I have a stereo camera connected to a Raspberry Pi. I want to get images off it, compress them, and send them to a PC continuously. I am trying to use MMAL for this.
I have this code to test it out:
from picamera import mmal, mmalobj
import cv2
import io
from threading import Event
finished = Event() # triggered whenever it finishes compressing an image
image = cv2.imread('image.png')
image = cv2.resize(image, (3200, 1300))
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
encoder = mmalobj.MMALImageEncoder()
encoder.inputs[0].format = mmal.MMAL_ENCODING_I420
encoder.inputs[0].framesize = (3200, 1300)
encoder.inputs[0].commit()
encoder.outputs[0].copy_from(encoder.inputs[0])
encoder.outputs[0].format = mmal.MMAL_ENCODING_JPEG
encoder.outputs[0].commit()
encoder.outputs[0].params[mmal.MMAL_PARAMETER_JPEG_Q_FACTOR] = 90
def image_callback(port, buf):
jpg_data.write(buf.data)
if bool(buf.flags & mmal.MMAL_BUFFER_HEADER_FLAG_FRAME_END):
finished.set()
return True
return False
# perform compression on the image 100 times
for i in range(100):
finished.clear()
encoder.inputs[0].enable(lambda port, buf: True)
encoder.outputs[0].enable(image_callback)
jpg_data = io.BytesIO()
buf = encoder.inputs[0].get_buffer()
buf.data = image[:]
encoder.inputs[0].send_buffer(buf)
finished.wait()
jpg_data.close()
encoder.inputs[0].disable()
encoder.outputs[0].disable()
This only works if I disable and reenable the ports on every iteration. However, it is slower than just using OpenCV:
import cv2
import io
image = cv2.imread('image.png')
image = cv2.resize(image, (3200, 1300))
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# perform compression on the image 100 times
for i in range(100):
success, buffer = cv2.imencode(".jpg", image)
io_buffer = io.BytesIO(buffer)
data = io_buffer.read()
Also, I found that the disabling and reenabling was taking up about half the time. Does anyone know why this is happening, and if there is a faster way? Thanks.
Related
I'm writing a python script to perform camera calibration with OpenCV.
I found that the cv2.findChessboardCorners function may take very long to run on certain images.
I would therefore like to be able to stop the function after a certain period of time has passed, and move on to the next image.
How do I do that?
for fname in images:
img = cv2.imread(fname)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, corners = cv2.findChessboardCorners(gray, (20, 17), None)
You could use Pebble as a multiprocessing library, which allows scheduling tasks. The code below also uses multiple threads for the processing:
from pebble import ProcessPool
from concurrent.futures import TimeoutError
import cv2
import glob
import os
CALIB_FOLDER = "path/to/folder"
# chessboard size
W = 10
H = 7
def f(fname):
img = cv2.imread(fname)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Find the chessboard corners
ret, corners = cv2.findChessboardCorners(gray, (W-1, H-1), None)
return ret, corners
calib_imgs = glob.glob(os.path.join(CALIB_FOLDER, "*.jpg"))
calib_imgs = sorted(calib_imgs)
futures = []
with ProcessPool(max_workers=6) as pool:
for fname in calib_imgs:
future = pool.schedule(f, args=[fname], timeout=10)
futures.append(future)
for idx, future in enumerate(futures):
try:
ret, corners = future.result() # blocks until results are ready
print(ret)
except TimeoutError as error:
print("{} skipped. Took longer than {} seconds".format(calib_imgs[idx], error.args[1]))
except Exception as error:
print("Function raised %s" % error)
print(error.traceback) # traceback of the function
Hi I have just started with holoviews and I am trying to prepare a small streaming video app using holoviews, opencv. I have very limited experience with tornado and async programming.
from holoviews.streams import Pipe, Buffer
from tornado.ioloop import IOLoop
from tornado import gen
import cv2
#gen.coroutine
def f():
pipe = Pipe(data=[])
#print(pipe)
vd = cv2.VideoCapture("TestVideo.mp4")
width = int(vd.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(vd.get(cv2.CAP_PROP_FRAME_HEIGHT))
frames = int(vd.get(cv2.CAP_PROP_FRAME_COUNT))
print("Hello")
for i in range(frames):
ret, frame = vd.read()
#print(i)
try:
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
gen.sleep(10000000000)
pipe.send(rgb[:])
#print(str(i)+'x')
except:
#print(str(i)+'Error')
print("Error at Frame:"+str(i))
pass
vd.release()
cv2.destroyAllWindows()
IOLoop.current().add_callback(f)
hv.DynamicMap(hv.RGB, streams=[pipe])
I am not getting running/streaming updates. I just get a single image with last frame. Can somebody help me with figuring out my mistake here
Apart from the comment about gen.sleep taking the time in seconds, you need want to write your callback as a generator. Something like this should do it:
from holoviews.streams import Pipe, Buffer
from tornado.ioloop import IOLoop
from tornado import gen
import cv2
#gen.coroutine
def f():
vd = cv2.VideoCapture("TestVideo.mp4")
width = int(vd.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(vd.get(cv2.CAP_PROP_FRAME_HEIGHT))
frames = int(vd.get(cv2.CAP_PROP_FRAME_COUNT))
while frames > 0:
ret, frame = vd.read()
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
pipe.send(rgb)
frames -= 1
yield gen.sleep(1)
vd.release()
cv2.destroyAllWindows()
pipe = Pipe(data=[])
IOLoop.current().add_callback(f)
hv.DynamicMap(hv.RGB, streams=[pipe])
Thank you #philippjfr
In the end I got something workable using streamz python library . However this approach works. This is my working solution based on above approach.
```
import numpy as np
import pandas as pd
import holoviews as hv
hv.extension('bokeh', 'matplotlib')
from holoviews.streams import Pipe, Buffer
from tornado.ioloop import IOLoop
from tornado import gen
import cv2
#gen.coroutine
def f():
width = int(vd.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(vd.get(cv2.CAP_PROP_FRAME_HEIGHT))
frames = int(vd.get(cv2.CAP_PROP_FRAME_COUNT))
while frames > 0:
ret, frame = vd.read()
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
frames -= 1
yield pipe.send(rgb)
vd.release()
cv2.destroyAllWindows()
vd = cv2.VideoCapture("TestVideo.mp4")
ret, frame0 = vd.read()
rgb = cv2.cvtColor(frame0, cv2.COLOR_BGR2RGBA)
pipe = Pipe(data=rgb)
#pipe = Pipe(data=[])
IOLoop.current().add_callback(f)
hv.DynamicMap(hv.RGB, streams=[pipe])
```
I'm trying to load an image with OPENCV from an io.BytesIO() structure.
Originally, the code loads the image with PIL, like below:
image_stream = io.BytesIO()
image_stream.write(connection.read(image_len))
image_stream.seek(0)
image = Image.open(image_stream)
print('Image is %dx%d' % image.size)
I tried to open with OPENCV like that:
image_stream = io.BytesIO()
image_stream.write(connection.read(image_len))
image_stream.seek(0)
img = cv2.imread(image_stream,0)
cv2.imshow('image',img)
But it seems that imread doesn't deal with BytesIO(). I'm getting an error.
I'm using OPENCV 3.3 and Python 2.7. Please, could someone help me?
Henrique
Try this:
import numpy as np
import cv2 as cv
import io
image_stream = io.BytesIO()
image_stream.write(connection.read(image_len))
image_stream.seek(0)
file_bytes = np.asarray(bytearray(image_stream.read()), dtype=np.uint8)
img = cv.imdecode(file_bytes, cv.IMREAD_COLOR)
The answer delivered by arrybn, worked for me. It was only necessary to add a cv2.waitkey(1) after cv2.imshow. Here is the code:
Server Side:
import io
import socket
import struct
import cv2
import numpy as np
server_socket = socket.socket()
server_socket.bind(('0.0.0.0', 8000))
server_socket.listen(0)
connection = server_socket.accept()[0].makefile('rb')
cv2.namedWindow("Image", cv2.WINDOW_NORMAL)
try:
while True:
image_len = struct.unpack('<L', connection.read(struct.calcsize('<L')))[0]
if not image_len:
break
image_stream = io.BytesIO()
image_stream.write(connection.read(image_len))
image_stream.seek(0)
file_bytes = np.asarray(bytearray(image_stream.read()), dtype=np.uint8)
img = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
cv2.imshow("Image", img)
cv2.waitKey(1)
finally:
connection.close()
server_socket.close()
Based on the example Capturing to a network stream
I have written a code which works fine for a recorded video or video from webcam of my laptop.. but i need it to work with video directly from my phone.. Now i have been able to get video from phone and show it through python. But i need frames of this video to apply OpticalFlow function on it. (calcOpticalFlowFarneback).. Here's my two codes. i'll be thankful for your help.
This is code for getting video from android phone's camera to python
import cv2
import urllib2
import numpy as np
import sys
host = "192.168.1.2:8080"
if len(sys.argv)>1:
host = sys.argv[1]
hoststr = 'http://' + host + '/video'
print 'Streaming ' + hoststr
stream=urllib2.urlopen(hoststr)
bytes=''
while True:
bytes+=stream.read(1024)
a = bytes.find('\xff\xd8')
b = bytes.find('\xff\xd9')
if a!=-1 and b!=-1:
jpg = bytes[a:b+2]
bytes= bytes[b+2:]
i = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8),cv2.IMREAD_COLOR)
cv2.imshow(hoststr,i)
if cv2.waitKey(1) ==27:
exit(0)
And this one is relevant portion for motion flow, notice i need frames from video
vid=cv2.VideoCapture('vidaflv.flv')
ret, frame = vid.read()
imgrayp = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
while True:
ret, frame = vid.read()
if ret:
imgray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(imgrayp,imgray,None,0.5,3,15,3,5,1.2,0)
cv2.imshow('Optical flow',draw_flow(frame,flow))
imgrayp=imgray
if cv2.waitKey(1)==ord('e'):
break
what i can't figure out is how to get a frame from live stream video code to put in my optical flow fuction..
Withourt being able to test this, I'd try something like:
import cv2
import urllib2
import numpy as np
import sys
host = "192.168.1.2:8080"
if len(sys.argv)>1:
host = sys.argv[1]
hoststr = 'http://' + host + '/video'
print 'Streaming ' + hoststr
stream=urllib2.urlopen(hoststr)
bytes=''
FirstTime=True
while True:
bytes+=stream.read(1024)
a = bytes.find('\xff\xd8')
b = bytes.find('\xff\xd9')
if a!=-1 and b!=-1:
jpg = bytes[a:b+2]
bytes= bytes[b+2:]
i = cv2.imdecode(np.fromstring(jpg, dtype=np.uint8),cv2.IMREAD_COLOR)
if FirstTime=True:
FirstTime=False
imgrayp = cv2.cvtColor(i,cv2.COLOR_BGR2GRAY)
imgray = cv2.cvtColor(i,cv2.COLOR_BGR2GRAY)
flow = cv2.calcOpticalFlowFarneback(imgrayp,imgray,None,0.5,3,15,3,5,1.2,0)
cv2.imshow('Optical flow',draw_flow(frame,flow))
if cv2.waitKey(1) ==27:
exit(0)
I am working with opencv and have two video source. I am using the following code. The code works sometimes and sometimes it does not work. Is there a problem with my code. How can I make the amends...
import cv2
Channel0 = cv2.VideoCapture(0)
IsOpen0, Image0 = Channel0.read()
Channel1 = cv2.VideoCapture(1)
IsOpen1, Image1 = Channel1.read()
while IsOpen0 and IsOpen1:
IsOpen0, Image0 = Channel0.read()
IsOpen1, Image1 = Channel1.read()
cv2.imshow("Webcamera",Image0)
cv2.imshow("Panasonic",Image1)
cv2.waitKey(10)
PS It always works when I use only one video source.
I think I figured out my error. For some reason the following code works. It must have been problem with threading...
import thread
import time
import cv2
def Webcamera():
Channel0 = cv2.VideoCapture(0)
IsOpen0, Image0 = Channel0.read()
while IsOpen0:
IsOpen0, Image0 = Channel0.read()
cv2.imshow("Webcamera",Image0)
cv2.waitKey(10)
if not IsOpen0:
time.delay(0.5)
print "Error opening Web camera"
def Panasonic():
Channel1 = cv2.VideoCapture(1)
IsOpen1, Image1 = Channel1.read()
while IsOpen1:
IsOpen1, Image1 = Channel1.read()
cv2.imshow("Panasonic",Image1)
cv2.waitKey(10)
if not IsOpen1:
time.sleep(0.5)
print "Error opening Panasonic"
try:
thread.start_new_thread(Webcamera,())
thread.start_new_thread(Panasonic,())
except:
print "Error: unable to start thread"
while 1:
pass