Some help with IMAGE_VIEW_FT

Hi,

maybe i can get some help with the IMAGE VIEW FT value - imho there must be something wrong. I think the speed measured is nearly double as fast as they really drive. Heres a litte image of the road with the camera in place. Maybe the angle is the problem?

Im using the following calculation (320*45)/120 = 120 Rpi 3 with standard raspi cam.

Config looks like:

# Motion Event Settings
# =====================
IMAGE_VIEW_FT = 120     # Set the width in feet for the road width that the camera width sees 120px 45ft = (320*45)/120
SPEED_MPH = False       # Set the speed conversion  kph=False  mph=True
track_len_trig = 100   # Length of track to trigger speed photo Default=100
track_timeout = 1      # Number of seconds to wait after track End (prevents dual tracking)
event_timeout = 2      # Number of seconds to wait for next motion event before starting new track

# Camera Settings
# ===============
CAMERA_WIDTH = 320    # Image stream width for opencv motion scanning default=320
CAMERA_HEIGHT = 240    # Image stream height for opencv motion scanning  default=240
CAMERA_FRAMERATE = 75  # framerate for video stream default=35 90 max for V1 cam. V2 can be higher
CAMERA_ROTATION = 0    # Rotate camera image valid values are 0, 90, 180, 270
CAMERA_VFLIP = True   # Flip the camera image vertically if required
CAMERA_HFLIP = True   # Flip the camera image horizontally if required

Thanks in advance!!

[pageauc]

Thanks for your feedback. This is just a project I wrote for fun to tinker with. Some people re purpose the code for other things beside vehicles. One user rewrote it in java and some have written it for PC. I think another did a pedestrian counter.

Recently added support for webcam’s and did have fun figuring out how to change resolution and other features on a USB webcam on the RPI. Also did some work on makehtml.py code web page html formatting.
The project is more of a learning tool and not intended to be super accurate but with more work could be improved by optimizing for direction, background, Etc as you mention. I have a version (not on github) that I use for tracking motion and speed in any direction. As this is just a hobby I mainly do it for myself as a learning exercise. I have been retired for eleven years and non of my friends use computers for any type of content creation like music, video, imaging, writing, science, programming, design, problem solving Etc. To me this seems like a waste of brain power but each their own.
Anyway this is just my way of providing something back to society where some young person might find it and learn something that might help them. Appreciate your Comments Claude …

[afletch]

Apologies for not feeding back before, but this has slipped down my list.

I’ve had this running now for a few months and my general feeling is that there are inconsistencies in the speed reported between different vehicles. Some vehicles are very accurate and others are not. I think it depends on a few factors:

• the background against which the vehicle is moving: if the background us busy/complex then accuracy of speed is reduced (eg. good against a solid surface like a road, bad against a housing/garden backdrop)

• the colour of the vehicle this seems to make a big difference, and combines with the first item above. Where there’s a greater contrast between the moving vehicle and the background, the better the detection and more accurate the speed.

• the direction of travel This is an odd one, which I can’t explain. Even the same vehicle travelling in different directions seems to be better L-R than R-L

I expect much of the above is down to opencv and way beyond your control, but thought I’d give my feedback in any case, such that it may be useful in some way.

Thanks for your hard work