config.ini.sample

# This is an example of how you can mix config values with command line values
# This file contains arguments you may want to reuse across multiple requests
# Simply do a -c <this config file> and add any other parameters you want in CLI
# and they will be merged


username=admin
password=password
portal=https://server/zm

#If True, will first download videos and then locally process
download=True

#If True, will show progress bars
show_progress=False

# If True, only extract events that have object detection previously
# identified using zmeventserver machine learning hooks
objectonly=False

# If True, opens a useful graphical window to show whats being detected
# and how. Needs X
display=False

# Only extracts events that have at least one alarmed frame
alarmonly=True
# if alarmonly is true, will only get events with these many minimum alarmed frames
minalarmframes=2

# Writes frames only if the detection logic said it found something
relevantonly=True

# Minimum area the object that moves must occupy. Only relevant
# if you selected mixed or extract_background mode
minblendarea=500

# If you use GPU, you have two options:

# Use OpenCV's new GPU DNN support (requires OpenCV 4.2+)
# or, you need to have darknet compiled in GPU mode
# and point darknet_lib to where that compiled SO is placed

gpu=False

#If true, will ignore darknet_lib
use_opencv_dnn_cuda=True 
darknet_lib=/home/pp/fiddle/zmMagik/libdarknet_gpu.so

# If you want detections to lie inside a specified polygon
# Note that only one mask is supported for now
# doorbell
#mask=4,406 1276,411 1279,719 0,719
#driveway
#mask=69,130 604,68 646,307 1167,616 0,619

# I've found it useful to manually specific fps of videos being processed
# If you don't I'll try and guess, but its a bit random in my experience. 
# Try without it. If you get accurate results, you can keep this commented
fps=5

# How many frames will be skipped during processing. Use to make things faster
# 1 means no frames skipped
skipframes=1
# Used only for background_extraction mode. Keep this to 0.7
threshold=0.7
# Used by Yolo, if you use yolo or mixed mode. This is the minimum confidence level
# of matched objects (keep it to 0.5 to 0.9)
confidence=0.5
# How much to resize images. No need to feed in huge frames. 
resize = 0.5

# If enabled, it tries to histogram match colors of of new event 
# to blended events. I tried this while blending day and night events. It adjusts
# to the higher intensity (day). Not sure it really works well.
balanceintensity=False
#balanceintensity=True

# size of text that is written on top of objects
fontscale=0.8

# First uses opencv background extraction to detect if an object is moving. If it is moving, then run yolo on it to make sure its something that is valid
detection_type=mixed
detectpattern =  (person|car|motorbike|bus|truck|boat)

#detection_type=yolo_extraction
#detection_type=background_extraction

# you need these if you use yolo or mixed for detection
config_file=/var/lib/zmeventnotification/models/yolov3/yolov3.cfg
weights_file=/var/lib/zmeventnotification/models/yolov3/yolov3.weights
labels_file=/var/lib/zmeventnotification/models/yolov3/yolov3_classes.txt