# loop over each of the layer outputs
for output in layerOutputs:
# loop over each of the detections
for detection in output:
scores = detection[5:]
#print(detection)
classID = np.argmax(scores)
confidence = scores[classID]
if confidence > CONF_THRESH:
#print("Box")
box = detection[0:4] * np.array([W, H, W, H])
(centerX, centerY, width, height) = box.astype("int")
x = int(centerX - (width / 2))
y = int(centerY - (height / 2))
boxes.append([x, y, int(width), int(height)])
confidences.append(float(confidence))
classIDs.append(classID)
idxs = cv2.dnn.NMSBoxes(boxes, confidences, CONF_THRESH,NMS_THRESH)
ObjectCount = {}
if len(idxs) > 0:
for i in idxs.flatten():
(x, y) = (boxes[i][0], boxes[i][1])
(w, h) = (boxes[i][2], boxes[i][3])
color = colors[classIDs[i]]
color = [i * 255 for i in color]
class_name = LABELS[classIDs[i]]
cv2.rectangle(frame,(x,y),(x+w,y+h),color,2)
# if class_name == "Human":
cv2.putText(frame, class_name,(x, y-10),0, 0.5,color,2)
obj, conf = LABELS[classIDs[i]], confidences[i]
if obj not in ObjectCount.keys():
ObjectCount[obj] = 1
else:
ObjectCount[obj] += 1
allvalues=[]
allvalues.append(ObjectCount[obj])
print("Number of Humans detected ", max(allvalues))
if writer is not None:
writer.write(frame)
# show the output frame
#cv2_imshow(frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
# increment the total number of frames processed thus far and
# then update the FPS counter
totalFrames += 1
fps.update()
# stop the timer and display FPS information
#for (objectID, centroid) in objects.items():
#print(objectID, centroids)
fps.stop()
print("[INFO] elapsed time: {:.2f}".format(fps.elapsed()))
print(totalFrames)
#print(info)
# check to see if we need to release the video writer pointer
if writer is not None:
writer.release()
# if we are not using a video file, stop the camera video stream
if not input:
vs.stop()
# otherwise, release the video file pointer
else:
vs.release()
# close any open windows
cv2.destroyAllWindows()
schedule.every(1).minutes.do(event(input,output,net,labelsPath))
while 1:
schedule.run_pending()
time.sleep(1)

saving random images in separate folder in python

I am facing a little problem,
actually I have a function which generates so many frames from a video that I provided to my code which then saves in a specific folder , then I access some frames from that folder by using RND (random ) command , now what I want is that those random frames which my code pick randomly should also save in some other folder, for example, if there are 300 frames and my code pick 15 frames randomly from those 300 frames then these 15 frames must also save in some other separate folder .
This is my code,
def video_frames(nameof_video,frame_savelocation,cropimages_save):
vidcap = cv2.VideoCapture(nameof_video)
success, image = vidcap.read()
print(success)
count = 1
success = True
while success:
success, image = vidcap.read()
cv2.imwrite(frame_savelocation+"/%d.jpg" % count, image)
# save frame as JPEG file
# if cv2.waitKey(10) == 27: # exit if Escape is hit
# break
if count == 0:
break
count += 1
print("frames saved in the desired location!!!!!")
##### crop faces from frame and save them----###
for r in range(1, 15):
random_imagecrop(frame_savelocation, cropimages_save) #-----> function called
return
def random_imagecrop(frame_savelocation,cropimages_save):
#b=1
crop_faces_path = frame_savelocation
list_frames = os.listdir(crop_faces_path) # dir is your directory path
number_files = len(list_frames)
rnd = random.randint(1, number_files)
print("random:", rnd)
image = face_recognition.load_image_file(frame_savelocation + "/" + str(rnd) + ".jpg")
#pil_image.save("Datasets/randomimg" + "/" + str(b) + ".jpg")
#b=b+1
# Find all the faces in the image
face_locations = face_recognition.face_locations(image)
check = os.listdir(cropimages_save) # dir is your directory path
already_prsntimg = len(check)
a = 1+already_prsntimg
for face_location in face_locations:
# Print the location of each face in this image
top, right, bottom, left = face_location
# print("A face is located at pixel location Top: {}, Left: {}, Bottom: {}, Right: {}".format(top, left, bottom, right))
# You can access the actual face itself like this:
face_image = image[top:bottom, left:right]
pil_image = Image.fromarray(face_image)
# pil_image.show()
pil_image.save(cropimages_save + "/" + str(a) + ".jpg")
a = a + 1
print("--> Images saved successfully...!!!")
# a=a+len(face_locations)
return

You can use os.chdir('output') to change the working directory to the output directory and then write the image. Then to return to the original directory to pick your random images use os.chdir('../').

Python FTP Upload calling variable

I'm uploading a file to the ftp server, the actual settings for the upload are correct but it isn't uploading the correct filename, it is uploading filename as the actual name of the file instead of capture......
#!/usr/bin/python
#
# Lightweight Motion Detection using python picamera libraries
# based on code from raspberry pi forum by user utpalc
# modified by Claude Pageau for this working example
# ------------------------------------------------------------
# original code on github https://github.com/pageauc/picamera-motion
# This is sample code that can be used for further development
verbose = True
if verbose:
print "Loading python libraries ....."
else:
print "verbose output has been disabled verbose=False"
import picamera
import picamera.array
import datetime
import time
import ftplib
from PIL import Image
from PIL import ImageFont
from PIL import ImageDraw
from fractions import Fraction
#Constants
SECONDS2MICRO = 1000000 # Constant for converting Shutter Speed in Seconds to Microseconds
# User Customizable Settings
imageDir = "images"
imagePath = "/home/pi/pimotion/" + imageDir
imageNamePrefix = 'capture-' # Prefix for all image file names. Eg front-
imageWidth = 1980
imageHeight = 1080
imageVFlip = False # Flip image Vertically
imageHFlip = False # Flip image Horizontally
imagePreview = False
numberSequence = False
threshold = 10 # How Much pixel changes
sensitivity = 100 # How many pixels change
nightISO = 800
nightShutSpeed = 6 * SECONDS2MICRO # seconds times conversion to microseconds constant
# Advanced Settings not normally changed
testWidth = 100
testHeight = 75
def checkImagePath(imagedir):
# Find the path of this python script and set some global variables
mypath=os.path.abspath(__file__)
baseDir=mypath[0:mypath.rfind("/")+1]
baseFileName=mypath[mypath.rfind("/")+1:mypath.rfind(".")]
# Setup imagePath and create folder if it Does Not Exist.
imagePath = baseDir + imagedir # Where to save the images
# if imagePath does not exist create the folder
if not os.path.isdir(imagePath):
if verbose:
print "%s - Image Storage folder not found." % (progName)
print "%s - Creating image storage folder %s " % (progName, imagePath)
os.makedirs(imagePath)
return imagePath
def takeDayImage(imageWidth, imageHeight, filename):
if verbose:
print "takeDayImage - Working ....."
with picamera.PiCamera() as camera:
camera.resolution = (imageWidth, imageHeight)
# camera.rotation = cameraRotate #Note use imageVFlip and imageHFlip variables
if imagePreview:
camera.start_preview()
camera.vflip = imageVFlip
camera.hflip = imageHFlip
# Day Automatic Mode
camera.exposure_mode = 'auto'
camera.awb_mode = 'auto'
camera.capture(filename)
sftp = ftplib.FTP('ftpdomainname','myftpusername','myftppassword') # Connect
fp = open(filename) # file to send
sftp.storbinary('STOR filename', fp) # Send the file
fp.close() # Close file and FTP
sftp.quit()
if verbose:
print "takeDayImage - Captured %s" % (filename)
return filename
def takeNightImage(imageWidth, imageHeight, filename):
if verbose:
print "takeNightImage - Working ....."
with picamera.PiCamera() as camera:
camera.resolution = (imageWidth, imageHeight)
if imagePreview:
camera.start_preview()
camera.vflip = imageVFlip
camera.hflip = imageHFlip
# Night time low light settings have long exposure times
# Settings for Low Light Conditions
# Set a frame rate of 1/6 fps, then set shutter
# speed to 6s and ISO to approx 800 per nightISO variable
camera.framerate = Fraction(1, 6)
camera.shutter_speed = nightShutSpeed
camera.exposure_mode = 'off'
camera.iso = nightISO
# Give the camera a good long time to measure AWB
# (you may wish to use fixed AWB instead)
time.sleep(10)
camera.capture(filename)
if verbose:
print "checkNightMode - Captured %s" % (filename)
return filename
def takeMotionImage(width, height, daymode):
with picamera.PiCamera() as camera:
time.sleep(1)
camera.resolution = (width, height)
with picamera.array.PiRGBArray(camera) as stream:
if daymode:
camera.exposure_mode = 'auto'
camera.awb_mode = 'auto'
else:
# Take Low Light image
# Set a framerate of 1/6 fps, then set shutter
# speed to 6s and ISO to 800
camera.framerate = Fraction(1, 6)
camera.shutter_speed = nightShutSpeed
camera.exposure_mode = 'off'
camera.iso = nightISO
# Give the camera a good long time to measure AWB
# (you may wish to use fixed AWB instead)
time.sleep( 10 )
camera.capture(stream, format='rgb')
return stream.array
def scanIfDay(width, height, daymode):
data1 = takeMotionImage(width, height, daymode)
while not motionFound:
data2 = takeMotionImage(width, height, daymode)
pCnt = 0L;
diffCount = 0L;
for w in range(0, width):
for h in range(0, height):
# get the diff of the pixel. Conversion to int
# is required to avoid unsigned short overflow.
diff = abs(int(data1[h][w][1]) - int(data2[h][w][1]))
if diff > threshold:
diffCount += 1
if diffCount > sensitivity:
break; #break outer loop.
if diffCount > sensitivity:
motionFound = True
else:
# print "Sum of all pixels=", pxCnt
data2 = data1
return motionFound
def scanMotion(width, height, daymode):
motionFound = False
data1 = takeMotionImage(width, height, daymode)
while not motionFound:
data2 = takeMotionImage(width, height, daymode)
diffCount = 0L;
for w in range(0, width):
for h in range(0, height):
# get the diff of the pixel. Conversion to int
# is required to avoid unsigned short overflow.
diff = abs(int(data1[h][w][1]) - int(data2[h][w][1]))
if diff > threshold:
diffCount += 1
if diffCount > sensitivity:
break; #break outer loop.
if diffCount > sensitivity:
motionFound = True
else:
data2 = data1
return motionFound
def getFileName(imagePath, imageNamePrefix, currentCount):
rightNow = datetime.datetime.now()
if numberSequence :
filename = imagePath + "/" + imageNamePrefix + str(currentCount) + ".jpg"
else:
filename = "%s/%s%04d%02d%02d-%02d%02d%02d.jpg" % ( imagePath, imageNamePrefix ,rightNow.year, rightNow.month, rightNow.day, rightNow.hour, rightNow.minute, rightNow.second)
return filename
def motionDetection():
print "Scanning for Motion threshold=%i sensitivity=%i ......" % (threshold, sensitivity)
isDay = True
currentCount= 1000
while True:
if scanMotion(testWidth, testHeight, isDay):
filename = getFileName(imagePath, imageNamePrefix, currentCount)
if numberSequence:
currentCount += 1
if isDay:
takeDayImage( imageWidth, imageHeight, filename )
else:
takeNightImage( imageWidth, imageHeight, filename )
if __name__ == '__main__':
try:
motionDetection()
finally:
print ""
print "+++++++++++++++"
print "Exiting Program"
print "+++++++++++++++"
print ""

Instead of 'STOR filename', use the actual name of the file
sftp.storbinary('STOR ' + filename, fp)