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Vehicle counting, Classification and Axle count. Must((C++ or C#) and OpenCV)

We need a vehicle counting and classification project written in C++ or C# using OpenCV, Visual Studio 2017, Windows 10. The problem is to count and classify vehicles inside a predefined area and multi lanes. Classification shall consist of large vehicles (trucks, buses, etc.) and small vehicles (cars, Pickup trucks, motorcycles, minibus, etc.) only. Counting shall consider that the vehicles might be at zero velocity. Expert knowledge of C++ or C# and OpenCV is mandatory. Note that the input will be a 'cv::VideoCapture'. Counting performance shall be 99% and the classification performance shall be above 98%.

FHWA 13 Vehicle Classification

Class 1-

Motorcycles: All two- or three-wheeled motorized vehicles. Typical vehicles in this category have saddle-type seats and are steered by handlebars rather than wheels. This category includes motorcycles, motor scooters, mopeds, motor-powered bicycles, and three-wheeled motorcycles.

Class 2-

Passenger Cars: All sedans, coupes, and station wagons manufactured primarily for transport passengers and including those passenger cars pulling recreational or other light trailers.

Class 3-

Other Two-Axle, Four-Tire, Single Unit Vehicles: All two-axle, four-tire, vehicles other than passenger cars. Included in this classification are pickups, panels, vans, and other vehicles such as campers, motor homes, ambulances, hearses, carryalls, and minibus. Other two-axle, four-tire single unit vehicles pulling recreational or other light trailers are included in this classification.

Class 4-

Buses: All vehicles manufactured as traditional passenger-carrying buses with two axles and six tires or three or more axles. This category includes only traditional buses (including school buses) functioning as passenger-carrying vehicles. Modified buses should be considered to be trucks and be appropriately classified.

Note: In reporting information on trucks the following criteria should be used:

a. Truck tractor units traveling without a trailer will be considered single-unit trucks.

b. A truck tractor unit pulling other such units in a “saddle mount” configuration will be considered as one single unit truck and will be defined only by axles on the pulling unit.

c. Vehicles shall be defined by the number of axles in contact with the roadway. Therefore, “floating” axles are counted only when in the down position.

d. The term “trailer” includes both semi- and full trailers.

Class 5-

Two-Axle, Six-Tire, Single Unit Trucks: All vehicles on a single frame including trucks, camping, and recreational vehicles, motor homes, etc., having two axles and dual rear wheels.

Class 6-

Three-axle Single unit Trucks: All vehicles on a single frame including trucks, camping, and recreational vehicles, motor homes, etc., having three axles.

Class 7-

Four or More Axle Single Unit Trucks: All trucks on a single frame with four or more axles.

Class 8-

Four or Less Axle Single Trailer Trucks: All vehicles with four or fewer axles consisting of two units, one of which is a tractor or straight truck power unit.

Class 9-

Five-Axle Single Trailer Trucks: All five-axle vehicles consisting of two units, one of which is a tractor or straight truck power unit.

Class 10-

Six or More Axle Single Trailer Trucks: All vehicles with six or more axles consisting of two units, one of which is a tractor or straight truck power unit.

Class 11-

Five or Less Axle Multi-Trailer Trucks: All vehicles with five or fewer axles consisting of three or more units, one of which is a tractor or straight truck power unit.

Class 12-

Six-Axle Multi-Trailer Trucks: All six-axle vehicles consisting of three or more units, one of which is a tractor or straight truck power unit.

Class 13-

Seven or More Axle Multi-Trailer Trucks: All vehicles with seven or more axles consisting of three or more units, one of which is a tractor or straight truck power.

OUTPUT:

Vehicle Count, Lane 2, Truck, 4 Axle, TimeDate, Picture.

No training data, No Video.

Beceriler: C++ Programlama, Yazılım Mimarisi, OpenCV, Algoritma, C# Programlama

Daha fazlasını gör: vbulletin able send pms post count must, vehicle counting matlab, vehicle image classification matlab, vehicle counting video matlab code, matlab code vehicle counting, people count line opencv, vehicle counting using opencv, vehicle counting opencv, count face opencv, opencv vehicle counting, vehicle counting opencv python, vehicle detection using opencv c++, vehicle counting opencv code python, image processing vehicle counting using opencv, image processing vehicle counting using opencv python, vehicle counting opencv python github, opencv vehicle counting classification github

İşveren Hakkında:
( 0 değerlendirme ) Biscayne Park, United States

Proje NO: #22105868

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