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vehicle_counting.py
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vehicle_counting.py
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#----------------------------------------------
#--- Author : Ahmet Ozlu
#--- Mail : [email protected]
#--- Date : 27th January 2018
#----------------------------------------------
# Imports
import tensorflow as tf
# Object detection imports
from utils import backbone
from api import object_counting_api
input_video = "traffic_video.mp4"
# By default I use an "SSD with Mobilenet" model here. See the detection model zoo (https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md) for a list of other models that can be run out-of-the-box with varying speeds and accuracies.
detection_graph, category_index = backbone.set_model('inference_graph', 'labelmap1.pbtxt')
is_color_recognition_enabled = 1 # set it to 1 for enabling the color prediction for the detected objects
roi = 385 # roi line position
deviation = 5 # the constant that represents the object counting area
w, h, f = object_counting_api.cumulative_object_counting_y_axis(input_video, detection_graph, category_index, is_color_recognition_enabled, roi, deviation) # counting all the objects
##print(w)
##print(h)
##print(f)