SA-Kenan/02_Kameraaufnahme/Rest/mp_raspividyuv_fast_rgb.py

# This script uses multi processing and raspividyuv to capture frames @35 fps with canny edge detection
# To-Do:
#   -set parameter for camera
#   -typos and uniformity
#   -comment things better and make more steps for easier understanding for non-python-people (or maybe proficiency level beginner)
#   -capture led strips and save video
#   -How about OV-Sensor? because putting camera in sensor mode 4 and requesting image with less resolution drops fps.
#   -Ist blitzen auch bei diesem skript da??!?!?!??!?

import cv2 as cv
import numpy as np
import subprocess as sp
import time
import atexit

from fractions import Fraction

max_frames =500

N_frames = 0

# Video capture parameters
(w,h) = (416,320) # height must be multiple of 16 and width multiple of 16
colour_channels = 3
bytesPerFrame = w * h * colour_channels
fps = 30 # setting to 250 will request the maximum framerate possible

sensor_mode = 4


AWB_MODE = 'off'  # Auto white balance mode
AWB_GAINS = f"{485/256},{397/256}"  # White Balance Gains to have colours read correctly: (red, blue)
ISO = 100  # ISO value
EXPOSURE_MODE = 'off'

shutterspeed = 20000

# "raspividyuv" is the command that provides camera frames in YUV format
#  "--output -" specifies stdout as the output
#  "--timeout 0" specifies continuous video
#  "--luma" discards chroma channels, only luminance is sent through the pipeline
# see "raspividyuv --help" for more information on the parameters
# videoCmd = "raspividyuv -w "+str(w)+" -h "+str(h)+" --output - --timeout 0 --framerate "+str(fps)+" --rgb --nopreview --mode "+str(sensor_mode)
videoCmd = (f"raspividyuv -w {w} -h {h} --output - --timeout 0 --framerate {fps} --rgb --nopreview "
            f"--mode {sensor_mode} --awb {AWB_MODE} -awbg {AWB_GAINS} --ISO {ISO} --exposure {EXPOSURE_MODE} -ss {shutterspeed}")

    # with sensor mode 38 fps instead of 72 fps -->  How about Camera OV-Sensor?
# videoCmd = "raspividyuv -w "+str(w)+" -h "+str(h)+" --output - --timeout 0 --framerate "+str(fps)+" --rgb --nopreview"
videoCmd = videoCmd.split() # Popen requires that each parameter is a separate string

cameraProcess = sp.Popen(videoCmd, stdout=sp.PIPE) # start the camera
atexit.register(cameraProcess.terminate) # this closes the camera process in case the python scripts exits unexpectedly

# wait for the first frame and discard it (only done to measure time more accurately)
rawStream = cameraProcess.stdout.read(bytesPerFrame)

print("Start...")

start_time = time.time()

while True:
    cameraProcess.stdout.flush() # discard any frames that we were not able to process in time

    frame = np.frombuffer(cameraProcess.stdout.read(bytesPerFrame), dtype=np.uint8) # raw NumPy array without JPEG encoding

    if frame.size != bytesPerFrame:
        print("Error: Camera stream closed unexpectedly")
        break
    frame.shape = (h,w,colour_channels) # set dimensions for numpy array --> from (921600,) to (480,640,3)


    # do the processing here with OpenCV

    r,g,b = cv.split(frame)  # OpenCV works with bgr. Image is also speciefied to be captured in bgr.

    frame = cv.cvtColor(frame,cv.COLOR_BGR2RGB)  # convert frame to rgb

    N_frames += 1

    #put text
    font = cv.FONT_HERSHEY_SIMPLEX  # font
    fontScale = 1                   # fontScale
    color = (255, 255, 255)         # Font colour in BGR
    thickness = 1                   # Line thickness in px

    # set text position
    frame_width = int(frame.shape[1])
    frame_height = int(frame.shape[0])
    text_start_position_Y = int(round(frame_height*0.12))  # start position of text in pixels 12 % of frame height
    text_linespacing = 50  # line spacing between two strings in pixels
    # text_start_position_X = int(frame_width/4) # start text from 1/4 of image width
    text_start_position_X = int(0) # start text from left edge of image
    pos_1 = (text_start_position_X, text_start_position_Y) 
    text_line_1 = f"Frame: {N_frames}"
    cv.putText(frame, text_line_1, pos_1, font, fontScale, color, thickness, cv.LINE_AA)

    # if N_frames > max_frames: break #if i deactivate cv.imshow i can control end of program with this parameter.


    cv.imshow("Current Frame", frame)  # display the image
    cv.imshow("b", b)
    cv.imshow("g", g)
    cv.imshow("r", r)
    pressed_key = cv.waitKey(1) & 0xff
    if pressed_key == ord('q'):
        break

    

cv.destroyAllWindows()


end_time = time.time()

cameraProcess.terminate() # stop the camera


elapsed_seconds = end_time-start_time
print(f"Finish! Result: {(N_frames/elapsed_seconds)} fps")