I am trying to save images from the Raspi cameras connected to my Jetson nano. My Code is below. However, the code shows that it is saving the files, but no matter which method I try I cannot find the images. Thanks for your help. I've included a smaller snippet of just the while loop itself so it will be easier for you all to refer to.
While loop:
while True:
_ , left_image=left_camera.read()
_ , right_image=right_camera.read()
camera_images = np.hstack((left_image, right_image))
cv2.imshow("CSI Cameras", camera_images)
t1 = datetime.now()
cntdwn_timer = countdown - int ((t1-t2).total_seconds())
# If cowntdown is zero - let's record next image
if cntdwn_timer == -1:
counter += 1
filename = './scenes/scene_'+ str(counter) + 'x'+'_'+ '.png'
#img = cv2.imread(camera_images)
#cv2.imwrite(os.path.join(os.path.expanduser('~'),'CSI-Camera', filename), camera_images)
cv2.imwrite('/home/aryan/CSI-Camera/{}'.format(filename), camera_images)
print (' monkey'+filename)
t2 = datetime.now()
time.sleep(1)
cntdwn_timer = 0 # To avoid "-1" timer display
next
# This also acts as
keyCode = cv2.waitKey(30) & 0xFF
# Stop the program on the ESC key
if keyCode == 27:
break
left_camera.stop()
left_camera.release()
right_camera.stop()
right_camera.release()
cv2.destroyAllWindows()
import cv2
import threading
import numpy as np
import time
from datetime import datetime
# gstreamer_pipeline returns a GStreamer pipeline for capturing from the CSI camera
# Flip the image by setting the flip_method (most common values: 0 and 2)
# display_width and display_height determine the size of each camera pane in the window on the screen
left_camera = None
right_camera = None
#PiCam
# Photo session settings
total_photos = 30 # Number of images to take
countdown = 5 # Interval for count-down timer, seconds
font=cv2.FONT_HERSHEY_SIMPLEX # Cowntdown timer font
class CSI_Camera:
def __init__ (self) :
# Initialize instance variables
# OpenCV video capture element
self.video_capture = None
# The last captured image from the camera
self.frame = None
self.grabbed = False
# The thread where the video capture runs
self.read_thread = None
self.read_lock = threading.Lock()
self.running = False
def open(self, gstreamer_pipeline_string):
try:
self.video_capture = cv2.VideoCapture(
gstreamer_pipeline_string, cv2.CAP_GSTREAMER
)
except RuntimeError:
self.video_capture = None
print("Unable to open camera")
print("Pipeline: " + gstreamer_pipeline_string)
return
# Grab the first frame to start the video capturing
self.grabbed, self.frame = self.video_capture.read()
def start(self):
if self.running:
print('Video capturing is already running')
return None
# create a thread to read the camera image
if self.video_capture != None:
self.running=True
self.read_thread = threading.Thread(target=self.updateCamera)
self.read_thread.start()
return self
def stop(self):
self.running=False
self.read_thread.join()
def updateCamera(self):
# This is the thread to read images from the camera
while self.running:
try:
grabbed, frame = self.video_capture.read()
with self.read_lock:
self.grabbed=grabbed
self.frame=frame
except RuntimeError:
print("Could not read image from camera")
# FIX ME - stop and cleanup thread
# Something bad happened
def read(self):
with self.read_lock:
frame = self.frame.copy()
grabbed=self.grabbed
return grabbed, frame
def release(self):
if self.video_capture != None:
self.video_capture.release()
self.video_capture = None
# Now kill the thread
if self.read_thread != None:
self.read_thread.join()
# Currently there are setting frame rate on CSI Camera on Nano through gstreamer
# Here we directly select sensor_mode 3 (1280x720, 59.9999 fps)
def gstreamer_pipeline(
sensor_id=0,
sensor_mode=3,
capture_width=1280,
capture_height=720,
display_width=1280,
display_height=720,
framerate=30,
flip_method=0,
):
return (
"nvarguscamerasrc sensor-id=%d sensor-mode=%d ! "
"video/x-raw(memory:NVMM), "
"width=(int)%d, height=(int)%d, "
"format=(string)NV12, framerate=(fraction)%d/1 ! "
"nvvidconv flip-method=%d ! "
"video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
"videoconvert ! "
"video/x-raw, format=(string)BGR ! appsink"
% (
sensor_id,
sensor_mode,
capture_width,
capture_height,
framerate,
flip_method,
display_width,
display_height,
)
)
def start_cameras():
left_camera = CSI_Camera()
left_camera.open(
gstreamer_pipeline(
sensor_id=0,
sensor_mode=3,
flip_method=0,
display_height=540,
display_width=960,
)
)
left_camera.start()
right_camera = CSI_Camera()
right_camera.open(
gstreamer_pipeline(
sensor_id=1,
sensor_mode=3,
flip_method=0,
display_height=540,
display_width=960,
)
)
right_camera.start()
cv2.namedWindow("CSI-AV Cameras", cv2.WINDOW_AUTOSIZE)
if (
not left_camera.video_capture.isOpened()
or not right_camera.video_capture.isOpened()
):
# Cameras did not open, or no camera attached
print("Unable to open any cameras")
# TODO: Proper Cleanup
SystemExit(0)
counter = 0
t2 = datetime.now()
#Main stuff here
while True:
_ , left_image=left_camera.read()
_ , right_image=right_camera.read()
camera_images = np.hstack((left_image, right_image))
cv2.imshow("CSI Cameras", camera_images)
t1 = datetime.now()
cntdwn_timer = countdown - int ((t1-t2).total_seconds())
# If cowntdown is zero - let's record next image
if cntdwn_timer == -1:
counter += 1
filename = './scenes/scene_'+ str(counter) + 'x'+'_'+ '.png'
#img = cv2.imread(camera_images)
#cv2.imwrite(os.path.join(os.path.expanduser('~'),'CSI-Camera', filename), camera_images)
cv2.imwrite('/home/aryan/CSI-Camera/{}'.format(filename), camera_images)
print (' monkey'+filename)
t2 = datetime.now()
time.sleep(1)
cntdwn_timer = 0 # To avoid "-1" timer display
next
# This also acts as
keyCode = cv2.waitKey(30) & 0xFF
# Stop the program on the ESC key
if keyCode == 27:
break
left_camera.stop()
left_camera.release()
right_camera.stop()
right_camera.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
start_cameras()
Put breakpoint on line where you want to save image. Inspect image you want to save:
Does it have data inside?
Does it have camera_images.shape ?
What is return value of cv2.imwrite function?
Does path you are trying to write really exist?
Did you appended .png or .jpg ?
Related
My goal is to get 1280x1280 frame from nvarguscamerasrc. The problem is that nvarguscamerasrc scaled the 3840x2160 frame to 1280x720. The consequence is that the bottom of the frame is always black.
JetsonCamera.py
def gstreamer_pipeline(
# Issue: the sensor format used by Raspberry Pi 4B and NVIDIA Jetson Nano B01 are different
# in Raspberry Pi 4B, this command
# $ libcamera-still --width 1280 --height 1280 --mode 1280:1280
# uses sensor format 2328x1748.
# However, v4l2-ctl --list-formats-ext do not have such format.
capture_width=1920,
capture_height=1080,
display_width=640,
display_height=360,
framerate=21,
flip_method=0,
):
return (
"nvarguscamerasrc ! "
"video/x-raw(memory:NVMM), "
"width=(int)%d, height=(int)%d, "
"format=(string)NV12, framerate=(fraction)%d/1 ! "
"nvvidconv flip-method=%d ! "
"video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
"videoconvert ! "
"video/x-raw, format=(string)BGR ! appsink"
% (
capture_width,
capture_height,
framerate,
flip_method,
display_width,
display_height,
)
)
class Camera(object):
frame_reader = None
cap = None
previewer = None
def __init__(self, width=640, height=360):
self.open_camera(width, height)
def open_camera(self, width=640, height=360):
self.cap = cv2.VideoCapture(gstreamer_pipeline(flip_method=0, display_width=width, display_height=height), cv2.CAP_GSTREAMER)
if not self.cap.isOpened():
raise RuntimeError("Failed to open camera!")
if self.frame_reader == None:
self.frame_reader = FrameReader(self.cap, "")
self.frame_reader.daemon = True
self.frame_reader.start()
def getFrame(self, timeout = None):
return self.frame_reader.getFrame(timeout)
class FrameReader(threading.Thread):
queues = []
_running = True
camera = None
def __init__(self, camera, name):
threading.Thread.__init__(self)
self.name = name
self.camera = camera
def run(self):
while self._running:
_, frame = self.camera.read()
while self.queues:
queue = self.queues.pop()
queue.put(frame)
def addQueue(self, queue):
self.queues.append(queue)
def getFrame(self, timeout = None):
queue = Queue(1)
self.addQueue(queue)
return queue.get(timeout = timeout)
def stop(self):
self._running = False
main.py
exit_ = False
if __name__ == "__main__":
camera = Camera(width=1280, height=1280)
while not exit_:
global frame
frame = camera.getFrame(2000)
cv2.imshow("Test", frame)
key = cv2.waitKey(1)
if key == ord('q'):
exit_ = True
I am attempting to save the output of the code proposed here: https://www.programmersought.com/article/34317272452/
The output video is created, but when I try to reproduce the result, there is this message: 'an error occurred could not demultiplex stream'. Also, I have tried several forms to save the video; for example, I have used the shape of the frames, but it neither recognizes them. Could anyone help to figure out where I am doing wrong?
def read_video(video):
# Saliency detection algorithm
saliency_algorithm = "BinWangApr2014"
start_frame = 0
if saliency_algorithm is None or video is None:
print('Please set saliency_algorithm and video')
return
cap = cv2.VideoCapture(video)
video = cv2.VideoWriter('out_j.avi',cv2.VideoWriter_fourcc(*'XVID'), 5, (360,360))
# Set the video start frame
cap.set(cv2.CAP_PROP_POS_FRAMES, start_frame)
_, frame = cap.read()
if frame is None:
print('Please set saliency_algorithm and video')
return
image = frame.copy()
if saliency_algorithm.find("BinWangApr2014")==0:
saliency_algorithm = cv2.saliency.MotionSaliencyBinWangApr2014_create()
# set the size of the data structure
saliency_algorithm.setImagesize(image.shape[1], image.shape[0])
# Initialization
saliency_algorithm.init()
paused = False
while True:
if not paused:
_, frame = cap.read()
if frame is None:
break
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
start = cv2.getTickCount()
success, saliencyMap = saliency_algorithm.computeSaliency(frame)
duration = (cv2.getCPUTickCount() - start)/ \
cv2.getTickFrequency()
#print("computeBinaryMap cost time is: {} ms".format(duration * 1000))
video.write(frame)
#cv2.imshow('image', frame)
cv2.imshow('saliencyMap', saliencyMap*255)
c = cv2.waitKey(2)
c = chr(c) if c !=-1 else 0
if c == 'q':
break
if c == 'p':
paused = not paused
#video.write(frame)
cv2.destroyAllWindows()
video.release()
#camera.stop()
return
Thanks in advance
I am working on a project to predict the pedestrian path using a history and so on so i am using this paper and trying to run and implement the missing annotation in this
https://github.com/JunweiLiang/Multiverse/blob/master/SimAug
so i used yolov5 to solve this issue but i found that the fps is 30 and it takes a long time to process all these frames so i wanted to decrease the fps so for example it take only 2 frames per second and run the pipeline
(detection --> tracking) --> segmentation --> prediction and so on.
so basically here is what i did
import numpy as np
import cv2
import datetime
import queue
from threading import Thread
# global variables
stop_thread = False # controls thread execution
def start_capture_thread(cap, queue):
# global stop_thread
i=0
# continuously read fames from the camera
while True:
_, img = cap.read()
queue.put(img)
# cv2.imwrite('Images/frame{:d}.jpg'.format(i), img)
i=i+1
# if (stop_thread):
# break
def main():
global stop_thread
# create display window
cv2.namedWindow("webcam", cv2.WINDOW_NORMAL)
# initialize webcam capture object
cap = cv2.VideoCapture(0)
#cap = cv2.VideoCapture(0 + cv2.CAP_DSHOW)
# retrieve properties of the capture object
cap_width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
cap_height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
cap_fps = cap.get(cv2.CAP_PROP_FPS)
print('* Capture width:', cap_width)
print('* Capture height:', cap_height)
print('* Capture FPS:', cap_fps)
# create a queue
frames_queue = queue.Queue(maxsize=0)
# start the capture thread: reads frames from the camera (non-stop) and stores the result in img
t = Thread(target=start_capture_thread, args=(cap, frames_queue,), daemon=True) # a deamon thread is killed when the application exits
t.start()
# initialize time and frame count variables
last_time = datetime.datetime.now()
frames = 0
cur_fps = 0
i=0
while (True):
if (frames_queue.empty()):
continue
if i%5 !=0 :
_ = frames_queue.get()
i+=1
continue
# blocks until the entire frame is read
frames += 1
# # measure runtime: current_time - last_time
# delta_time = datetime.datetime.now() - last_time
# elapsed_time = delta_time.total_seconds()
# # compute fps but avoid division by zero
# if (elapsed_time != 0):
# cur_fps = np.around(frames / elapsed_time, 1)
# retrieve an image from the queue
img = frames_queue.get()
cv2.imwrite('Images/frame{:d}.jpg'.format(i), img)
i+=1
# for i in range(10):
# _ = frames_queue.get()
# i+=1
# TODO: process the image here if needed
# draw FPS text and display image
# if (img is not None):
# cv2.putText(img, 'FPS: ' + str(cur_fps), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2, cv2.LINE_AA)
# cv2.imshow("webcam", img)
# wait 1ms for ESC to be pressed
key = cv2.waitKey(1)
if (key == 27):
stop_thread = True
break
# release resources
cv2.destroyAllWindows()
cap.release()
if __name__ == "__main__":
main()
and it works so i want to use this in the track.py in yolov5 instead of the
dataset = LoadStreams(source, img_size=imgsz, stride=stride, auto=pt and not jit)
but i can't modify it as it used in the code like this
for frame_idx, (path, img, im0s, vid_cap, s) in enumerate(dataset):
but i couldn't full understand this line
so i wanted to modify the LoadStreams function in here https://github.com/ultralytics/yolov5/blob/master/utils/datasets.py but i am kinda stuck here
I'm trying to create a stereo vision camera on my jetson nano with 2 raspi cameras. However, I can find a lot of information and code online regarding RasPi but not jetson nano. So for example let's say I have these 2 python programs, the first for starting both cameras on Jetson nano and the second for starting both cameras on RasPi. I'm quite new to all this, so it would be great to get some advice on how I could get started on this. Thanks!
Jetson (taken from JetsonHacks):
# MIT License
# Copyright (c) 2019,2020 JetsonHacks
# See license
# A very simple code snippet
# Using two CSI cameras (such as the Raspberry Pi Version 2) connected to a
# NVIDIA Jetson Nano Developer Kit (Rev B01) using OpenCV
# Drivers for the camera and OpenCV are included in the base image in JetPack 4.3+
# This script will open a window and place the camera stream from each camera in a window
# arranged horizontally.
# The camera streams are each read in their own thread, as when done sequentially there
# is a noticeable lag
# For better performance, the next step would be to experiment with having the window display
# in a separate thread
import cv2
import threading
import numpy as np
# gstreamer_pipeline returns a GStreamer pipeline for capturing from the CSI camera
# Flip the image by setting the flip_method (most common values: 0 and 2)
# display_width and display_height determine the size of each camera pane in the window on the screen
left_camera = None
right_camera = None
class CSI_Camera:
def __init__ (self) :
# Initialize instance variables
# OpenCV video capture element
self.video_capture = None
# The last captured image from the camera
self.frame = None
self.grabbed = False
# The thread where the video capture runs
self.read_thread = None
self.read_lock = threading.Lock()
self.running = False
def open(self, gstreamer_pipeline_string):
try:
self.video_capture = cv2.VideoCapture(
gstreamer_pipeline_string, cv2.CAP_GSTREAMER
)
except RuntimeError:
self.video_capture = None
print("Unable to open camera")
print("Pipeline: " + gstreamer_pipeline_string)
return
# Grab the first frame to start the video capturing
self.grabbed, self.frame = self.video_capture.read()
def start(self):
if self.running:
print('Video capturing is already running')
return None
# create a thread to read the camera image
if self.video_capture != None:
self.running=True
self.read_thread = threading.Thread(target=self.updateCamera)
self.read_thread.start()
return self
def stop(self):
self.running=False
self.read_thread.join()
def updateCamera(self):
# This is the thread to read images from the camera
while self.running:
try:
grabbed, frame = self.video_capture.read()
with self.read_lock:
self.grabbed=grabbed
self.frame=frame
except RuntimeError:
print("Could not read image from camera")
# FIX ME - stop and cleanup thread
# Something bad happened
def read(self):
with self.read_lock:
frame = self.frame.copy()
grabbed=self.grabbed
return grabbed, frame
def release(self):
if self.video_capture != None:
self.video_capture.release()
self.video_capture = None
# Now kill the thread
if self.read_thread != None:
self.read_thread.join()
# Currently there are setting frame rate on CSI Camera on Nano through gstreamer
# Here we directly select sensor_mode 3 (1280x720, 59.9999 fps)
def gstreamer_pipeline(
sensor_id=0,
sensor_mode=3,
capture_width=1280,
capture_height=720,
display_width=1280,
display_height=720,
framerate=30,
flip_method=0,
):
return (
"nvarguscamerasrc sensor-id=%d sensor-mode=%d ! "
"video/x-raw(memory:NVMM), "
"width=(int)%d, height=(int)%d, "
"format=(string)NV12, framerate=(fraction)%d/1 ! "
"nvvidconv flip-method=%d ! "
"video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
"videoconvert ! "
"video/x-raw, format=(string)BGR ! appsink"
% (
sensor_id,
sensor_mode,
capture_width,
capture_height,
framerate,
flip_method,
display_width,
display_height,
)
)
def start_cameras():
left_camera = CSI_Camera()
left_camera.open(
gstreamer_pipeline(
sensor_id=0,
sensor_mode=3,
flip_method=0,
display_height=540,
display_width=960,
)
)
left_camera.start()
right_camera = CSI_Camera()
right_camera.open(
gstreamer_pipeline(
sensor_id=1,
sensor_mode=3,
flip_method=0,
display_height=540,
display_width=960,
)
)
right_camera.start()
cv2.namedWindow("CSI Cameras", cv2.WINDOW_AUTOSIZE)
if (
not left_camera.video_capture.isOpened()
or not right_camera.video_capture.isOpened()
):
# Cameras did not open, or no camera attached
print("Unable to open any cameras")
# TODO: Proper Cleanup
SystemExit(0)
while cv2.getWindowProperty("CSI Cameras", 0) >= 0 :
_ , left_image=left_camera.read()
_ , right_image=right_camera.read()
camera_images = np.hstack((left_image, right_image))
cv2.imshow("CSI Cameras", camera_images)
# This also acts as
keyCode = cv2.waitKey(30) & 0xFF
# Stop the program on the ESC key
if keyCode == 27:
break
left_camera.stop()
left_camera.release()
right_camera.stop()
right_camera.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
start_cameras()
RasPi (from https://github.com/realizator/stereopi-tutorial/blob/master/1_test.py):
# Copyright (C) 2019 Eugene Pomazov, <stereopi.com>, virt2real team
#
# This file is part of StereoPi tutorial scripts.
#
# StereoPi tutorial is free software: you can redistribute it
# and/or modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# StereoPi tutorial is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with StereoPi tutorial.
# If not, see <http://www.gnu.org/licenses/>.
#
# Most of this code is updated version of 3dberry.org project by virt2real
#
# Thanks to Adrian and http://pyimagesearch.com, as there are lot of
# code in this tutorial was taken from his lessons.
#
import picamera
from picamera import PiCamera
import time
import cv2
import numpy as np
import os
from datetime import datetime
# File for captured image
filename = './scenes/photo.png'
# Camera settimgs
cam_width = 1280
cam_height = 480
# Final image capture settings
scale_ratio = 0.5
# Camera resolution height must be dividable by 16, and width by 32
cam_width = int((cam_width+31)/32)*32
cam_height = int((cam_height+15)/16)*16
print ("Used camera resolution: "+str(cam_width)+" x "+str(cam_height))
# Buffer for captured image settings
img_width = int (cam_width * scale_ratio)
img_height = int (cam_height * scale_ratio)
capture = np.zeros((img_height, img_width, 4), dtype=np.uint8)
print ("Scaled image resolution: "+str(img_width)+" x "+str(img_height))
# Initialize the camera
camera = PiCamera(stereo_mode='side-by-side',stereo_decimate=False)
camera.resolution=(cam_width, cam_height)
camera.framerate = 20
camera.hflip = True
t2 = datetime.now()
counter = 0
avgtime = 0
# Capture frames from the camera
for frame in camera.capture_continuous(capture, format="bgra", use_video_port=True, resize=(img_width,img_height)):
counter+=1
t1 = datetime.now()
timediff = t1-t2
avgtime = avgtime + (timediff.total_seconds())
cv2.imshow("pair", frame)
key = cv2.waitKey(1) & 0xFF
t2 = datetime.now()
# if the `q` key was pressed, break from the loop and save last image
if key == ord("q") :
avgtime = avgtime/counter
print ("Average time between frames: " + str(avgtime))
print ("Average FPS: " + str(1/avgtime))
if (os.path.isdir("./scenes")==False):
os.makedirs("./scenes")
cv2.imwrite(filename, frame)
break
I have a function which grabs an image from a camera:
img = cam.read()
Now I want to read that image with tf.read_file,
but when I do img_raw = tf.read_file(img), it doesn't work.
This is the code for the camera class:
"""camera.py
This code implements the Camera class, which encapsulates code to
handle IP CAM, USB webcam or the Jetson onboard camera. The Camera
class is further extend to take either a video or an image file as
input.
"""
import time
import logging
import threading
import numpy as np
import cv2
def open_cam_rtsp(uri, width, height, latency):
"""Open an RTSP URI (IP CAM)."""
gst_str = ('rtspsrc location={} latency={} ! '
'rtph264depay ! h264parse ! omxh264dec ! '
'nvvidconv ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! videoconvert ! '
'appsink').format(uri, latency, width, height)
return cv2.VideoCapture(gst_str, cv2.CAP_GSTREAMER)
def open_cam_usb(dev, width, height):
"""Open a USB webcam.
We want to set width and height here, otherwise we could just do:
return cv2.VideoCapture(dev)
"""
gst_str = ('v4l2src device=/dev/video{} ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)RGB ! videoconvert ! '
'appsink').format(dev, width, height)
return cv2.VideoCapture(gst_str, cv2.CAP_GSTREAMER)
def open_cam_onboard(width, height):
"""Open the Jetson onboard camera.
On versions of L4T prior to 28.1, you might need to add
'flip-method=2' into gst_str.
"""
gst_str = ('nvcamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)2592, height=(int)1458, '
'format=(string)I420, framerate=(fraction)30/1 ! '
'nvvidconv ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! videoconvert ! '
'appsink').format(width, height)
return cv2.VideoCapture(gst_str, cv2.CAP_GSTREAMER)
def grab_img(cam):
"""This 'grab_img' function is designed to be run in the sub-thread.
Once started, this thread continues to grab a new image and put it
into the global 'img_handle', until 'thread_running' is set to False.
"""
while cam.thread_running:
if cam.args.use_image:
assert cam.img_handle is not None, 'img_handle is empty in use_image case!'
# keep using the same img, no need to update it
time.sleep(0.01) # yield CPU to other threads
else:
_, cam.img_handle = cam.cap.read()
if cam.img_handle is None:
logging.warning('grab_img(): cap.read() returns None...')
break
cam.thread_running = False
class Camera():
"""Camera class which supports reading images from theses video sources:
1. Video file
2. Image (jpg, png, etc.) file, repeating indefinitely
3. RTSP (IP CAM)
4. USB webcam
5. Jetson onboard camera
"""
def __init__(self, args):
self.args = args
self.is_opened = False
self.thread_running = False
self.img_handle = None
self.img_width = 0
self.img_height = 0
self.cap = None
self.thread = None
def open(self):
"""Open camera based on command line arguments."""
assert self.cap is None, 'Camera is already opened!'
args = self.args
if args.use_file:
self.cap = cv2.VideoCapture(args.filename)
# ignore image width/height settings here
elif args.use_image:
self.cap = 'OK'
self.img_handle = cv2.imread(args.filename)
# ignore image width/height settings here
if self.img_handle is not None:
self.is_opened = True
self.img_height, self.img_width, _ = self.img_handle.shape
elif args.use_rtsp:
self.cap = open_cam_rtsp(
args.rtsp_uri,
args.image_width,
args.image_height,
args.rtsp_latency
)
elif args.use_usb:
self.cap = open_cam_usb(
args.video_dev,
args.image_width,
args.image_height
)
else: # by default, use the jetson onboard camera
self.cap = open_cam_onboard(
args.image_width,
args.image_height
)
if self.cap != 'OK':
if self.cap.isOpened():
# Try to grab the 1st image and determine width and height
_, img = self.cap.read()
if img is not None:
self.img_height, self.img_width, _ = img.shape
self.is_opened = True
def start(self):
assert not self.thread_running
self.thread_running = True
self.thread = threading.Thread(target=grab_img, args=(self,))
self.thread.start()
def stop(self):
self.thread_running = False
self.thread.join()
def read(self):
if self.args.use_image:
return np.copy(self.img_handle)
else:
return self.img_handle
def release(self):
assert not self.thread_running
if self.cap != 'OK':
self.cap.release()
So in another python script I want to use this camera class in order to grab a image and load it with tf.read_file:
from utils.camera import Camera
import numpy as np
import cv2
import tensorflow as tf
cam = Camera(args)
cam.open()
cam.start()
img = cam.read()
img_raw = tf.read_file(img)#here read_file expects a string but I am passing img which is an array
No need to call tf.read_file(img).
ret_val, img = cam.read()
img = tf.convert_to_tensor(img, dtype=tf.float32)
img = tf.image.resize(img, (HEIGHT, WIDTH))
images = tf.expand_dims(img, axis=0) / 255.0
Results = model.predict(images)